Unlocking the Potential of The Prospect Data Platform: Use Cases to Boost Your Business Growth

In our last post we introduced the Prospect Data Platform (PDP), the newest essential tool for growth marketers. In today’s post, we continue our introduction by discussing PDP's key offerings, and how consumer brands across the D2C space can benefit from integrating a PDP into their marketing stack.

If you missed our first post introducing the Prospect Data Platform, read here first!

Predictive, lookalike audiences are built based on your most profitable or engaged customers, deployed in ad platforms to find your next most profitable or engaged customer. But as the best marketers know, just because you found your next “whale,” doesn’t mean they will be ready to “bite,” or that is, they might not be ready to immediately purchase your product the first time they see an ad. Creating personalized experiences for prospective customers throughout their user journey is essential to moving these customers through the funnel from discovery to conversion.

Prospect Data Platforms, like the platform we are building at Angler AI, enable marketers and operators to do both: With your PDP you can build custom predictive audiences that help you find your next whale. Before and after they engage, your PDP will help you create personalized engagements on- and off-platform, accelerating your retention marketing efforts. With this tool, brands can create a more differentiated experience across their buyer's journey and build even deeper and more durable relationships with their customers. In this article we discuss the Prospect Data Platform’s three core offerings, predictive seed, predictive signal, and predictive audiences for integrated marketing & cross-platform measurement, and their use cases to a few specific business verticals.

Before we move on, remember that PDPs are designed to take on the cookieless world, where users’ click path view is no longer visible to brands and ad platforms alike. PDPs leverage machine learning and the brand’s valuable first- and zero-data data signals, coupled with relevant 3rd party data signals, to make this a reality without needing to drop in a tracking pixel.

Predictive Seeds

To build personalization that improves after each interaction, growth teams must fully understand the preferences, needs and habits of their customers and prospects. Prospect Data Platforms start with first- and zero-party data, then apply machine learning and third-party data signals, to create predictive seeds: defined seeds with more well-rounded attributes and appended with signals that help predict prospects' future value. Predictive seed creation is great for growth marketers that prefer to utilize ad platforms’ lookalike audience capabilities but want to provide a better, smarter seed. With Angler’s predictive seed tool, marketers can control smart seed creation and distribute to ad platforms directly and seamlessly. 

Predictive seeds can be defined and filtered based on signals from your specific customer. The options for utilizing descriptive filters within your Prospect Data Platform are endless by leveraging first-party attributes or with third-party. With your existing customer data integrated into the platform you can easily filter based on first product or category purchased, seasonal or bargain shoppers, such as those who only purchase your product during Black Friday sale periods or those that only shop with promo codes, or by customers defined as high predicted lifetime value (pLTV) customers, loyal purchasers. You can also define based on third-party attributes. For example, you could create a seed with the demographics of your ideal customer who are busy moms living in cities. Or you could target busy moms that shop at brands complementary to yours. These filters provide marketers more autonomy with defining the smart seeds for their campaigns without the reliance on an in-house data science infrastructure.

A unique benefit to predictive seed creation, particularly within Angler’s PDP, is that you can improve seed match rates by appending advanced matching with seed creation. Ad platforms maintain essentially what is a “graph” of all of its users which includes all the information and insights they have on each person on that platform, but these days consumers have multiple touch points beyond ad platforms: several devices, multiple accounts or email addresses. When brands share their customer information with the ad platform, that customer may exist as a user on the ad platform but if the contact information isn’t the same on-platform, they won’t match. PDP acts as an on-boarder, filling in missing information or user attributes. When you share that on-boarded information, the probability of matching on the ad platform increases. In turn helping the ad platform better advertise your product to its user. 

Alternatively, predictive seeds based platform lookalike audiences can be used for “negative targeting,” or signaling to the ad platform that you want to avoid acquiring customers that look like that seed. For e-commerce brands, that may look like defining the seed with “one and done” shoppers, or for subscription brands that could be a list of your low pLTV customers. 

Finally, predictive seed distribution to ad platforms requires a low level of effort from marketers and operators. The platform takes on the heavy lifting of creating campaigns from these smart seeds by automatically creating lookalike audiences in the ad platform based on the new seed,  and they can be refreshed behind the scenes.

Predictive Signals

When a customer makes a purchase, ad platforms receive “conversion events'' from the advertisers, either via pixel or from the server side. The ad platforms receive information about that order such as who bought it, when it was bought and how much they spent (“value”). Ad platforms then impute that information as feedback to the ad delivery, showing ads to more people who are similar to the converters. However, we know that not all new customers are equal. Some customers will become your most loyal advocates, but some will purchase once and never return. What if you could send signals to ad platforms that more accurately estimate the future value of each user soon after interactions with your brand or service?

This is where our Prospect Data Platform comes in: Using first- and zero-party data, your PDP forecasts conversion, lifetime value, retention and churn on the user-level. These predictive signals share customers’ and prospects’ future value with ad platforms in real time: events are sent directly to the ad platform through API (Conversion APIs on Meta and Google Ads) making it easy and seamless to optimize your campaigns for future value and boost your ROAS at scale. For e-commerce businesses, for example, predictive signals can improve your growth marketing efforts by broadening reach (by accessing higher CAC and higher LTV audiences), and for subscription services, improve acquisition of high-value subscribers. Furthermore, by predicting other products that these customers are likely to purchase next, marketers can personalize acquisition campaign creatives and ad copy that are acquiring these customers. By leveraging these predictive signals, marketers can realize the full potential of LTV by acquiring the right customers with relevant ads and creatives, becoming less reliant on limited in the moment information. 

