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Regulatory Compliance: The Intersection of Policy and Innovation

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Regulatory Compliance: The Intersection of Policy and Innovation

Artificial intelligence stands as one of the most disruptive and transformative forces in human history. With the power to revolutionize fields such as medicine, climate science, energy storage and process automation, AI’s potential so far has shown no limit.

The same velocity that fuels innovation also magnifies it’s risk. AI systems can amplify bias, hallucinate falsehoods, or generate synthetic media indistinguishable from reality.

The growth AI of has compressed decades of progress into a handful of years. New use-cases and techniques can go from lab paper to global deployment in a single quarter. Technology advances faster than governments can legislate, creating a regulatory lag.

While executives from companies like Google, Microsoft, and OpenAI are often invited to share expertise, helping to lead conversation on ethical and technical aspects, they recognize governments are not able to move sufficiently fast enough. Absent any federal guardrails, internal efforts to police themselves were made by creating ethics frameworks and internal governance teams such as ethics boards and committees, assuaging public concerns.

As AI systems become more autonomous and integrate deeper into our daily lives, calls for safety and transparency are demanded in the public domain. Corporations on the other hand, seek to mitigate liability, staying ahead of regulatory bodies through self-regulatory practices.

GDPR was the world’s first comprehensive data privacy and protection regulation, creating the enforcement and penalty framework for EU’s AI regulatory legislation, called the AI Act.

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At the most basic level, the AI Act seeks to verify AI Systems:

  • Are not used to break any laws
  • Collect and use data legally and ethically
  • Do not discriminate a group or individual
  • Do not manipulate or deceive in any way
  • Do not invade on an individual’s privacy or cause harm
  • Are employed responsibly
  • Can be created in sandboxes, bypassing regulation, while promoting innovation

The AI Act uses a risk-based approach to regulate AI systems. This framework categorizes AI systems into the below four distinct risk levels, with proportional obligations and restrictions, defined here in more detail.

While GDPR and the AI Act share similar enforcement and penalty structures, their oversight models differ. GDPR is enforced locally by each member state’s Data Protection Authority (DPA), as opposed to each member-state Market Surveillance Authorities (MSA) enforces the AI Act, overseen centrally by the European Commission’s AI Office to maintain consistency across the EU. Both GDPR and the AI Act use a tier penalty model that increase fines for more egregious or repeated offenses, with varying percentages between the two legislations.

The United States, on the other hand, has since veered sharply from Europe’s unified structure with a new administration. President Biden’s 2023 Executive order 14110 balancing innovation and safe AI practices, promoting coordination across federal agencies.

At the start his 2025 term, one of President Trump’s first Executive Orders revoked Biden’s EO 14110, reversing, softening or simply renaming several oversight initiatives. For example, the AI Safety Institute dropping “Safety” from its name signaling a shift toward deregulation and speed.

Absent any federal legislation, individual states have begun drafting their own AI regulation, creating a disparate regulatory environment. Each state may use different definitions, enforcement mechanisms, and risk thresholds.

Private companies operating nationally are finding themselves in a maze of nuanced overlapping obligations. Because state-level laws can be aggressive, the risk for non-compliance increases even in a federally permissive administration.

Globally, AI regulation resembles a patchwork of legislation, using EU’s model as a comprehensive guide, converging on the ethos of the EU AI Act: transparency obligations, high-impact systems, and human oversight. These terms have become the lingua franca for companies and governments worldwide.

It’s the same pattern for GDPR. Europe wrote the detailed rules, and the rest of the world gravitated towards them, for lack of a cleaner alternative.

Recommendations for Responsible Adoption

1. Collaborate with industry bodies:

Engage with groups like the IAB and standards committees defining AI guidance.

2. Bring legal in early:

Translate emerging obligations into contracts, products, and data policies.

3. Audit training data:

Vet datasets for legality, bias, and provenance before they reach production.

4. Maintain human oversight:

Keep escalation paths for critical decisions and monitor models for drift.

5. Keep detailed decision logs:

Audit trails protect against both regulatory and reputational fallout.

6. Test for bias:

Treat fairness like any other QA process.

7. Build for change:

Design modular systems that can adapt as laws evolve.

8. Assess your markets:

Align AI practices with regional expectations.

9. Vet your vendors:

Accountability extends down the supply chain.

10. Use compliance tools:

Leverage readiness checkers and risk frameworks to measure exposure early.

While AdTech is not at the epicenter of the AI debate, it’s large scale data pipelines, automated decision systems and regional privacy constraints have exposed governance challenges prior to other industries.

Having dealt with the arm of the law for non-compliance, the lessons learned about transparency, bias, consent, and data ethics echo across every industry where automated decision making occurs.

AI will continue to move quickly. Legislation will try to keep up. It’s a cat and mouse game, where the future of AI governance will not come from a single regulator. It is the responsibility of companies to act with responsible principles. Regulation may lag, but responsibility doesn’t have to.

Novi AI Launches Independent AI Creation Studio Following Brand Upgrade

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Novi AI Launches Independent AI Creation Studio Following Brand Upgrade

Novi Ai

Novi AI, a generative AI–powered creative platform, has launched its new independent website, establishing itself as a standalone AI Creation Studio for images, videos, and multimodal content. The platform streamlines AI creation for individuals and teams, integrating multiple leading AI models into one workflow.

Novi AI, a generative AI–powered creative platform, has officially launched its new independent website, marking a significant brand upgrade. With this transition, Novi AI is established as a standalone AI Creation Studio for images, videos, and multimodal content, designed to support modern creative workflows for individuals and teams.

A New Chapter of Independence

The launch of the new platform marks the culmination of Novi AI’s evolution from a specialized AI initiative into a comprehensive creation platform. To better support its growing global user base and enable more focused product development, Novi AI has officially transitioned into an independent brand.

Originally incubated as part of the iMyFone AI product line, Novi AI has now completed its brand separation. The platform operates independently with its own infrastructure, technical roadmap, and long-term product vision.

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“Our transition to independence allows us to focus entirely on how creators actually use AI in real-world workflows,” said the Product Manager of Novi AI. “Rather than offering fragmented tools, we are building a unified platform that makes AI creation practical, accessible, and consistent.”

Built to Simplify AI Creation

As AI models and tools continue to evolve at a rapid pace, using them effectively has become increasingly complex. Creators often need to manage multiple platforms, interfaces, and generation processes to complete a single project.

Novi AI was developed to address this challenge by bringing essential image and video generation capabilities into a single, streamlined environment. The platform supports multiple leading AI models — such as Veo 3.1, Sora 2, Kling, Nano Banana, and Seedream — within one workflow, reducing friction and allowing users to focus on creative execution rather than technical coordination.

Redefining the AI Creation Studio

With its updated positioning, Novi AI introduces an integrated approach to AI-powered content creation. The platform is designed to deliver a consistent experience across text, image, and video formats, with tools optimized for clarity, speed, and ease of adoption.

Key capabilities currently available on the platform include:

  • AI Story-to-Video Generator: Transform long-form text—such as stories, novels, fiction or written scripts—into cinematic, animated long-form videos with structured visuals and coherent narrative flow.
  • AI Video Generator: Convert ideas or images into polished video content through a simplified, end-to-end text-to-video and image-to-video creation workflow.
  • AI Image Generator: Generate high-quality visuals from text prompts or existing images, supporting rapid iteration and creative refinement.

All features are integrated within a unified workflow, enabling seamless transitions between image and video creation while maintaining creative continuity.

Built on Experience, Focused on Real-World Work

While Novi AI now operates as an independent platform, it enters this new phase with the foundation of a mature and widely adopted product. During its earlier development, the platform supported millions of users across more than 120 countries and regions, providing valuable insight into how AI tools are applied in real-world creative and production environments.

These learnings are reflected in the independent platform through a simplified interface, consistent output quality, and tools optimized for practical use cases such as content creation, marketing assets, storytelling, and collaborative projects.

Vision for the Future

As an independent brand, Novi AI will continue developing its AIGC ecosystem with a focus on usability, reliability, and scalable creative workflows. Future updates will prioritize multi-model integration, creator-focused product refinement, and enhanced storytelling features. The platform will also continue adding tools that make advanced AI creation more accessible across diverse use cases.

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HitPaw API is Integrated by Comfy for Professional Image and Video Enhancement to Global Creators

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HitPaw API is Integrated by Comfy for Professional Image and Video Enhancement to Global Creators

HitPaw, a leader in AI-powered visual enhancement solutions, announced Comfy, a global content creation platform, is integrating its image and video enhancement API. The HitPaw and Comfy integration embeds HitPaw API into Comfy’s workflow, letting creators achieve pro-level visual enhancement in-platform. Blending HitPaw’s AI visual processing expertise with Comfy’s creator ecosystem, the partnership streamlines workflows and meets rising demand for high-quality digital visuals across digital platforms.

HitPaw Image Enhancer

Comfy integrates HitPaw Image Enhancer providing AI-powered photo enhancement, super-resolution, denoising, and generative restoration. It turns low-quality images into publish-ready visuals while preserving natural facial identity and textures.

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Key Features

  • One-click portrait and scene enhancement inside Comfy
  • Dual-model face and background pipelines for natural results
  • 2x and 4x super-resolution options
  • High-fidelity enhancement for already sharp images
  • Diffusion-based generative models for extreme recovery
  • Batch processing and API access for platform workflows

HitPaw Image Enhancer Models

  • Face Clear Model 2x and 4x: Dual-model portrait upscaling with softened facial style and sharpened background details
  • Face Natural Model 2x and 4x: Texture-preserving portrait enhancement with realistic skin detail
  • General Enhance Model 2x and 4x: Super-resolution for animals, plants, architecture, and everyday scenes
  • High Fidelity Model 2x and 4x: Premium upscaling for DSLR photos, posters, and AIGC images
  • Sharp Denoise and Detail Denoise Models: 1x denoising for mobile and camera images
  • Generative Portrait and Generative Enhance Models: Diffusion-based 1x to 4x restoration for heavily compressed images

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HitPaw Video Enhancer

Comfy integrates HitPaw Video Enhancer delivering frame-aware restoration and ultra HD upscaling. It supports single and multi-frame processing to enhance facial clarity, reduce artifacts, and maintain natural textures over time.

Key Features

  • Multi-frame face restoration for temporal consistency
  • Face-first pipelines that preserve identity and skin texture
  • GAN and diffusion models for defect repair and reconstruction
  • Ultra HD upscaling from HD to ultra HD
  • API support for automated and large-scale workflows

HitPaw Video Enhance Models

  • Face Soft Model: Face-optimized noise and blur reduction while retaining identity.
  • Portrait Restore Model: Multi-frame fusion to enhance facial detail with smooth frame transitions.
  • General Restore Model: GAN-based restoration for broad video scenarios.
  • Ultra HD Model: Premium upscaling that generates natural textures.
  • Generative Model: Diffusion-driven repair for low-resolution video reconstruction.

