The overall quality of CX in the digital marketplace has fallen over the recent months; Derek Slager, Co-founder & CTO and Amperity weighs in with a few observations and best practices:

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Welcome to this MarTech Series chat, Derek. Tell us about Amperity and the platform’s latest innovations.

Amperity is an end-to-end CDP that connects seamlessly with the leading tools for marketing, analytics, customer service and data management, pulling data in from digital and offline touchpoints to build unified customer profiles. Amperity has revolutionized how brands identify, understand and connect with our customers by using AI to deliver comprehensive and actionable customer profiles.

Our mission from the start has been to help every brand turn complex customer data into business value. With our customer data platform, we solve the fundamental data quality problem, and use the output of that to fuel the whole ecosystem. No one else creates a unified view of the customer as accurate, comprehensive, reliable, and interoperable as we do.

If a brand wants to know their customers — and stay on the right side of privacy regulations — their only choice is to unify and understand their own first-party data, collected with consent directly from the consumer, and put that to work across all their tools and teams. That’s where Amperity comes in.

When it comes to driving CX experiences: what do brands today still not get right, and what best practices would you share around this? 

The looming deprecation of third-party cookies is going to result in brands’ limited access to external data sources to support marketing and advertising strategies. This will be (and already is) detrimental to organizations using third-party data to secure customer insights.

Many brands still rely on third-party data to identify and understand their customers, but the data they’ve provided is often outdated and disjointed, causing them to miss out on a full view of the customer and their journey.

For instance, customers may be targeted with an ad for a product they’ve already purchased. This can negatively impact CX and lead to a distrust in brands. In 2022, CX quality fell for 19% of brands, with 49% of customers stating they left a brand they had been initially loyal to in the last 12 months due to poor CX. It’s more critical now than ever for brands to identify customer preferences to boost retention and drive company growth.

However, there has been a fundamental shift in data ownership and accessibility for all brands fueled by market conditions. This shift has presented unique challenges for brands. Namely, brands must now balance accuracy, reach, privacy, and agility to serve a rapidly growing set of evolving channels, divisions, & teams. Layer in confusing and very loud narratives from software companies, and finding the best approach becomes even more challenging. This complexity often results in paralysis, preventing brands from making comprehensive decisions in a unified direction which benefits all teams in a flexible, interoperable, and relevant way.

Companies can use CDPs to learn and predict customer needs based on clean, unified first-party data. By implementing these tools, brands gain a 360-degree view of their customer, enabling them to create marketing and advertising strategies that address buyers’ needs and desires and abide privacy laws.

How can identity resolution solutions specifically fix this challenge?

The digital customer journey is more fragmented than ever, making identity resolution a significant challenge for today’s brands. Without the ability to recognize a customer’s journey and create unified profiles, brands struggle to understand and meet customer needs.

Identity resolution allows brands to create comprehensive views of their customers and maximize learnings from previous customer experiences to improve retention. An effective ID resolution tool will offer advanced artificial intelligence and machine learning capabilities that produce algorithms to help separate clean data from dirty data. This allows brands to have a clear view of each customer and enables teams to provide world-class CX based on accurate and up-to-date information.

For example, when trying to match records when an account ID is not present in both records, it requires using data that is messy and unreliable. Last name, address, and email change over time. People often have a formal name and a nickname. Device IDs can be shared across people within a family. ID resolution needs to find accurate matches based on messy data and often unreliable data.

In addition, identity resolution needs to be able to store and compute matches over very large data sets. Matching two records together is easy. As the number of records grows, the required comparisons grow exponentially. For record sets in the millions, it’s theoretically in the quadrillions of comparisons which is computationally expensive. Even with intelligent blocking techniques (to reduce the number of required comparisons), doing so requires sophisticated management of the significant compute resources.

ID resolution also requires integrations with dozens of data sources. Managing it efficiently requires pre-built integrations, tools to rapidly add new integrations, and tools to monitor the health of integrations. Identity is a constantly evolving space which requires dedicated resources to monitor and react to all the changes in privacy regulation and new requirements.

