It’s a tale as old as e-commerce – your team has poured everything it has into building the perfect martech stack. You’ve got all the hottest platforms, your CRM is on point, and your decisioning engine is state-of-the-art. But, you’re just not realizing the results you expected. Conversions remain stagnant. Your campaigns fail to resonate. What gives?

The issue doesn’t lie in your actual decisioning tech itself, but in your data tech – you’re not set up to capture and ingest the data your decisioning tool needs. You’re not focused on solving for digital identity or building detailed, cohesive customer profiles. You must bring together customer profiles and digital identity along with journey building so your journey has a passenger.

Garbage in, garbage out. You’re relegated to what you capture – half the story just won’t cut it anymore.

The lag time of feeding your system with data from interaction to next-best-action is also, well…not helping. Without actually solving for digital identity and building profiles, you simply can’t look at the 360-degree view of the customer. You need adequate, high-quality, reliable digital identity data to feed your decisioning engine or even the most advanced platform can’t work to its full capacity. So before you rip and replace your entire martech stack, take a step back. Ensure you’re feeding your system the digital identity and insights it needs.

Here’s why optimizing the power behind these systems matters in the first place:

Optimizing your decisioning strategy means taking a hard look at your data sets and data capture tools. Are you able to persist consumer identity across multiple sessions, devices and platforms? Or are you experiencing multiple profiles or identities for the same user that has interacted with your brand on multiple occasions? Are you truly able to follow the user journey and understand how someone is interacting with you? If the answer is anything less than a resounding “YES!” taking a hard look at how optimizing your digital data forces a solution to your digital identity and customer profiles challenges.

With a solid decisioning strategy, you can provide extremely personalized experiences that make customers feel understood, mimic a level of customer service similar to an in-person experience, and keep customers coming back. By translating their needs and preferences over the entire customer journey, you serve the right message, product, or offer at the right time. These tailored experiences build trust and are key to building a valuable customer loyalty program.

Individual session and historical data allow you to make smarter decisions that drive conversions, but one without the other gives you a limited view and limits the power of your decisioning engine. Understanding how a customer shops, when they buy, and offers that are meaningful (ie. they convert on) is the foundation of a best laid customer conversion plan. Well-timed, data-driven decisioning leads to higher conversion rates and more revenue.

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With a decisioning solution that taps into all your data, your brand can adapt quickly to changes in the market or customer preferences. As new data comes in, the system learns and adjusts automatically to optimize the customer experience. This constant optimization and ability to pivot based on the latest data ensures your customer experiences stay highly relevant into the future.

Data quality can make or break your decisioning engine’s functionality and power.

When it comes to digital decisioning, the quality of your data is everything. Your decisioning engine is only as good as the information it has to work with. If you feed your decisioning platform flawed, incomplete, or outdated data, the insights and recommendations it produces will be less than stellar.

Siloed data is useless for decision making. Collecting and aggregating high-quality data across channels, platforms, and devices ensures your systems have a full picture of who the customer is, how they interact with your brand, and over time, their preferences. Think single customer view.

Outdated or batch data won’t cut it – you’ll be left with a platform that makes decisions long after the customer has ended their interaction with you. Leveraging a platform that collects – and connects all your customer PII and digital interaction data in real time, gives you the capacity to leverage your digital decisioning platform to make decisions and take action instantly based on the full, real-time customer profile. The old saying, ‘A bird in hand is better than two in the bush’ becomes reality – interact with those interacting with you and convert them in the moment.

Decisioning and AI without good data leads to bias. As you collect, connect, and ingest volumes of data, ensure you’re applying machine learning and AI ethically. Ethical AI is important, especially as you determine who and what to show as an offer to varying individuals. You must have the right digital identity data for you models to train off of.

Machine learning should be used to identify patterns, predict customer needs, and optimize decision making. It sounds straight forward, but without the right quantity of quality data, this advanced tech is underutilized with decisioning systems.

As machine learning algorithms and AI models learn, analyzing more data and interactions, the capacity to truly understand a single customer grows. Your tech is better equipped to recognize new patterns and unlock valuable predictive abilities. True one-to-one personalization becomes possible and transforms decisioning from a blunt tool into a precision instrument.

Overall, the capacity of your digital decisioning platform is only as strong as the quality of data it receives. Without clean, accurate data that truly reflects your customers and prospects and that lands in your system while the customer is still interacting with you, even the most robust of decisioning tools and predictive models will fail you.

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Episode 203: Sales Trends Dominating 2024 with Andy Kankula, Vice President of Business Development at Sion Power