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LoopMe Data: Global Consumers Doubt Social Media Bans Actually Protect Young People

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LoopMe Data: Global Consumers Doubt Social Media Bans Actually Protect Young People

LoopMe | The global leader in brand performance

Widespread skepticism about effectiveness, with only 6% of Australians feeling online spaces are now safer

New research from LoopMe, the global leader in brand performance, has revealed widespread consumer skepticism about whether under-16 social media bans actually work.

The study surveyed 73,841 consumers across Australia, the United States, and the United Kingdom, revealing a disconnect between the intent of such bans and their perceived impact. Australia became the first country to introduce a nationwide under-16 social media ban in November 2025, sparking global debate about similar measures.

The Reality Check

In Australia, where the ban is already in effect, only 6% of consumers feel online spaces are now safer and more age-appropriate. Just 25% believe the ban has been effective at reducing online harm, while 37% say it’s been ineffective, and another 37% remain unsure.

Crucially, 31% of Australians believe many young people are already finding ways to bypass the ban.

Doubts About Effectiveness

Even in markets considering similar bans, some consumers are unconvinced they’d work. About half of UK and US respondents think a ban would be effective, but 35% of Americans and 29% of Britons disagree.

Concerns about young people circumventing restrictions are widespread: 42% of Americans and 40% of Britons expect this would happen.

Only 14% of Americans and 17% of Britons believe a ban would make online spaces feel safer and more age-appropriate.

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Mixed Support Across Markets

Awareness varies dramatically: 74% of Australians know about the ban, compared to 51% in the UK and just 36% in the US.

Support for bans being introduced is highest in the UK (54%), followed by the US (40%) and Australia (43%). However, significant opposition exists everywhere, ranging from 28% in the UK to 37% in the US.

Uncertainty on Content Exposure

When asked about impact on exposure to harmful content and misinformation, uncertainty dominates. In Australia, 45% are unsure how the ban has affected exposure, while 27% feel it’s made little difference.

“Consumers clearly support levels of protection for young people online, but our research shows real skepticism about whether blanket bans work,” says Sarah Tims, AVP Marketing at LoopMe. “Many are unsure the policy is making a meaningful difference, and there’s widespread expectation that young users will simply find workarounds. This points to a growing appetite for solutions focused on education, digital resilience, and smarter safeguards, not just prohibition.”

LoopMe surveyed 73,841 consumers in Australia, the United States, and the United Kingdom in December 2025 to understand awareness, attitudes, and perceptions around Australia’s under-16 social media ban and the potential impact of similar measures in other markets.

LoopMe is the global leader in brand performance, redefining brand advertising for the digital and app ecosystem. LoopMe was the first to apply AI to brand advertising and its Intelligent Marketplace, finding solutions to industry challenges that haven’t previously been solved. With consumer insights and AI at its core, LoopMe makes brand advertising better, outperforming industry benchmarks for leading global brands. Our vision is to change advertising for the better, by building technology that will redefine brand advertising. LoopMe was founded in 2012 and is headquartered in the UK, with global offices across New York, Boston, Atlanta, Chicago, Detroit, San Francisco, Los Angeles, Toronto, Singapore, Sydney, Melbourne, Dnipro, Krakow, Beijing, Shanghai and Hong Kong.

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TokTak Launches New Video Editing Feature to Enhance AI-Powered Content Automation

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TokTak Launches New Video Editing Feature to Enhance AI-Powered Content Automation

TokTak lets users edit transitions, subtitles, images, and background music—where AI-driven automation meets full customization for professional content.

TokTak, the world’s first platform for fully automated SNS content creation and distribution based on a single link, has introduced a new Video Editing feature that allows users to directly modify AI-generated short-form videos with full customization.

TokTak automatically generates three types of content—short-form videos, image-based card news, and blog-style articles—based on a product URL or a single-line text prompt. It then distributes the content to connected SNS channels such as Instagram, YouTube Shorts, and TikTok, providing an end-to-end solution for global creators, marketers, and online sellers.

TokTak is evolving into a complete automation platform where anyone can create, personalize, and distribute content—no technical background required.”

— Jin Kim, CSO of BodaPlay

The newly launched Video Editing Mode enables users to fine-tune each video by directly editing transitions, captions, text, images, and background music. Once content is generated, each scene’s elements are visually organized and can be edited individually. Real-time previews ensure that changes are immediately reflected, helping users create more polished final results quickly and efficiently.

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TokTak also supports seamless media replacement. Users can upload their own images or use AI-powered media generation to create visuals from simple text descriptions. All assets can be inserted into the video timeline, and background music can be added, replaced, or trimmed to better match the tone and pacing of each video.

“TokTak’s automation combined with customizable editing opens the door for everyone to create engaging content—no technical background needed,” said Mo Young-il, CEO of BodaPlay. “The new editing functionality marks another major step in building a complete content automation ecosystem,” added Jin Kim, CSO of BodaPlay.

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In addition to video editing, TokTak supports AI prompt-based image and video generation, multilingual content creation, expert-level customization options, and automated distribution across multiple SNS channels. The platform recently launched its global version with support for 11 languages and added a Chrome extension called ‘Link Analyzer,’ enabling users to instantly extract and convert content from any URL.

With these expanded capabilities, TokTak continues to lower the barrier to content production and empower users worldwide to scale their creative output through AI.

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How Knowband Is Driving Innovation Across the Global eCommerce Platform Ecosystem with Generative AI

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How Knowband Is Driving Innovation Across the Global eCommerce Platform Ecosystem with Generative AI

Knowband

Knowband Launches New Gen AI Plugins, including AI Chatbots and LLMs TXT Generator for e-commerce stores, helping admins to evolve with Popular AI Platforms.

Knowband, a well-known and trusted name in the global eCommerce solutions space, has taken a major step by introducing generative AI as part of its product ecosystem. After years of building performance-driven plugins for platforms like PrestaShop, OpenCart, WooCommerce, Shopify, and Magento, Knowband has helped more than 50,000 merchants grow their businesses online. Now, the company is focusing on using generative AI to handle complex e-commerce tasks and cut down the manual workload for store owners.

Knowband has launched two AI-powered modules designed specifically for what online merchants face every day. These AI-powered plugins include the AI chatbots that automatically provide Live AI chat support and assist shoppers with product queries in real time, and a Prestashop LLMs.txt generator that generates llms.txt files for popular LLMs access. Generative AI is now built directly into Knowband’s ecommerce solutions to make running an online store less of a headache.

Generative AI helps eCommerce merchants automate operations, improve visibility, and focus on growth without adding extra complexity.”

— Mr. Kumar

E-Commerce Operation and Visibility Challenges

Running an e-commerce store has gotten way more demanding. Merchants need to answer customer questions at all hours, keep inventory updated, get orders out fast, and somehow make the shopping experience feel personal. On top of that, they need to make sure their products can be discovered when shoppers ask AI platforms for recommendations. Studies show that most store owners struggle to keep up with traditional methods. Manual work eats up too much time, support teams can’t answer every question immediately, and customers want everything fast and personalised.

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As a result, stores end up with missed sales, frustrated customers, and overwhelmed teams. Knowband saw this problem and figured merchants needed smarter, scalable solutions that could handle repetitive tasks automatically.

Knowband Launches Generative AI Solutions for E-Commerce Websites

To tackle these issues, Knowband has developed two must-have AI Plugins for store owners. The Prestashop AI Chatbot module answers product and order questions automatically in real-time, saving merchants time without needing technical skills.

On the other hand, the Prestashop LLMs TXT Generator Addon creates structured files called llms.txt that AI answer engines can crawl to suggest store products to people asking related questions. This llms.txt file generator focuses on products, categories, and CMS pages, giving AI platforms access to store content with more detail.

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Mr. Kumar, Co-founder of Knowband, mentioned, “eCommerce merchants are juggling a lot with customer questions, order management, product updates, and marketing. With generative AI, we’re giving store owners a way to automate the repetitive stuff so they can focus on growth, all without needing a bigger team or extra manual work.”

What the Prestashop AI Chatbot Module Delivers

The LLM-based Prestashop AI Chatbot Addon automates the customer support system with AI. Shoppers get instant answers to questions about store catalogues without waiting. This Live chat feels like talking to a real person. The Prestashop AI chat assistant grabs live information from your store’s backend for questions about pricing, stock, product categories, and comparisons.

This Chatbot also handles order-related questions. Shoppers can ask about order status and get shipment updates from the chat. It fetches order IDs, recent orders, and current status in seconds, making order tracking simpler and keeping customers engaged.

Store owners can use various popular AI engines like Gemini, ChatGPT, Claude, and DeepSeek based on their store’s needs. The AI chat support keeps detailed chat logs so store owners can review what customers asked, spot common queries, and figure out where people get stuck.

This Prestashop AI Chatbot Module supports multi-language and dynamic-currency responses. The multilingual AI Chatbot detects the shop’s language and responds in the languages and currencies selected by the customer. Merchants don’t need massive support teams or worry about maintaining quality across different markets.
This Prestashop live AI Chatbot module uses vector search through Qdrant. This AI chatbot doesn’t just look for exact matches but understands the meanings of their queries. Customers can locate products faster, making browsing quicker and less frustrating.

What the LLMs TXT Generator Addon Delivers
The Prestashop LLMs TXT Generator Module helps store owners automatically generate llms.txt files for their catalog. This llms.txt file generator allows AI crawlers to access store content and recommend it to customers asking related queries on AI search engines like OpenAI ChatGPT, Gemini, DeepSeek, Claude, or Perplexity.

By creating a structured llms.txt file, your Prestashop store becomes accessible to AI answer engines. This increases the chances of your products being discovered and referenced in AI-generated responses. This module allows admins to select which content types to include in the file to ensure accurate AI targeting and avoid unnecessary content exposure. Moreover, merchants can filter products, categories, and CMS pages and add additional content for AI models for their better understanding.

The Prestashop AI answer engine optimization module creates and refreshes the llms.txt file automatically as your product catalog evolves. No manual file management or technical upkeep is needed. It also supports multiple languages for global eCommerce operations.

Why These AI Modules Are Beneficial for Merchants

The AI-powered Chatbot handles repetitive questions automatically, while the LLMs TXT Generator gets products recommended by AI platforms. Teams can spend time on growth and strategy instead. The outcome is faster response times, satisfied customers, improved retention, and better product discovery.
For customers, things just work more smoothly. Real-time AI chat provides help in the store without making users switch channels or wait for emails. When they ask AI platforms for product recommendations, stores using the llms.txt generator have a better shot at getting mentioned.

The Future of eCommerce with Generative AI
With this launch, Knowband strengthens its position as a provider of practical and future-ready solutions. Adding AI chat support and AI-powered product discovery shows they’re focused on fixing real problems merchants and customers face daily.
eCommerce keeps evolving, and solutions like generative AI chatbots and AI answer engines aren’t extras anymore; they’re becoming must-haves. Knowband’s AI plugins help merchants stay competitive.

The AI-powered Chatbot and LLMs TXT Generator are available now for Prestashop and Opencart. Both represent steps towards making e-commerce smarter through innovation and automation.

