Tealium Predict Machine Learning

Anticipate Customer Behavior
Data about your customers‘ past behaviors holds clues to their future behaviors.  When you can accurately predict future behaviors, you can take action to shape them toward better outcomes. Tealium Predict ML uses the power of machine learning to predict the likelihood of any behavior you’re tracking in Tealium AudienceStream Customer Data Platform.

Now you can anticipate when a customer will make a purchase and take action to increase revenue. Or identify prospects who won’t purchase and suppress them from advertising to save costs. The possibilities are endless!

Learn What Data Points are Predictive
Tealium Predict ML shows you exactly which customer data points are used by your custom-tailored models to create predictions, as well as how important each data point is to the prediction. By getting insights into the most important behaviors you can craft better customer experiences that more effectively support your goals.

When predicting a purchase, for example, you might see that a particular video view, or offline interaction is critical. Or if predicting cart abandonment, you might see a particular device overly represented, implying there may be a bug. Armed with these insights, you can take action to produce better results.

Machine Learning Insights “In-Line” with Your Customer Data Supply Chain
Machine learning projects are notoriously resource-intensive. Even if you have a good model, it can be hard to feed it enough high quality data. Once you figure that out, it can be even more time-consuming and difficult to activate those insights so they’re actually benefiting your customers.

Tealium Predict ML coupled with AudienceStream CDP is the lowest cost and lowest risk way to simultaneously solve these challenges. Predictions simply become another data point in the customer profile that can be activated using our industry-leading integration marketplace. All of a sudden, machine learning capabilities are sitting in-line with data collection and activation, powering your whole tech stack.

Automatically Identify and Target the Best Prospects and Customers
Pick any customer goal you’re tracking and score every user’s likelihood to achieve it. It’s that easy. You can use that score to drive action using Tealium’s 1,300+ integrations. Knowing which users will or won’t convert lets you focus your time and budget where it will have the most impact. Your entire stack becomes ML-enabled regardless of native capabilities.

Potential Use Cases

Likely to Buy: Focus budget on prospects who are most likely to buy

Loyalty Campaigns: Target customers most likely to join

Abandoner Campaigns: Target prospects who are most likely to come back

Make Existing Audiences Smarter
Whether you’re running campaigns for acquisition, retention or support, layer in ML insights with your existing audiences to make them better. This means you can target the ‘sweet spot’ and provide the most relevant experience possible. Marketing just got a whole lot more personalized.

Potential Use Cases

„Intelligent“ Cart Recovery: Only target those who will come back and buy

High Value / VIPs: Amplify engagement with those who are likely to become high value

Suppress Poor Targets: Exclude users with low likelihood to convert

Better Customer Acquisition, Retention and Support
Whatever your goal along the customer journey, Predict can provide insights. With these ML insights, you can more strategically engage prospects and customers. You can suppress low likelihood users, and focus on the users most likely to help you achieve your goals.

Potential Use Cases

Support Intervention: Identify those who need help and proactively engage

Retention Campaigns: Engage customers who are at risk of churning

Acquisition: Only target those who are likely to buy

Augment ML Projects
ML projects are notoriously slow, difficult, and rigid. They require a lot of data wrangling and integration efforts. With Predict ML added to the Tealium AudienceStream Customer Data Platform, there’s already a rich customer dataset and the integrations to put that data to work. Data science teams get an agile and actionable complement that makes it a breeze to collaborate with other business users.

Potential Use Cases

Rapid Insights: No data-wrangling required to apply ML to customer data

Collaborate with Marketing: ML insights right where marketing campaigns are triggered

Streamline Exploratory Analysis: Reduce time sifting through data with access to automated, but configurable insights