For brands considering the use of these types of tools for the first time, what should they keep in mind when implementing and setting them up as part of their tech stack? 

There are a number of things brands should consider before implementing ID resolution.

1. Legacy third-party-based ID resolution solutions still exist, but are wildly ineffective. The best data to support ID resolution is a company’s first-party data.
2. Before companies invest in ID resolution tools, ensuring all their customer data is in one centralized location is critical. This can be done using a customer data platform.
3. No business is identical. Each company needs the flexibility to customize ID resolution for its business without starting from scratch.
4. Privacy compliance is also an essential step in data gathering and utilization. However, brands should think of privacy regulations as an opportunity to build customer trust, not create a barrier. ID resolution offers a responsible and transparent way for brands to leverage customer insights to inform CX and engage with their buyers.
5. Some CDPs, such as Amperity, which has 9 patents for ID resolution, were designed with ID resolution in mind as a critical value-add for users. These organizations have also developed their solutions with consumer privacy top-of-mind, developing flexible tools that empower brands to maximize the customer data that’s available to them ethically and responsibly.

What are the five top personalization mistakes brands often make despite having access to tools to help drive this part of the process?

Not pulling data from multiple channels.

Customer engagement has moved beyond email to SMS, mobile, and direct engagement on social media networks. This has led to the birth of new martech systems driving that engagement. And this, in turn, has created the need to have an “omnichannel view” of the customer that is central and can manage that connection. As omnichannel retail becomes more popular, it’s crucial that marketing teams leverage the data they receive from each channel to create informed customer profiles.

Not taking data privacy seriously.

It’s more important than ever that brands are transparent in how they secure and use consumer data. Many brands are focused on collecting mass amounts of data rather than prioritizing what they are allowed to collect, what they can do with it, and what they need to disclose to customers.

Overlooking the impact of personalized marketing strategies on other business areas.

Personalizing customer experiences can have a trickle effect on other areas of a business. For example, suppose a brand identifies a rise in popularity of a particular product and promotes it to customers who have expressed interest. In that case, they also must ensure that inventory is stocked and prepared to support a potential increase in sales.

Executing marketing campaigns with outdated data.

Consumer trends and demands constantly shift, and marketing and advertising tactics should, too. It’s paramount for organizations to use the tools at their disposal to ensure the data that’s informing strategy is accurate and up to date.

Not preparing for the depreciation of third-party cookies.

Google plans to scale back the use of third-party cookies in early 2024, and brands need to take action now to ensure they’re prepared and that their marketing and digital advertising strategies are using data that will be available long-term.

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If you had to share five thoughts about the state of martech and CX in the next decade, what would it be?       

First-party data will take the driver’s seat.

Once third-party cookies are no longer available, brands will collect and utilize first-party data to build customer relationships and personalized CX.

AI will move the needle on hyper-personalization.

Marketing technology and customer experience will rapidly evolve towards hyper-personalization driven by advanced AI tools, similar to what we see with platforms like ChatGPT and Bing AI.

Brands will leverage vast amounts of data to tailor customer interactions in real time, offering highly personalized experiences across various touchpoints to enhance customer satisfaction.

Consolidated martech stacks and increased overlap of marketing and advertising.

Martech stacks will be reduced from one tool for every task to a couple of solutions that can perform and support multiple tasks and processes, such as data gathering, consolidation and ad targeting. This will lead to overlap in marketing and advertising strategies, enabling brands to spend their demand generation dollars more strategically.

Privacy-first marketing.

The introduction of GDPR and CCPA is the manifestation of changing consumer and regulatory views on customer data. This in turn creates a requirement for brands to centrally manage information about the customer, with enough financial penalties to make this a necessity. Brands must prioritize securing consent for data usage and implementing robust security measures.

The collapse of cookie-based adtech.

Most brands still spend most of their marketing dollars on cookie-based ad tech systems. These systems have been decaying for some time, but now have reached a tipping point where that decay is showing up in the results that fuel ad spend but fail to produce results. Match rates are down and dropping, conversion rates are falling, and email engagement is no longer visible and measurable – taken together this means that brands are struggling to find audiences, drive engagement, and measure success on this fuel.

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