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Xtm Launches Intelligent Post-Editing to Bring Ai-Driven Review Automation to Enterprise Localisation

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Xtm Launches Intelligent Post-Editing to Bring Ai-Driven Review Automation to Enterprise Localisation

XTM International, a leading AI globalisation platform, expands its AI platform with the launch of Intelligent Post-Editing, a powerful new capability designed to automate the review and correction of translated content directly within XTM Cloud, reducing operational effort for localisation managers and linguists while preserving the human oversight enterprises require.

XTM’s latest release strengthens its position as a composable AI platform for enterprise localisation, extending automation deeper into the quality and review stages of the translation lifecycle.

Solving the globalisation bottleneck

As enterprises increase their use of AI translation and AI-assisted workflows, manual reviews slow global content operations down, creating a major bottleneck. Manual post-editing is time-consuming, expensive, and difficult to scale consistently across languages and vendors.

XTM’s Intelligent Post-Editing addresses this challenge by applying context-aware, LLM-driven edits automatically across human and AI translations. Built for enterprise workflows, Intelligent Post-Editing automates review steps without removing human control, supporting both hybrid and fully automated workflows.

“With this release, we’re tackling one of the biggest pain points in modern localisation,” said Lorcan Malone, CEO of XTM International. “Enterprises want the speed and efficiency of AI, but they can’t compromise on quality or governance. Intelligent Post-Editing helps teams achieve that balance by automating routine review work while keeping humans firmly in control of the final output.”

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Enterprise consistency, scaled with AI intelligence

Intelligent Post-Editing works in concert alongside XTM Cloud’s workflow engine, giving enterprises a highly configurable and automated way to run AI-driven review steps.

With Intelligent Post-Editing, teams can:

  • Automate routine linguistic corrections to reduce manual review time.
  • Enforce consistent use of terminology, the right level of formality, and linguistic rules across all content types.
  • Apply context-aware checks for formality, gender neutrality, locale-specific spelling, and number formatting.
  • Maintain full transparency and governance, with all changes auditable and clearly attributed within the system.

“Review shouldn’t slow teams down or distract them from high-impact decisions,” said Andreas Ljungström, Head of Product at XTM. “Intelligent Post-Editing acts as an AI review assistant, handling routine fixes automatically so linguists and reviewers can focus on nuance, intent, and quality. It’s a practical step towards more scalable, closed-loop AI localisation.”

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Uncompromising enterprise control and traceability

By shifting routine review work to AI while preserving full visibility into every change, Intelligent Post-Editing helps enterprises speed up global delivery and maintain quality at scale. The result is faster time-to-market with the governance and auditability required for enterprise operations.

The launch of Intelligent Post-Editing marks another step in helping global organisations bring products, communication, and content to international audiences faster through a composable AI platform. By embedding automation directly into the localisation lifecycle, XTM enables teams to scale quality, speed, and governance across every market.

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Reach Selects DeeperDive From Taboola, Gen AI Answer Engine Built for the Open Web, to Connect Readers with Timely, Contextual Answers for Topics They Care About

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Reach Selects DeeperDive From Taboola, Gen AI Answer Engine Built for the Open Web, to Connect Readers with Timely, Contextual Answers for Topics They Care About

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Taboola announced that Reach has selected DeeperDive, a Gen AI answer engine that lives directly on publisher websites and leverages their own content. As part of the agreement, Reach will use DeeperDive across sites including Express and Daily Star.

Today’s publishers face growing challenges from Generative AI-powered search engines that scrape their content, impacting their traffic. Publishers continue to seek out new methods and technologies to stay competitive to ensure reader engagement stays strong, both in the short and long term.

Since launching in 2025, many of the world’s top publishers have implemented DeeperDive to meet these challenges head on, including Gannett I USA TODAY Network, India Today Group, BuzzFeed Asia, The Bangkok Post, and more.

DeeperDive brings the power of GenAI search engines directly onto publisher websites, tapping into years of proprietary, real-time, high-quality content created by journalists and editors across the open web. Readers can ask questions about topics they’re interested in, and have AI provide answers instantly, sourced from trusted journalists such as the best travel desk or top sports reporters.

DeeperDive also prompts questions that may be of interest to readers, delivers direct responses, and surfaces additional context and stories from the same publisher site.

By meeting users with intuitive, conversational interfaces and instant, relevant answers, Reach can stay competitive in a rapidly shifting digital landscape and reinforce their brand as a trusted, forward-thinking destination.

“This is an important step for us as we focus on how to reach readers where they are, with conversational search becoming increasingly common. DeeperDive gives us the ability to continue that focus, giving readers the ability to learn more and explore topics they care about. Taboola has been a great partner for us as we continue to harness generative AI and apply to our everyday user journey,” said Terry Hornsby, Chief Product & Technology Officer at Reach PLC.

“Reach PLC is taking their rich history of delivering quality content and with DeeperDive, offering it to readers in a completely new, appealing and innovative way,” said Adam Singolda, CEO and Founder, Taboola. “Publishers who adopt DeeperDive aren’t just keeping up with the GenAI revolution, they’re leading it, on their terms. We’re creating a new user habit, one where readers lean in, ask follow-up questions, and stay to explore. We’re also giving publishers the potential to unlock even more ways to grow.”

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DeeperDive is built to provide:

  • Smarter, more diverse answers for readers: Readers receive rich, multifaceted answers, based on Taboola’s advanced AI and real-time insights from over 600 million daily active users across a global network of 9,000 publisher partners. Unlike traditional GenAI engines that rely on static training data, Taboola understands what people are actively reading and engaging with — across topics, geographies, and moments. This unique “pulse of the internet” allows DeeperDive to surface timely, contextual answers and even suggest questions based on current trends. The result is a richer, more human search experience rooted in what truly matters to real people — right now, on the site they trust.
  • Increased readership and engagement for publishers: Every reader question is met with a clear, intuitive answer, along with links to relevant and timely articles from across the publisher’s site. This keeps users engaged longer and encourages deeper content exploration. For the first time, publishers can engage their audience with real-time, AI-powered content tailored to the user, whether it’s about travel plans, a favorite sports team, or important financial decisions, meaningfully increasing time on site and reader loyalty.
  • Unlocking high-intent ad revenue opportunities and owning the future with AI agents across high intent categories: DeeperDive has the potential to create a new monetization channel for publishers starting by inserting contextually relevant, high-intent ads directly into the AI-powered results page. Publishers can capture search-like advertising revenue within their own environments — turning user inquiries into meaningful commercial opportunities, all while maintaining a seamless reader experience.

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BFJ Digital Details Strategic Criteria for Choosing the Right CRM to Optimise Customer Sales

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DealsFlow Launches AI-Powered CRM and Social Media Automation Platform for Small and Medium Businesses

BFJ Digital, a Brisbane-based digital marketing firm, has released a strategic analysis detailing the essential criteria businesses must use when selecting a Customer Relationship Management (CRM) system. This insight addresses the critical need for a technological powerhouse that ensures scalable customer engagement, optimises sales processes, and delivers measurable Return on Investment (ROI) in today’s competitive digital marketplace.

Strategic Options for CRMs in Today’s Market
BFJ Digital states that the need for a strong CRM system extends well beyond simple contact management. Additionally, it helps enhance marketing campaigns, customer service initiatives, and sales automation. Choosing the appropriate platform is essential to providing a seamless customer experience and giving sales teams the accurate information they need to convert leads successfully.

The firm analysed industry-leading systems, breaking down their optimal use cases to help CMOs, CEOs, and Heads of Sales select the platform best suited for their scale and operational demands.

BFJ Digital’s insights categorise leading CRM systems based on core capabilities:

•HubSpot: Ideal for growing businesses and those new to CRM systems, HubSpot is noted for its user-friendly interface and comprehensive automation capabilities. It’s good for managing leads and tracking customer behaviours.

•Salesforce Essentials: Tailored for small to midsize businesses, this platform offers powerful CRM tools designed to streamline sales processes and improve customer insights without the full complexity of enterprise-level systems.

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•Zoho CRM: Businesses that prioritise extensive data collection and analytics to inform their marketing and attribution modelling are best suited for Zoho CRM. It also stands out for its affordability and social media management features.

•Microsoft Dynamics CRM: Known for its smooth integration with other Microsoft products, this system is recommended for businesses that are already utilising the Microsoft ecosystem. Additionally, it is highly customisable and scalable to meet larger operational requirements.

•Enterprise Solutions: Although more expensive and requiring IT support, systems like SAP and Oracle provide comprehensive features, high scalability, and advanced analytics for large-scale operations and complex sales cycles.

Choosing the Right CRM Tool
The process of choosing the best CRM, according to BFJ Digital, is about finding a solution that fits a company’s particular needs rather than trying to find a universal solution. Integration capabilities, customisation choices, usability, data handling, and scalability should all be important considerations.

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The digital marketing consultancy advises that good CRM software acts as a critical resource for aligning marketing campaigns with enhancing customer experience. It should allow teams to measure and fine-tune every initiative for maximum ROI. BFJ Digital works with businesses to conduct deep dives into these critical aspects, assisting them in selecting and implementing a CRM system that enhances customer satisfaction and aligns with future commercial goals.

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DriveCentric and automotiveMastermind® Expand Bi-Directional Data Integration to Power Smarter Dealer Engagement

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DriveCentric and automotiveMastermind® Expand Bi-Directional Data Integration to Power Smarter Dealer Engagement

DriveCentric, the modern CRM and engagement platform built for today’s dealerships, and automotiveMastermind, the leading provider of predictive analytics and marketing automation for automotive retailers, announced the next phase of their strategic partnership.

This expanded integration delivers a more unified customer experience by allowing dealership teams to work within one system, while customer, deal, and activity data remain continuously synchronized across both platforms. The result is a single, consistent customer record that aligns predictive intelligence with real-time sales and engagement.

“Dealers don’t need more tools and screens; they need technology partners that help reduce technology bloat through tighter integrations,” said Matt Leone, CEO of DriveCentric. “Our deep integration with automotiveMastermind puts that philosophy into action by pairing Mastermind’s industry-leading predictive insights with DriveCentric’s engagement platform. The result is clean, actionable intelligence unified within DriveCentric’s customer record and directly powering our Genius AI products.”

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At the core of the enhancement is a two-way data exchange that automatically syncs customer engagement history, lead status, notes, tasks, and deal status between DriveCentric and automotiveMastermind. Within DriveCentric, teams gain direct access to automotiveMastermind’s Behavior Prediction Score® (BPS) and Behavior Drivers, enabling smarter prioritization, more personalized outreach, and stronger follow-up. Those same insights help inform DriveCentric’s automation and AI-powered engagement tools.

“Predictive intelligence is only valuable when sales teams can turn insights into sold and delivered vehicles,” said Aaron Baldwin, President of Marketing & Sales Solutions. “By deepening our integration with DriveCentric, we’re helping dealers act on our data, move faster, reduce friction, and engage customers without forcing their teams to juggle systems.”

