Unlocking the Power of AI in Customer Data Platforms

Businesses amass vast amounts of customer information from a variety of touchpoints. To harness this data to create personalized experiences and drive tangible business outcomes, Customer Data Platforms (CDPs) are becoming increasingly important. 

A CDP is a packaged software solution that consolidates and unifies customer data from sources like online interactions, in-store purchases and mobile app usage. By creating a single, comprehensive customer profile, CDPs empower marketing, sales and customer service teams to deliver personalized experiences for each customer. When this specialized software is integrated with Marketing Technology (MarTech) tools, it ensures data is utilized consistently across marketing channels. CDPs democratize data access, allowing you to effectively leverage customer insights.  

These platforms can do a lot, but if you want to supercharge your data and your CDP – from improved efficiency and optimized costs to more deeply tapping into your customers’ expectations – consider integrating with custom algorithms.   

AI-Powered CDPs: Tailoring the Customer Experience

CDPs are designed to consolidate and manage customer data from diverse sources like websites, mobile apps, CRM systems and social media. But, as the number of touchpoints and amount of data grows, traditional methods are failing to extract meaningful insights. 

While CDPs excel at data consolidation, they sometimes fall short in realizing their full potential. Take the limitations of third-party cookies, for example. They only identify customers through their browser addresses – leaving marketers to guess at connecting the dots of their customer profiles. Marketing teams need a more holistic view – which is where custom algorithms come into play. 

These personalization algorithms leverage machine learning (ML) and predictive modeling to enhance customer engagement and experiences. By analyzing customers’ behavioral data, these algorithms generate hyper-personalized recommendations, delivering targeted messages, promotions, and advertisements that resonate deeply with individual users. 

Consider this example: As a marketer, you might want to generate dynamic content based on specific conditions or triggers. Custom AI/ML algorithms can display products to consumers that align with their data, such as location, user behavior and pages visited.  

How does this work? The algorithms use AI to create a real-time propensity score for each user, predicting the likelihood of a pre-set action – this is predictive targeting. Machine learning algorithms analyze structured and unstructured data from all visitors, identifying patterns and mapping similarities. This, in turn, enables the prediction of user behavior. 

In another example, AI can enhance recommendations based on user group behavior, improving customer segmentation. For instance, when seeking financial services online, AI CDPs can suggest product recommendations that adapt to changing financial behaviors or market conditions, tailored to your selected parameters or customer preferences. The same approach applies to customer segmentation in healthcare, where AI improves patient engagement by personalizing content and suggesting treatment options based on health data. 

If you’re still curious about how AI maps customer preferences, think of AI playing a chess game. It predicts the best possible move by analyzing tens of thousands of individual chess matches. Similarly, custom algorithms analyze complex metrics, compare them to historical data and provide accurate recommendations based on that comparison. This process enables a deeper understanding and more precise prediction of behavior by analyzing data from sources including 

• Site navigation paths 

• View durations 

• Search refinements 

• Back-and-forth navigations 

The more data collected, the more accurate your predictions and the better your conversion rates become. 

Here are some examples of leading businesses using custom algorithms to improve outcomes. 

• Netflix is a streaming platform well-known for using custom algorithms. It would be nearly impossible to create a customized homepage for every visitor using traditional data tools. But Netflix uses a complex set of algorithms to determine visitors’ preferences and then highlights movies and TV shows that fit their viewing patterns and interests. 

• Amazon, the global e-commerce giant, customizes its home page to make recommendations to each shopper. Each experience is customized based on past purchases, searches and other user data. Despite Amazon’s virtually limitless options, its use of custom algorithms makes online shopping convenient, quick and easy. 

• In automobile manufacturing, Subaru’s journey with custom algorithms began when the company adopted a CDP to enhance audience segmentation, target sales efforts and personalize customer journeys. Within weeks, Subaru’s successful CDP integration surpassed its initial goals. Realizing the untapped potential within their data, Subaru has since leveraged post-purchase customer data and predictive analytics to innovate new products and services, leading to increased revenue and customer loyalty.  

CDPs are powerful solutions, but AI-enabled custom algorithms make them even more powerful. Here’s how: 

While integrating with an AI customer data platform offers significant advantages, it also presents challenges – such as the explainability of “black-box” ML models and the risk of biased decisions. These biases can arise from existing data inaccuracies or from the algorithm itself. However, once these concerns are addressed and mitigated through fairness audits and privacy-preserving techniques, AI-powered CDPs unlock several benefits: 

Accurate Customer Profiles

One of the primary advantages of AI/ML in marketing is enhanced visibility into customer data. AI-powered identity resolution cleanses and consolidates duplicative data into a single, accurate customer profile. This eliminates redundancies and inaccuracies, providing marketers with a clearer view of the customer journey. It also links unknown customer data to known profiles, enabling the identification of audiences with similar affinities or attributes. This allows for greater personalization and segmentation, as well as improved customer experiences for both known and unknown audiences. 

Data-Driven Campaign Optimization

AI optimizes customer segmentation based on behavior, enhancing ad performance through predictive analytics. This approach helps in  

• Identifying likely converters for tailored lead nurturing 

• Discovering upsell and cross-sell opportunities 

• Improving loyalty programs 

• Preventing irrelevant targeting of loyal, high-value customers 

Orchestrating the Customer Journey

With an AI powered CDP, brands can personalize the entire customer experience across all channels and touchpoints, extending beyond mere ad campaign optimization. AI’s key applications include predictive analytics for next-best-action recommendations. By analyzing customer data and profiles, AI delivers tailored content and messaging, enhancing value and timing. This data-driven approach aligns with customer journey orchestration, using insights from the CDP with AI to understand customer behavior at different stages. Marketers can plan and execute campaigns and guide customers through their journeys more effectively. Quality recommendations based on search and purchase history offer highly relevant and personalized content, ultimately boosting conversions and ad campaign performance. 

Increased Efficiency through Automation

The average marketer spends a significant portion of their workday on routine, repetition-heavy tasks, such as tagging content and images, segmenting clients and running manual campaigns. By utilizing an AI-equipped CDP, marketers can automate these routine activities, freeing up time for more thoughtful and strategic work.

Unlock AI’s Potential with Material 

AI is a game-changer that can enable businesses to make confident, data-driven decisions and optimize marketing efforts. If you’re interested in AI-powered CDPs, connect with Material today. Our experts are ready to help you harness the potential of your data.