Predictive Audiences for Integrated Marketing & Cross-Platform Measurement

Predictive audiences are essentially custom lookalike audiences created outside of ad platforms’ walled gardens. As we touched on in an earlier post, a major reason to explore predictive audiences is because ad platforms’ targeting abilities are less effective than they were pre-iOS 14.5: ad platforms can no longer access users' click path activities outside of platform to match them with their activities within the platform (you can dig deeper in the why and how these work in our earlier post). Predictive audiences allow you to better match users' activity on- and off-platform, but there are additional benefits when it comes to running incremental campaigns, and measuring campaign effectiveness, both of which are much harder and less effective on-platform alone.

With predictive audiences, you can amplify the effect of your marketing by building integrated marketing campaigns, reaching your high value prospects by applying custom audiences across multiple platforms such as Meta and TikTok or Meta and YouTube. And as these audiences are created outside of -ad platforms, you can then measure the incremental campaign performance (a.k.a. incremental match back analysis at the user level) across these multiple ad platforms. This is made possible by custom audiences as they are created outside of these walled gardens, which is beyond the typical measurement match-market testing tactic for integrated campaigns. With your PDP you can control audience quality, providing you with better visibility to what campaign / ad platform / creative / messaging truly caused your customer to convert and thus, true incrementality of your campaigns. This opens up the ability to execute A/B and integrated campaign tests for creative and messaging testing across multiple destination platforms.

These capabilities are beneficial to all consumer brands, whether you are e-commerce,  omni-channel or subscription based, but certain verticals can find value in additional ways.

Opportunities for Vertical-Specific Applications

Subscription Brands

With a Prospect Data Platform, you can generate custom predictive signal events that acquire high quality prospective customers who are likely to convert from free to paid subscription, maximizing profitability of your customers by finding those that will maintain their subscription. Predictive signals require minimal setup and maintenance work, and can be set up so that events refresh automatically, further lessening maintenance for growth teams.

New customer acquisition is of course important to subscription consumer brands, but successful recurring revenue businesses have a keen customer retention strategy. Just as personalized experiences are essential to moving prospective customers through the funnel from discovery to conversion, customization can help maintain your high value subscribers, prevent churn and maximize profitability. Customers who subscribe to your brand expect that their experience will continue to become more tailored to their preferences as they continue paying for their membership. When creating your predictive seed or predictive audiences with a PDP, you can ensure you are feeding the ad platform the right signals to retain the highest value customers, identify active customers that may churn and avoid unintentional “harmful” outcomes such as reminding customers to end their subscription. Angler’s Prospect Data Platform does this by predicting intent, retention and churn and appending these values to the seed you deploy to destination platforms or by creating audiences with these defined parameters. These tools empower marketers and operators to increase marketing efficiency by optimizing on LTV and the quality of customers for the long term.

Omni-Channel Retail Brands

Omni-channel brands are those that create a fully integrated shopping experience across in-store and online. Growth marketing within omni-channel retail brands can leverage in-store activities to enhance their online presence and customer engagement by encouraging customers to interact with their physical stores while driving online sales and collecting valuable customer data. This valuable in-store data can be ingested into your PDP and leveraged within predictive seed or predictive audience creation, or provided for use with predictive signal events. 

If leveraging predictive audiences, omni-channel retail brands can further improve marketing efficiency by measuring campaign cross-channel, essentially opening the door to better and clearer measurement of paid media across in-store and e-commerce activities. This is harder and less effective with typical paid marketing within platforms because in-store, offline behavior is incomplete: often more limited information is available than within the customer’s digital profile. Your PDP helps you match the in-store customer with your online purchasers helping you answer the question, “how is my campaign driving omni-channel conversion.” This of course also helps growth teams create a seamless and integrated customer experience across all channels by knowing who already engages with your brand.

E-Commerce Brands

Profitable growth for single channel, e-commerce brands means higher quality new customers, repeat purchasers and less product returns. All of the use cases discussed above also apply for e-commerce brands since brand loyalty hinges on product obsession and personalization. With both predictive seed and audience creation, you can build your seed/audience based on your most loyal customers who have purchased high value products. 

Similar to the advanced matching or omni-channel benefits, if a prospect saw an ad and registered for your newsletter but didn’t convert, your PDP can analyze the predictive value of that prospect and send that predictive signal event back to the ad platform. For example, that nudge could say, if you convert that prospect, they will be a higher LTV customer for me.

Finally, your PDP can also amplify your personalization efforts in other owned marketing channels such as on-site, email marketing, and more. PDP generates valuable insights about your customers’ needs and interests, such as which products they’re likely to be interested in. This information can be fed back to your CRM tools to identify the right people for the right nurturing, and on the creative side, which dynamic content to display.

Prospect Data Platform’s use cases are truly endless! Want to learn more about how Angler’s Prospect Data Platform can help your business specifically? Contact us today for a demo!