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As part of the expanded partnership, eligible dealers can not only view customer-specific OEM Private Incentives directly within DriveCentric, but also desk deals using those incentives. The bi-directional integration also brings automotiveMastermind’s Behavior Prediction Score (BPS) and Behavior Drivers directly into DriveCentric, alongside detailed marketing campaign activity. This shared visibility allows DriveCentric users and its Genius AI products to understand what was sent to each customer, how they engaged, and what actions followed. That same customer activity from DriveCentric flows back into automotiveMastermind, continuously strengthening its machine-learning models and delivering even more accurate predictive insights for mutual customers.

The enhanced bi-directional integration is available now to DriveCentric and automotiveMastermind customers.

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Gallea Ai Joins IBM Partner Plus as an IBM Business Partner to Deliver Enterprise Grade AI and Hybrid Cloud Capabilities to Small and Mid Sized Businesses

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Gallea Ai Joins IBM Partner Plus as an IBM Business Partner to Deliver Enterprise Grade AI and Hybrid Cloud Capabilities to Small and Mid Sized Businesses

New IBM Business Partner status strengthens Gallea Ai’s ability to support secure, scalable AI adoption across North America and the United Kingdom

Gallea Ai, an advisory led consultancy specializing in applied artificial intelligence for small and mid sized businesses (SMBs), announced it has joined IBM Partner Plus as an IBM Business Partner. This designation expands Gallea Ai’s ability to support organizations as they move from AI experimentation to secure, production ready deployment leveraging IBM AI and hybrid cloud technologies across Canada, the United States, and the United Kingdom.

Strengthening capabilities through partnership

By joining IBM Partner Plus, Gallea Ai gains access to IBM enterprise AI and hybrid cloud solutions, as well as advanced training, technical enablement, and go to market support. These capabilities allow Gallea Ai to shorten time to value for clients, reduce implementation risk, and establish repeatable, defensible AI capabilities in an environment increasingly shaped by AI mediated discovery and automation.

The collaboration aligns IBM technology with Gallea Ai’s proprietary AI Implementation Framework, a structured methodology governing AI strategy, data readiness, workflow integration, and operational deployment. The framework is designed to ensure AI initiatives deliver measurable outcomes while remaining aligned with governance, brand integrity, and organizational priorities.

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A practical path to AI adoption

Gallea Ai works with growth oriented and operationally complex businesses to translate advances in artificial intelligence into actionable strategies that improve decision making, operational efficiency, and customer experience. The firm’s consulting approach emphasizes disciplined adoption, governance alignment, and business value realization, helping clients embed AI as a durable capability rather than a series of isolated projects.

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Leadership perspectives

“Joining IBM Partner Plus marks an important milestone in our mission to make AI practical, accessible, and business ready for small and mid sized organizations,” said Alessandro Rocca, Chief Operating Officer of Gallea Ai. “Our clients will benefit from IBM scalable technology portfolio while maintaining the hands on strategic guidance, governance discipline, and implementation rigor that define our firm.”

“For many small and mid sized businesses, the age of AI still feels like something reserved for the biggest players,” said Ryan Mackay, Managing Director of Gallea Ai’s Neural Networks division, the firm’s AI transformation consulting arm. “Partnering with IBM raises the ceiling on what we can safely deliver. Our team is now backed by the same class of AI and hybrid cloud tools that large enterprises rely on, and we use that to open doors that smaller organizations have historically been shut out of, while still keeping a clear path to more complex enterprise level applications as they grow.”

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Cognizant partners with Palantir to Accelerate AI-Driven Modernization in Healthcare and Enterprise Operations

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Cognizant partners with Palantir to Accelerate AI-Driven Modernization in Healthcare and Enterprise Operations

Partnership combines Palantir Foundry and AIP with Cognizant’s TriZetto healthcare platforms and business process operations to enable secure, scalable AI transformation for enterprises across industries.

Cognizant announced a strategic partnership with Palantir Technologies Inc.to accelerate AI-driven modernization across healthcare and enterprise operations. As part of the collaboration, Cognizant will leverage Palantir Foundry and Palantir Artificial Intelligence Platform (AIP) to advance AI integration within its TriZetto healthcare business, while jointly pursuing broader enterprise AI transformation opportunities for clients across industries.

The partnership advances Cognizant’s strategy as an AI builder: creating purpose-built, enterprise-grade solutions that turn the potential of AI into real business value. Cognizant brings together frontier AI platforms, deep industry expertise and the right combination of IP and services to modernize its own operations and help clients transform complex, regulated environments with a focus on responsible adoption, security and operational integrity.

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“This partnership reflects our commitment to using frontier technologies to deliver value for our clients, while also transforming our own businesses for the next era of AI-led growth,” said Surya Gummadi, President, Americas, Cognizant. “By combining Palantir’s AI platform capabilities with Cognizant’s deep industry expertise and global engineering scale, we are strengthening our ability to modernize mission-critical platforms like TriZetto while creating new opportunities to build purpose-driven, enterprise-grade solutions that help clients transform how they operate and deliver the experiences and outcomes their customers expect.”

Cognizant will work with Palantir to explore how AIP can support AI-driven optimization across TriZetto’s healthcare platforms and BPaaS (Business Process as a Service) operations, with a focus on high-value workflows in highly regulated, labor-intensive environments. This initiative is intended to enhance Cognizant’s ability to innovate across its healthcare portfolio, accelerate iterative product development and establish a secure, governed foundation for future AI-enabled capabilities that can provide a repeatable model for building enterprise-grade AI solutions, while supporting clients in maintaining robust compliance and auditability standards based on applicable law and client-defined controls.

“Enterprise AI doesn’t fail because models are weak. It fails when AI lacks a shared, governed understanding of how the business actually operates – something only the Ontology can provide,” said Eric Lakin, US Commercial Lead at Palantir. “That’s why we’re excited to partner with Cognizant and bring AIP to TriZetto, embedding AI into core workflows to transform enterprises from the ground up.”

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Palantir brings deep experience deploying AI platforms in mission-critical environments in addition to its advanced data analytics capabilities. Cognizant’s global delivery scale and domain expertise complement Palantir’s software-driven model, supporting both companies in expanding the reach and impact of AI-powered solutions while maintaining strong governance and security controls.

In parallel, Cognizant and Palantir plan to collaborate on enterprise AI transformation initiatives beyond healthcare, expanding on their existing work across industries.

The partnership also reflects Palantir’s focus on ontology-driven AI – a governed deployment layer to help translate AI innovation into secure, real-world operations – paired with Cognizant’s ability to industrialize and deliver those capabilities across enterprise environments.

The collaboration follows Cognizant’s recent AI partnerships and investments, reinforcing the company’s commitment to building a composable ecosystem of leading AI platforms to drive both internal transformation and client innovation.

Write in to psen@itechseries.com to learn more about our exclusive editorial packages and programs.

Zero-party Data Strategies: Building Trust While Powering Hyper-Personalized Marketing

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Zero-party Data Strategies: Building Trust While Powering Hyper-Personalized Marketing

In the digital world that is ever changing, one thing has become clear: protecting people’s privacy is now the most important thing in marketing. For years, brands used third-party tracking to keep an eye on how people browsed the web, create audience segments, and show them ads that were relevant to them. But because of recent acts like GDPR and CCPA, and since people are becoming more skeptical, relying on data collection that is hidden from view is no longer possible. It’s clear from what consumers are saying that privacy is important. This change is not only a problem for marketers; it is also a chance to rebuild trust and use more open and honest ways to personalize.

This is where zero-party data comes into play. It is important to tell it apart from other types of data you are used to and understand its value. First-party data is information that comes directly from how customers interact with a brand, such as website analytics, transaction histories, or email engagement. Second-party data is basically first-party data from another company that is shared through partnerships like co-marketing campaigns. Third-party data, on the other hand, comes from outside sources that collect data from many sources, often without the consumer’s knowledge or permission. These models have been used for digital advertising for decades, but their flaws are now clear, especially since people want more control over their personal information.

Zero-party data is different because consumers willingly and proactively share it. This could be in the form of stated preferences, product interests, communication choices, or even feedback given through surveys, quizzes, and loyalty programs. Zero-party data is not taken or guessed at by someone else; it is given freely by people who expect something in return. This change makes it much more reliable, open, and based on trust than the ones that came before it.

The rise of zero-party data shows that every brand needs to rethink how it uses data. The way things are changing is from surveillance-based personalization, where people are followed around the web without their knowledge, to trust-based personalization, where people give information willingly in exchange for better, more useful, and more rewarding experiences. This isn’t just about following the rules about privacy; it’s also about changing the way brands and customers interact with each other. In today’s market, being honest and respecting consumer choice are just as important as the quality or price of a product.

This change is both a problem and an opportunity for businesses. Brands will be in trouble when browsers stop using third-party cookies and regulators tighten controls. People who utilize zero-party data can also differentiate themselves as trustworthy partners by offering personalization that feels helpful rather than intrusive. Customers are more likely to get involved and share useful information when they know they are in charge. This creates a cycle of trust and value that benefits both sides.

The promise here is strong: personalized service without invasive tracking. Think about how much better it would be to tailor offers, recommendations, and communications by asking customers directly and respecting their answers instead of guessing what they want or putting together bits of data. For example, a shopper who says they like eco-friendly products can get personalized suggestions that fit with that value. If a subscriber says they are more interested in skincare than haircare, they can get promotions that match that. This is the most real form of personalization, based on what real customers say instead of hidden algorithms.

As we enter a time when cookies are no longer used and privacy is more important, brands that don’t use clear data practices could lose customers and fall behind their competitors. But those who use zero-party data will find a new way to grow in a way that is based on trust and will last. The future of marketing isn’t about getting as much data as possible at any cost. It’s about getting the right data with consent, openness, and relevance at its core.

Zero-party data strategies are a way to move forward that is both moral and useful. Marketers can make personalization that is richer, more accurate, and more human by focusing on what customers are willing to share. In the next few pages, we’ll talk about how zero-party data works, why it’s more important than ever, and how brands can use it to build stronger relationships while staying ahead of changes in privacy and the market.

What is Zero-Party Data and How Does It Come to Play?

Brands are under more and more pressure to respect customers’ privacy while still giving them personalized experiences in today’s digital economy, which puts privacy first. Cookies and third-party data brokers are examples of old-fashioned tracking methods that are becoming less reliable and, in many cases, illegal. This is where Zero-Party Data comes in.

Zero-Party Data is information that customers give to brands on purpose. Zero-party data is different from first-party data, which is collected by watching how customers act, and third-party data, which is bought from other companies. Zero-party data comes directly from the customer, with their full permission. Customers know exactly what they are sharing and why, which makes it the most open and trustworthy type of data.

If a shopper fills out a style preference quiz on a fashion website or says they prefer email over SMS, that is zero-party data. The most important thing is that the customer is giving this information willingly to make their experience with the brand better.

Some examples of zero-party data

Let’s look at some common types of zero-party data that businesses can collect to get a better idea of what they are.

1. Customer Needs

This includes things like the types of products you like, the way you like to talk to people, or the colors you like best. A customer might say they want to get updates about skincare products but not makeup, or they might say they want monthly newsletters instead of daily promotional emails.

2. Purchase Intentions

Customers can also tell us what they plan to buy soon. For example, someone who goes to a store that sells home appliances might use an interactive tool to say, “planning to buy a refrigerator within the next 3 months.” This gives the brand very useful information that can help it make personalized offers and suggestions.

3. Surveys and Feedback Forms

Feedback is one of the easiest types of zero-party data to get. When customers fill out surveys, review forms, or NPS (Net Promoter Score) questionnaires on their own, they give you information about how satisfied they are, what they expect from the product, and what you can do to make it better. Not only does this help brands improve their products, but it also builds customer trust because they feel like their opinions are being heard.

4. Loyalty Program Insights

Loyalty programs often collect a lot of zero-party data. When customers sign up, they might tell you their birthday, what products they like, or how they want to use their points (for example, for discounts, experiences, or gifts). These insights help brands tailor rewards to each member and keep them interested over time.

The main difference is between voluntary disclosure and passive collection.

Voluntary disclosure is what makes zero-party data unique. Customers choose what information to share, when to share it, and why they want to share it. On the other hand, other kinds of data often use passive collection methods.

Tracking how customers act, such as how many times they click, how long they stay on a page, or how many times they buy something, is how first-party data is collected.

Second-party data is first-party data that two companies share with each other. For example, a travel brand might share booking data with an airline partner.

External providers collect and sell third-party data, often without the customer knowing or agreeing to it.

With zero-party data, there is no tracking, guessing, or making assumptions. The customer directly tells the brand what they want, need, and think, which clears up any confusion and makes the exchange of value between the customer and the brand more real.

Why Zero-Party Data Is Important?

There are a few reasons why zero-party data is becoming more important:

  • Privacy Laws:

Companies must make sure that collecting data is open and based on consent because of stricter privacy laws like GDPR and CCPA. Zero-party data is naturally compliant because the customer shares it on purpose.

  • Trust in the Brand:

Customers trust a brand more when they feel like they are in charge of their data. Trust is not only required by law, but it also gives you an edge over your competitors.

  • Better Personalization:

Businesses can create highly relevant and personalized experiences with zero-party data because it is direct and accurate. This can be done through product recommendations, targeted offers, or personalized communication.

  • Future-Proofing:

Businesses need long-lasting ways to learn about their customers as third-party cookies go away. Zero-party data lets brands keep personalizing on a large scale without having to rely on outside sources.

Hence, zero-party data changes the way businesses interact with their customers. It’s not about spying on people; it’s about getting customers to join in an open exchange of value. Customers help brands serve them better by sharing their preferences, plans to buy, and feedback on purpose. This also builds trust and loyalty.

In a world where privacy is important, companies can’t afford to ignore zero-party data anymore; it’s the key to growth that puts customers first.

Why Zero-Party Data is Important Right Now?

Customer data is the lifeblood of modern marketing in the ever-changing digital world. But people are very interested in how businesses get and use this information. In a world where privacy and trust are very important, old ways of doing things, like third-party cookies and background tracking, don’t work anymore. In this context, Zero-Party Data has become the most trustworthy and ethical way for brands to personalize without going too far.

Cookie Deprecation and Privacy-First Regulations

One of the biggest changes in digital marketing right now is the decline of third-party cookies. Big tech companies like Google are getting rid of cookies, which makes it harder for advertisers to follow users from one website to another. This change is part of a larger trend around the world toward digital ecosystems that put privacy first.

The General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States are two laws that support the idea that people should be in charge of their data. Companies that don’t follow the rules could face big fines and damage to their reputation.

Zero-party data fits perfectly into this new way of doing things because it is based on consent and openness. Businesses can use data that customers give them directly about their preferences, plans to buy, or feedback, without worrying about breaking the law.

Erosion of Trust in Third-Party Tracking

People today know more than ever how their online activity is tracked. The world of digital surveillance, which used to be hidden, is now in the open, and many people don’t trust third-party tracking. A lot of people now think that targeted ads are intrusive, especially when they seem to “follow” them around the web.

This loss of trust has real effects. When customers find out that their data is being collected without their permission, they may feel like they are being taken advantage of instead of valued. This causes problems between brands and the people they want to help.

Zero-party data is a trust-based option. There are no surprises because customers know exactly what they are sharing. Brands can use this information to connect with people in a way that doesn’t make them suspicious or uncomfortable.

The Consumer Shift: Willingness to Engage When Value is Clear

Even though people are worried about their privacy, studies show that people are willing to give out personal information if they think it will help them. For instance, a shopper might tell a store about their dietary preferences in exchange for personalized meal kit suggestions, or a traveler might tell a travel agency about their favorite places to go in order to get curated vacation deals.

The most important thing is to make a clear exchange of value. Customers want to know, “What’s in it for me?” Customers are much more likely to get involved when brands show that sharing information leads to better service, more relevant experiences, or personalized rewards.

Zero-party data turns this exchange into a two-way conversation instead of just taking information from one person. Instead of just being passive targets of data collection, consumers take an active role in deciding how brands interact with them.

How Zero-Party Data Builds Trust and Personalization?

Personalization is a key part of good marketing, but if people don’t trust you, personalization can backfire. People may think a brand is intrusive instead of helpful if it seems to “know too much.” Finding the right balance is the hard part.

Zero-party data fills this gap perfectly. It lets brands give customers personalized experiences based on trust because the interaction starts with customer consent. For example:

  • Instead of looking at a customer’s browsing history, a fashion store can suggest styles based on what the customer says they like.
  • A fitness app can suggest workout plans based on the user’s goals and routines that they share with the app.
  • A loyalty program can give customers rewards that fit with how they say they want to interact with the brand.

In each of these situations, personalization isn’t a guess; it’s based on what the customer has clearly said. This makes the experience more accurate, more useful, and most importantly, more reliable.

Zero-party data is more important than ever because it is a strategy that will work in the future in a world where privacy is important. Businesses need a way to connect with customers that will last, since third-party cookies are going away, rules are getting stricter, and customers are becoming more skeptical. Zero-party data meets this need by making sure that personalization goals are in line with the values of trust and openness.

Brands can get customers to share useful information by making clear value exchanges. This will lead to stronger relationships and better engagement. In short, zero-party data is more than just a way to follow the rules; it is the basis for customer-first, trust-based marketing.

The Growth of Marketing Based on Trust

The world of digital marketing is moving away from targeting based on surveillance and toward an era of trust-based marketing. People are more aware, careful, and vocal about how their data is collected and used these days.

Brands that don’t accept this fact risk losing their customers, while those that do can build stronger loyalty and grow over time. Zero-party data is at the center of this change. This is information that customers freely give because they trust the brand and see value in the exchange.

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Why Customers Are Happy to Share Zero-Party Data?

Zero-party data needs openness to grow, unlike third-party data that is collected without permission. People aren’t tricked or tracked; instead, they are asked to help shape their own experiences. Let’s look at the main reasons why customers want to share this kind of information.

1. Trust and Transparency

Trust is the most important thing in any relationship, and the relationship between a brand and a customer is no different. Customers are much more likely to share personal information with a company if it clearly explains what data it is collecting, why it needs it, and how it will be used.

A skincare brand, for example, might ask customers what kind of skin they have and what problems they have with it, like dryness, acne, or sensitivity. The brand tells customers that their information will only be used to suggest products that are right for them, which makes them feel safe that their data won’t be sold or used in other ways.

This openness makes people feel more secure. Customers don’t see data collection as an invasion of privacy; they see it as a way to work together to make their experience better. In a market with a lot of choices, trust is a key way to stand out, and zero-party data helps brands build that trust.

2. Relevant offers and experiences

Every day, customers get a lot of emails, ads, and promotions, many of which aren’t useful. This “noise” makes people angry and makes them lose interest. But when brands send personalized and useful offers, people react positively.

This is possible because of zero-party data. For example, if a customer says they like vegan products, a food store can make suggestions and discounts that are exactly what they want. In the same way, a travel company can customize its offers based on what a user says are their dream destinations instead of sending them a lot of generic packages.

Relevance shows that the brand cares about the customer’s needs and is paying attention. This makes the emotional connection stronger and encourages people to come back. In short, people are okay with sharing information if it makes they get better.

3. Incentives: special offers, rewards, and VIP access

The promise of real benefits is another strong reason to share zero-party data. Customers are much more likely to give information when they know they will get something in return.

Loyalty programs are a good example. Brands can give perks that feel truly personalized by asking members what they like best, like discounts, early access to sales, or experiential rewards. Giving VIP access to events, special previews, or exclusive bundles also makes people feel special and like they belong.

This method works because it links sharing data to something useful right away. Customers don’t feel used; instead, they feel valued and in control.

4. Building Stronger Brand-Consumer Relationships Through Voluntary Exchange

Zero-party data is all about relationship-based marketing instead of transactional marketing. When customers are willing to share personal information, it shows that they trust you and want to connect with you. Over time, brands that respect this gesture and use the data wisely strengthen the bond.

Think about a fitness app that lets users set their own workout and diet goals. Every update or suggestion feels like a personal coaching session instead of just general advice. As time goes on, the user becomes loyal not only to the app but also to the brand’s values.

This voluntary exchange also makes the interaction more human. Customers are more than just numbers; they are actively involved in how they experience your brand. This feeling of control changes the relationship from one of passive consumption to active collaboration.

The rise of trust-based marketing shows that businesses are changing the way they talk to their customers in a big way. Customers won’t put up with hidden tracking or ads that aren’t relevant anymore. Instead, they want real, open, and mutually beneficial relationships with the brands they choose to support.

This change is being driven by zero-party data. Customers not only share useful information, but they also feel more connected to the brands they interact with through trust, relevance, incentives, and voluntary participation. The outcome is good for everyone: businesses get accurate, consent-based data to personalize their services, and customers get experiences that fit their needs, values, and goals.

In a time when trust is the most important thing, brands that use zero-party data and trust-based marketing will not only survive, but they will also do well.

How to Collect Zero-Party Data Well?

The idea of zero-party data sounds good, but how businesses gather it will determine its success. When the process is clear, fun, and rewarding, customers are more likely to share their information. They’ll be less likely to do it if it feels like a chore or an invasion of privacy. So, brands need to find a balance between asking the right questions and giving clear value in return.

Here are some useful tips and best practices for getting zero-party data in the best way possible.

a) Settings for Your Account and Preferences

Preference centers or account settings are one of the easiest and most effective ways to get zero-party data. These let customers tell the brand directly what they want.

For example, a preference center for email subscriptions might let users pick:

  • What kind of content do they want to get (news, promotions, educational updates).
  • How often do you talk to each other (every day, every week, or every month).
  • The ways they like to get messages (email, SMS, or push notifications).

Brands show that they care about their customers’ time and preferences by letting them choose how they want to communicate. This not only cuts down on people who unsubscribe, but it also makes sure that every interaction feels useful and welcome.

b) Interactive quizzes and suggestions for products

One of the most interesting ways to get zero-party data is through interactive experiences. Quizzes and product recommendations make the process fun and give you something useful right away.

For instance:

  • A beauty brand might have a quiz called “Find Your Perfect Foundation Shade” that asks about your skin tone, type, and coverage preferences.
  • A store that sells home decor could make a quiz called “What’s Your Interior Style?” to help people find things that match their taste.
  • Based on a short survey of your lifestyle, a fitness app could suggest personalized workout plans.

Not only do these tools give you useful information about your customers, but they also make you feel good right away, which makes sharing data feel less like a transaction and more like a discovery process.

c) Surveys and Feedback Forms

One of the most direct and reliable ways to get zero-party data is through feedback. Customers are usually happy to share their thoughts if they think it will make things better for them.

Businesses can learn a lot about how happy their customers are, what problems they have, and what they expect from them by using surveys, review requests, and NPS (Net Promoter Score) forms. For instance:

  • After a flight, an airline might ask travelers about their comfort, service quality, and booking experiences.
  • After you buy something from an e-commerce site, they might ask you questions like, “Why did you choose this product?” or “What can we do to make your shopping better?”

The most important thing is to make surveys short and to the point. Customers are more likely to get involved if they feel like their time is valued and their opinions are heard.

d) Loyalty Programs & Gated Experiences

Because loyalty programs work on a value-exchange model, they are good ways to get zero-party data. Customers willingly join to get rewards, discounts, or special privileges. In return, they give brands information that helps them make better offers.

For instance:

  • A coffee shop chain might ask its members to share their favorite drinks so that it can send them personalized deals.
  • A clothing store could ask loyalty members about their style preferences so that it can put together outfits for them.
  • A travel site might ask loyalty members to rank the places they want to go and then give them extra points based on those rankings.

In the same way, gated experiences like VIP webinars, exclusive content downloads, or early access events can make customers more likely to give information up front. The fact that it’s only for a few people makes the data exchange seem worth it.

e) Gamified Experiences: Contests, Polls, and Challenges

Gamification uses psychology to make sharing data fun and rewarding. Contests, polls, and challenges encourage customers to get involved and show what they like.

Here are some examples:

  • A brand is putting up a poll on social media and asking its followers to choose the next flavor of its product.
  • A fitness company is running a “30-Day Challenge” where people share their health goals and get personalized advice.
  • A fashion brand that runs a contest where people send in pictures of their favorite outfits to show what styles are popular right now.

Gamified experiences not only give you useful information, but they also get people more involved, make your brand more visible, and get more people involved in your community.

How to Get Zero-Party Data the Right Way?

How brands go about collecting zero-party data is what matters, no matter what method they use. Here are some things you should do:

1. Keep It Simple

People are less likely to participate when forms are complicated or questions are long. Start by gathering small, important pieces of information and then build on them. Customers are more likely to get involved if the process seems easy.

2. Give something of value back

Sharing data should feel good for both parties. Customers should be able to easily see what they get in return for sharing information, whether it’s a personalized recommendation, a special offer, or access to exclusive content.

3. Respect Consent and Privacy

Always let people know why you’re collecting certain data and what you’ll do with it. Give customers clear choices for changing or removing their preferences. Not only does transparency make sure that rules are followed, but it also builds trust.

4. Integrate Across Channels

There shouldn’t be any silos for zero-party data. Make sure that the information you get from quizzes, loyalty programs, or surveys is added to your CRM systems so that personalization stays the same at all points of contact.

5. Test and improve

Keep checking to see which methods work best for your audience. Some groups may like quizzes better, while others may be more interested in surveys that reward loyalty. A/B testing helps you improve your plans so they have the most effect.

Hence, to collect zero-party data well, you need to be creative, open, and respectful. Businesses have a lot of tools at their disposal, from preference centers to gamified experiences. But the real success is in making experiences that customers really enjoy and that give them clear value in return.

Brands can encourage voluntary participation, get useful information, and build trust-based relationships by making the process simple, rewarding, and clear. In a market where privacy is very important, brands that are good at collecting zero-party data will not only get information, but also long-term customer loyalty.

Leveraging Zero-Party Data for Personalization

The true value of zero-party data lies not only in collecting it but in how brands use it to deliver meaningful, personalized experiences. When customers willingly share their preferences, intentions, and needs, they expect brands to act on that information. Done well, personalization powered by zero-party data transforms generic marketing into relevant, value-driven interactions that strengthen loyalty and drive conversions.

a) Tailored Product Recommendations

One of the most powerful applications of zero-party data is in personalized product recommendations. Unlike behavioral data, which relies on assumptions, zero-party insights come directly from the customer. This makes recommendations more accurate and welcomed.

For example:

  • A beauty retailer can use quiz responses about skin tone and type to recommend specific foundations or moisturizers.
  • A sportswear brand can suggest running shoes designed for long-distance training if a customer indicates that as their fitness goal.
  • A streaming platform can create playlists based on genres or moods that the user has shared they enjoy.

These recommendations feel less like marketing and more like helpful guidance—because they are rooted in the customer’s self-disclosed needs.

b) Personalized Content Across Channels

Zero-party data also powers customized content strategies, ensuring customers receive information that resonates with their interests.

  • Emails: A newsletter can highlight product categories or topics a customer has expressed interest in, rather than sending blanket promotions.
  • Apps: A wellness app could adjust its dashboard based on a user’s stated goals—prioritizing meditation tips for stress relief or workout routines for muscle building.
  • Websites: A homepage can be tailored dynamically, showing different banners, offers, or blog posts depending on the visitor’s shared preferences.

This level of personalization makes interactions feel curated rather than intrusive, increasing engagement and reducing the risk of unsubscribes or app deletions.

c) Contextual Messaging: Timing, Channels, and Formats

Personalization extends beyond what message is delivered to how and when it is delivered. Zero-party data helps brands fine-tune these elements.

  • Timing: A customer may indicate they prefer receiving updates once a week instead of daily. Respecting this builds trust and avoids fatigue.
  • Channels: Some customers may want SMS alerts for time-sensitive promotions, while others may prefer email or push notifications.
  • Formats: A customer who prefers visual storytelling might engage more with short videos, while another may prefer detailed articles.

When brands align communication formats with customer preferences, they not only increase response rates but also reinforce respect for customer choice.

Case Example: Retail Brand Tailoring Suggestions Through a Quiz

Imagine a fashion retailer introducing a style preference quiz for new customers. The quiz asks about favorite colors, preferred fits (slim, relaxed, oversized), occasions (workwear, casual, party), and budget range.

Here’s how the retailer leverages that zero-party data:

  • Website: On the website, the customer’s homepage updates to showcase curated outfits aligned with their quiz answers.
  • In emails: Weekly recommendations highlight only the categories they care about—for instance, smart-casual blazers instead of party dresses.
  • In loyalty: In loyalty rewards, the customer receives exclusive offers on items within their chosen budget bracket, reinforcing affordability and personalization.
  • In retargeting ads: Instead of generic campaigns, the ads spotlight specific items from the curated collection.

The result? The customer feels understood and valued, rather than bombarded with irrelevant promotions. This not only increases conversion but also strengthens emotional loyalty, as the shopping journey reflects their unique identity.

Leveraging zero-party data for personalization allows brands to replace guesswork with genuine relevance. Tailored product recommendations, personalized content across channels, and contextual messaging ensure that every touchpoint feels purposeful. The retail quiz example illustrates how even simple data collection methods can yield powerful personalization outcomes.

In a digital environment where customers crave both privacy and relevance, zero-party data provides the bridge. By using it thoughtfully, brands can create experiences that respect consent, build trust, and drive stronger long-term relationships.

Finding a balance between personalization and privacy

Zero-party data can be very useful, but its value depends on how responsibly it is used. Customers are becoming more concerned about how brands use their information. If personalization feels intrusive or manipulative, the trust that made people want to share their data in the first place can quickly fade. Businesses need to find a balance between using zero-party data to improve experiences and not violating privacy, trust, or respect.

How to Use Zero-Party Data Responsibly?

Getting zero-party data is only half the job; you also need to get permission. Brands need to be careful with this information and make sure it is:

  • Stored safely to protect against breaches that could reveal private information.
  • Only for the stated purpose—don’t be tempted to use data for something other than what the customer agreed to.
  • Updated all the time, so customers can look over, change, or take back their choices at any time.

Using the brand responsibly shows that they care more about the relationship than making quick sales. This makes customers more loyal and more willing to share over time.

a) Being clear about how data is used

Being open is one of the best ways to build trust. Customers should never have to guess what you are doing with their information. When people talk to each other clearly, data collection becomes a group effort.

For instance:

  • A fashion brand that asks about your style might say, “We’ll use your answers to suggest outfits you’ll love and avoid sending you suggestions that don’t fit your style.”
  • A subscription service might say, “We’ll make sure your weekly digest only has topics you’ve chosen by sharing your content interests.”

Customers can be sure that their data is being handled properly when companies give them clear explanations up front. People are less likely to be skeptical when they can see the direct link between what they share and the benefits they get.

b) Stay away from “Creepy Personalization”

Not all personalized things are good. When you use too much data or show it in the wrong way, it can cross the line into what people think of as “creepy personalization.”

For instance, a brand that talks about very private information in public or makes assumptions based on information that isn’t related can make customers feel uneasy. Even when the information is correct, messages that are too pushy feel more like manipulation than help.

c) The basic rule is to focus on being helpful, not being overly aware

Suggest products based on preferences that customers have clearly stated, not on subtle behavioral cues that customers didn’t know were being tracked.

Don’t use personalization to show off how much the brand “knows.” Instead, use it to make decisions easier.

Don’t include sensitive topics like health issues or money habits in marketing messages unless the customer has given you permission to do so.

Customers like personalization when it feels like help instead of spying.

d) Clearly explaining the value exchange

Trust-based marketing is based on the idea of value exchange. Customers will share information if they know what they will get in return. The relationship gets weaker, though, if the exchange feels one-sided, with the brand getting something but the customer not.

e) To talk about value in a way that works:

  • Emphasize immediate benefits: “Tell us your favorite categories, and we’ll send you exclusive discounts only in those areas.”
  • Focus on long-term benefits: “By telling us what you like, we’ll keep making your shopping experience better so it’s easier and more relevant.”
  • Show off special rewards like loyalty bonuses, VIP access, or personalized experiences that show the customer how much you value their feedback.

Customers are more likely to share if they know exactly what they’re getting in return, and they’ll be happy afterward.

Not only is it a legal requirement to balance personalization and privacy, it’s also a brand requirement. Companies can use zero-party data to personalize experiences with accuracy and integrity, but only if they use it properly. Businesses can make sure that personalization builds trust instead of breaking it by being open, not going too far with “creepy” behavior, and clearly explaining the value exchange.

Personalization should feel like a service, not like spying. Customers are more likely to stay loyal for a long time if they feel like their data is being used only to improve their experience. When used responsibly, zero-party data is more than just a marketing tool; it’s the basis for long-lasting, trust-based relationships in a world where privacy is important.

Conclusion

It’s becoming more and more clear that the future belongs to brands that put trust, openness, and customer experience at the heart of their digital marketing strategies as the digital marketing world changes quickly. Zero-party data is more than just a new way to collect data; it’s the basis for a personalization model that will last for a long time and respects privacy while encouraging more interaction.

As third-party cookies become less common and privacy laws become stricter, marketers can no longer depend on old ways of tracking. Zero-party data is a long-term option because it is based only on what customers agree to and choose to share.

Zero-party data is clear, while behavioral data is not. Customers are happy to tell you what they want, like their preferences, plans to buy, or how they like to communicate. This makes personalization more precise, useful, and successful. Because the exchange is open, it also lowers compliance risks and boosts the brand’s reputation at the same time. In other words, zero-party data is the safest and most effective tool for marketers to use in the future.

Personalization has always been a strong way to keep customers coming back. But without trust, even the most advanced personalization can seem pushy or manipulative. This is where zero-party data really shines: it lets you create highly personalized experiences based on trust.

Customers who tell us what styles they like get product suggestions that are actually in line with their tastes. People who subscribe and choose what they want to see get emails that feel like they matter, not spam.

When loyalty program members get offers for their favorite rewards, they feel valued. These experiences make the connection between the brand and the customer stronger because they show that the brand is paying attention and responding in a thoughtful way. The end result is not just a sale, but a long-term relationship.

Begin with a small amount and then grow. One good thing about zero-party data is that brands don’t have to change their whole marketing system all at once. Instead, they can start small, try things out, and slowly grow.

Some useful first steps are:

  • Adding a place for people to choose their preferences when they sign up for email.
  • Using a simple quiz or survey to find out what customers want.
  • Giving people small rewards, like access to exclusive content or discounts, in exchange for information.

Businesses can use the data they collect to improve their CRM systems, make their personalization strategies more effective, and move on to more advanced methods like gamified experiences or loyalty-driven personalization. These small steps will eventually lead to a strong and future-proof framework for personalization.

Zero-party data is a shift from extractive marketing to collaborative marketing, where customers are active participants instead of passive targets. This change is not optional; it is necessary.

Brands that can earn and keep customers’ trust will be the ones that do well in marketing in the future. In a crowded market, those who put value, respect, and honesty first will stand out. Zero-party data is the key that lets businesses personalize their services without losing trust. In short, the brands that will do well in the future are the ones that people trust now.

mrge Releases New Industry Report “State of Commerce Advertising 1/2026”

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mrge Releases New Industry Report “State of Commerce Advertising 1/2026”

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Why Reach Is No Longer Enough: Authority Emerges as the New Success Factor in Commerce Advertising

mrge, the leading commerce growth suite for Commerce Advertising, has published its semi-annual industry report, “State of Commerce Advertising 1/2026”. The results are based on a survey of publishers, advertisers, and networks and highlight key developments and success factors in the market. As the industry evolves and consumers’ behaviour around research and discovery changes, one clear theme emerges: consumers are seeking authoritative publishers and sources of information. Publishers must evolve from being traffic providers to trusted authorities, with direct implications for budgets and partnerships.

Marketing Technology News: MarTech Interview with Michael McNeal, VP of Product at SALESmanago

The report shows that the industry is lagging behind this paradigm shift, with a significant gap between industry evolution and organizational maturity. At a time when AI summaries are becoming more important than search ranking, we’ve found that just 11.3% of companies consider themselves very well prepared for the era of ‘zero-click discovery’, while 32.8% report being not prepared at all or only slightly prepared.

“We are experiencing the next evolutionary stage in Commerce Advertising,” says Dave Reed, CEO of mrge. “As consumers increasingly rely on AI-summarised results and turn to publishers they trust, brands need to navigate a new landscape, reaching consumers in the right contexts at the right price with the right data-driven optimization. In this landscape, publishers need the tools to effectively maximize their yield across the waterfall and spot areas of value where they can increase both monetization and advertiser ROAS.”

Further key findings from the survey include:

  • AI agents are shaping purchase decisions: Nearly 60% of respondents already see AI agents as influencing online sales or in the near future. They expect that by the end of the year at the latest, more than a quarter of their online revenues will be influenced by AI-powered chatbots and shopping assistants during the purchase decision phase.
  • Balancing stability and change: Companies are responding to the phenomenon of ‘zero-click discovery’ with a dual-track approach. On the one hand, they are compensating: 37.2% are strengthening their affiliate partnerships and 33.5% are increasing paid media budgets to offset traffic losses. On the other hand, they are transforming: around one third (31.7%) are optimizing content for AI-led discovery, while 22.6% are already testing AI-driven shopping assistants and marketplaces directly.
  • Budgets follow measurable results: In 2026, investments will primarily flow to areas where purchase intent can be clearly measured. 66.7% expect the largest budget increases in affiliate marketing, followed by social commerce at 36.7%. By contrast, AI-driven discovery, at 27.1%, is not yet a primary budget target.
  • More than a traffic issue: AI-driven, zero-click discovery also presents organizations with structural challenges. Beyond declining visibility, respondents primarily cite inadequate measurement models, limited internal AI expertise, and a lack of organizational and cultural change readiness as key barriers.

Despite these profound changes, overall sentiment within the Commerce Advertising industry remains highly positive. More than 57% of respondents report being satisfied or very satisfied with their business performance in 2025. This confidence is also reflected in expectations for the year ahead: over 63% plan to increase their Commerce Advertising budgets in 2026—underscoring the continued relevance and economic strength of Commerce Advertising.

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Stensul 2026 MarTech Outlook Finds AI Becomes Core Investment as Budgets Rise and Teams Shift Work In-House

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Stensul 2026 MarTech Outlook Finds AI Becomes Core Investment as Budgets Rise and Teams Shift Work In-House

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Research shows organizations investing in AI-powered workflows, internal enablement, and execution models built for speed and scale

Stensul released the 2026 MarTech Outlook, a new proprietary research report indicating that 2026 will be a growth year for marketing technology budgets and a turning point for AI adoption. The findings show organizations increasingly treating AI as a core MarTech investment, alongside efforts to modernize workflows and build internal capability to execute faster.

Marketing Technology News: MarTech Interview with Michael McNeal, VP of Product at SALESmanago

The research also points to an operating-model shift as marketing teams prioritize enablement and reskilling over outsourced campaign support, signaling a move toward AI-enabled in-house execution.

“AI has moved beyond experimentation and into the center of the MarTech roadmap,” said Rachel Meranus, Chief Revenue and Marketing Officer of Stensul. “What stands out in this research is that companies aren’t just investing in tools—they’re investing in the training and workflows required to make AI work day-to-day.”

Report highlights

  • 79% of organizations expect an increase in marketing technology budgets in 2026.
  • AI-powered tools rank as the top planned MarTech investment for 2026.
  • Organizations are prioritizing in-house enablement, with 57% planning to invest in AI reskilling for teams.
  • 31% of respondents plan to reduce spending on external agencies for campaign execution, reflecting a shift toward internal capacity.

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Qlik Connect 2026 Expands Keynote Program as Enterprises Prepare for the Next Wave of AI

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Qlik Connect 2026 Expands Keynote Program as Enterprises Prepare for the Next Wave of AI

Qlik

New featured speakers Jason Del Rey and Dr. Rumman Chowdhury join an expanded program focused on helping organizations make their data work for AI, with accountability and measurable impact

Qlik®, a global leader in data integration, data quality, analytics, and artificial intelligence (AI), announced an expanded program for Qlik Connect® 2026, taking place April 13–15, 2026 at the Gaylord Palms Resort and Convention Center in Kissimmee, Florida. As more organizations move from AI experimentation to scaled deployment, the conversation is shifting from what AI can generate to what teams can reliably operationalize in real workflows. The next wave will favor organizations that can make their data work for AI with the governance, transparency, and control required to act with confidence.

Qlik Connect 2026 will bring together customers, partners, and industry voices to explore what it takes to make your data work for AI as organizations move from experimentation to accountable action in real workflows. The program spans mainstage keynotes, featured customer sessions, and strategy briefings focused on what is changing in the market, what accountability requires, and how teams can do data differently to bring it all together, including the data and operating model needed for what comes next.

Newly announced featured speakers include:

  • Jason Del Rey, founder and author of The Aisle, an independent publication covering how AI is reshaping commerce. Del Rey has reported on emerging technologies across Silicon Valley and global retail for more than a decade, previously serving as a technology correspondent at Fortune and a senior correspondent at Recode. He also co-chairs the Fortune Brainstorm Tech and Fortune Brainstorm AI conferences.
  • Dr. Rumman Chowdhury, founder and CEO of Humane Intelligence, a nonprofit advancing ethical, explainable, and accountable AI through rigorous algorithmic evaluations. Chowdhury previously led Twitter’s META (ML Ethics, Transparency, and Accountability) team and has served on global advisory bodies including the UK Centre for Data Ethics and Innovation, the UN Broadband Commission for Sustainable Development, and Oxford University’s Commission on AI and Governance. She also serves on Qlik’s AI Council.

The two industry luminaries will join Qlik Chief Strategy Officer James Fisher for a conversation looking at what’s next in AI and strategies for the audience to consider in their roles as data professionals. The session will also feature audience interaction as the speakers discuss the near and longer-term opportunities in AI.

Marketing Technology News: MarTech Interview with Michael McNeal, VP of Product at SALESmanago

The Qlik Connect 2026 keynote program also includes previously announced guest speaker Jesse Cole, Founder of Fans First Entertainment and Owner of the Savannah Bananas, and an impressive lineup of customers offering their perspectives on the importance of a strong data strategy as foundational for AI success and business return on technology investments.

“AI is moving from an interesting capability to an operational expectation, and the moment it touches real decisions, trust becomes a hard requirement, not a slogan,” said Mike Capone, CEO of Qlik. “At Qlik Connect, we will focus on how organizations make their data work for AI so they can move faster while staying transparent, auditable, and in control as agentic automation becomes part of everyday work.”

“Qlik Connect is where we pressure-test what’s next through three lenses: what’s changing in our operations, what accountability requires, and how to close the loop from insight to action in the systems we run,” said Mark Green, Head of Data, Analytics and Insight, South Central Ambulance Service NHS Foundation Trust. “We leave with practical steps we can implement now, and a clear path to be ready for what’s coming next.”

Qlik Connect 2026 will feature keynotes, customer-led sessions, and hands-on learning designed to help organizations operationalize data, analytics, and AI with speed and control, including:

  • Keynotes and industry perspectives on how AI is reshaping business models, decision-making, and customer expectations
  • Strategy and outlook sessions led by James Fisher, Chief Strategy Officer, focused on what enterprises should plan for in the near term and longer term
  • Customer sessions and technical breakouts highlighting implementation lessons, governance patterns, and measurable outcomes
  • Product and roadmap sessions, previewing Qlik’s upcoming agentic capabilities and MCP-based interoperability, designed to help teams move from insight to governed action
  • Hands-on workshops and training, plus partner demos and structured networking

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Qubika Launches QBricks, Built on Databricks: An Enterprise Accelerator for AI Agent Development

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ReachLabIQ Launches SEO for AI Consulting Services to Elevate Content Marketing

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Qubika has announced the public launch of QBricks, a Built on Databricks enterprise accelerator designed to speed up the development, evaluation, and deployment of AI agents at scale. Already in use with multiple clients, QBricks provides a centralized platform covering the full AI agent lifecycle, with built-in scalability, observability, and compliance with standards such as SOC 2, GDPR, and ISO 27001.

Qubika, a leading provider of enterprise data and AI services, today announced the public launch of QBricks, a Built on Databricks solution and comprehensive enterprise accelerator that streamlines the development, evaluation, and deployment of intelligent agents at scale.

Already in active use across numerous clients of Qubika, QBricks serves as a centralized platform for the full lifecycle of AI agents – ensuring scalability, observability, and compliance with standards including SOC 2, GDPR, and ISO 27001.

QBricks dramatically accelerates time to value when building AI agents. It means development teams don’t have to spend time setting up the infrastructure, building connectors, setting up monitoring, building a security infrastructure – or any of the other numerous tasks that agents require.

Marketing Technology News: MarTech Interview with Michael McNeal, VP of Product at SALESmanago

Key Benefits of QBricks

  • Secure & compliant – Runs natively on the Databricks Data Intelligence Platform, ensuring adherence to SOC 2, GDPR, and ISO 27001 frameworks.
  • Enterprise-grade data privacy – All data remains encrypted, access-controlled, and fully contained within the customer’s cloud or preferred environment.
  • Cloud & Databricks integration – Connects seamlessly to Databricks and can be deployed across any enterprise cloud or infrastructure setup.
  • Reusable, standalone code – Agents function independently of Qubika and can be executed on any mainstream agent orchestrator, ensuring no vendor lock-in.

Core Capabilities

QBricks delivers a powerful suite of capabilities designed for production use:

  • Pre-built agents and a library of workflows
  • Visual agent workflow builder
  • Evaluation framework
  • End-to-end observability dashboard
  • Production-ready agent ecosystem

The accelerator provides a curated library of agent templates covering common enterprise patterns such as RAG systems, translation workflows, and API-driven automations.

QBricks is a Built on Databricks solution. The Databricks Data Intelligence Platform democratizes access to data and AI, making it easier for more than 20,000 organizations to harness the power of their data for analytics and AI apps and agents. Built on an open-source foundation, the platform enables organizations to drive innovation to increase revenue, lower costs, and reduce risk. QBricks is built with Databricks Lakebase, Vector Search, and GraphFrames.

Leadership Commentary

Sebastian Diaz, SVP of Data & AI at Qubika, commented that “The key differentiator of QBricks compared to other low-code/no-code AI workflow builders is that it has native data integration with data platforms and external data sources. We ensure that the agents developed are fully portable and our clients can continue to manage, deploy, and evolve them completely independently. In addition, the library of pre-built agent templates (RAGs, translators etc) makes it a highly attractive offering to enterprise clients.”

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Kentico Unveils Major AI Leap Bringing Agentic AI Workflows to Marketing Teams

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Kentico Unveils Major AI Leap Bringing Agentic AI Workflows to Marketing Teams

Kentico announced the launch of the AIRA Agentic Marketing Suite, extending its AI strategy within Xperience by Kentico. The new suite introduces specialized agents designed to execute defined marketing and content tasks, underscoring Kentico’s belief that AI should be operational, transparent, and embedded directly into how teams work.

AIRA: The Foundation of AI-Powered Marketing   

Launched in 2025, AIRA (Artificial Intelligence Recommendations & Assistance) provides marketers with embedded tools that reduce repetitive work and simplify daily tasks. AIRA offers everything from automatic translation and content tagging to campaign ideation, customer journey insights, instant product guidance, all accessible through an in-product conversational chat interface and intuitive in-context icons.

These built-in capabilities are available directly within the Xperience by Kentico platform, giving users an immediate productivity boost, without the need for extra add-ons or integrations.

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

Introducing the Agentic Marketing Suite: Marketing’s Virtual Team   

The AIRA Agentic Marketing Suite represents a major expansion of AIRA’s capabilities, evolving it from an assistive tool into an orchestrated system of specialized AI agents that support the full marketing lifecycle, from strategy and content creation to optimization and campaign execution.

These agents function as dedicated virtual collaborators, designed to assist marketers with specific tasks. Among the first available is the Content Strategist, which helps shape and refine content strategies through intelligent analysis and recommendations.

Additional agents will be introduced as part of our ongoing release, expanding support into areas such as campaign management, market analysis, and workflow optimization, with each addition focused on improving speed, precision, and impact for marketing teams.

Marketers have no shortage of ideas. What they need is the bandwidth to bring them to life,” said Dominik Pinter, CEO at Kentico. “With the Agentic Marketing Suite, we’re giving teams a way to scale their expertise, cut through complexity, and deliver results faster”.

Marketing Technology News: From MarTech Stack to MarTech Fabric: Weaving Brand, Content, and Conversion Into One Thread

Looking Ahead   

The launch of the Agentic Marketing Suite marks a significant milestone in Kentico’s vision to redefine how marketers work with AI, not as a tool, but as a trusted team. With more specialized agents planned, continued AIRA enhancements, and an upcoming AI-powered chatbot designed to turn on-site search into conversational customer journeys, Kentico is committed to helping marketers build faster, market smarter, and dream bigger.

About Kentico

Kentico is a content management system and commerce platform, with built-in digital marketing and AI capabilities that help deliver personalized customer experiences through websites, microsites, emails, and other digital channels. It consolidates marketing tools to improve efficiency, drive stronger customer engagement, and reach business goals faster.

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Zyxel Communications to Unveil New AI-Powered Management Solution, Wi-Fi 8 and 50G Fiber at MWC 2026

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Zyxel Communications to Unveil New AI-Powered Management Solution, Wi-Fi 8 and 50G Fiber at MWC 2026

Zyxel

Discover how Zyxel sets new standards for AI-powered management and next-generation connectivity, helping internet service providers deliver smarter, more reliable service for their subscribers.

Zyxel Communications, an industry-leading provider of cutting-edge broadband and AI-powered management solutions to service providers worldwide, announced plans to showcase next-generation innovations at Mobile World Congress (MWC) 2026, taking place March 2–5 at Fira Gran Via in Barcelona.

At Hall 5, Stand 5I20, Zyxel will showcase Wi-Fi 8, present its latest 50G fiber solutions, and host a special area where experts will introduce Zyxel One, its new AI-powered management solution.

“Mobile World Congress is a key opportunity for us to demonstrate not only where connectivity is headed, but how Zyxel continues to lead the innovation that directly increases value for service providers,” said Nicolai Redfern, Product Director at Zyxel Communications. “This year, visitors can experience groundbreaking technologies including Wi-Fi 8, Zyxel One, 50G Fiber and more, all designed to keep service providers ahead of the competition.”

Marketing Technology News: MarTech Interview with Michael McNeal, VP of Product at SALESmanago

Zyxel One

At the show, Zyxel will showcase Zyxel One, its new AI-powered solution that sets a new standard in intelligent network management, built for service providers and their subscribers. Zyxel One enables proactive network monitoring, automated optimization, and faster issue resolution across a pre-integrated portfolio supporting all major access technologies. This helps service providers to simplify operational complexity, reduce support costs, benefit from a shorter time to market through pre-integration, and enhance subscriber satisfaction.

Wi-Fi 8 Preview

At MWC 2026, Zyxel will offer a preview of its upcoming Wi-Fi 8 solutions. Zyxel experts will be on site to share thorough insights into the technology and how it enables ultra-low latency for real-time applications, improved stability in dense residential environments, and smarter support for increasingly complex smart-home and IoT deployments.

50G Fiber

Visitors to the Zyxel stand can also explore the company’s next-generation 50G optical access solutions, featuring its end-to-end NeoX portfolio, designed to help service providers scale efficiently and deliver the ultra-high performance required for future-ready broadband networks.

Zyxel’s broader product lineup on display will include industry-leading innovations across Wi-Fi 7, 5G FWA, 10G fiber, and more.

Visitor Experience

Beyond the technology, Zyxel will host its popular Beers, Bubbles & Broadband social event, offering attendees the opportunity to connect with Zyxel experts and peers in an informal setting.

Zyxel’s global team of service-provider specialists will be on site throughout MWC 2026 to discuss emerging industry trends, share real-world deployment insights, and explore how service providers can simplify operations while delivering exceptional subscriber experiences.

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Ecer.com Drives Cross-Border B2B into the Mobile-First Era

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Ecer.com Drives Cross-Border B2B into the Mobile-First Era

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As the digitization of global trade accelerates, the landscape of international commerce is shifting from fixed desktops to the palms of buyers’ hands. Recent data reveals a pivotal trend: over 70% of cross-border B2B sourcing now occurs on mobile devices, transforming business from a desk-bound chore into a flexible, real-time “pocket collaboration.”
Under this trend, Ecer.com (www.ecer.com), as an early B2B maketplace to embrace mobile technology, has gradually established a new form of cross-border trade centered around mobile devices through continuous technological iteration and product restructuring, making “conducting foreign trade anytime, anywhere” a feasible and replicable daily capability for enterprises.

Breaking the Time Barrier
In the traditional trade model, time zone differences and back-and-forth emails often extended communication cycles to several days. Ecer.com, an early pioneer in mobile B2B infrastructure, is changing that narrative. By integrating real-time messaging, instant multi-language translation, and high-definition audio/video capabilities, the platform enables “minute-level” responsiveness. This 24/7 connectivity ensures that international buyers can initiate inquiries or remote inspections at any moment, drastically increasing overall order processing efficiency.

From 8 Days to 2 Hours: The Power of Virtual Trust
Trust is the hardest currency to earn in B2B trade. To bridge the physical gap, ECER has migrated core offline processes—such as factory inspections and product demonstrations—to a mobile-centric, visual experience. Through 360° VR factory tours and 3D product modeling, overseas buyers can evaluate suppliers as if they were standing on the factory floor.
The impact is measurable: the traditional decision-making path, which typically averaged 8 days for onsite inspections, has been compressed to approximately 2 hours.
Guangzhou Micron Vending Technology Co.,Ltd targeting the European market previously spent over a week navigating email chains and third-party inspections. By utilizing ECER’s mobile panoramic inspection tool, the buyer was able to remotely verify production lines and quality control processes via smartphone. The result? The supplier evaluation and the first order were confirmed within the same day.

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A Complete Trade Ecosystem in Your Pocket
ECER has moved beyond simple tools to build a comprehensive mobile collaboration system that covers the entire trade lifecycle:
• Intelligent Response: AI-powered customer service handles global inquiries 24/7.
• Visual Confidence: VR and 3D displays boost communication and trust.
• Instant Access: Direct audio and video links connect buyers to key decision-makers.
• Ecosystem Integration: Seamless connectivity with global tools like WhatsApp extends the reach of the trading network.

The New Infrastructure of Global Trade
The fusion of mobile technology and AI is flattening international trade, closing the gap between information exchange and final decision-making. As ECER’s practice demonstrates, when trade is freed from the constraints of space and hardware, business becomes a natural, anytime-anywhere occurrence. For enterprises embracing this mobile evolution, it is more than just an upgrade—it is the cornerstone of their future competitiveness.

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