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How to keep fueling eCommerce marketing growth with a customer data platform

Updated: Jan 20, 2022

Three marketing use cases that utilize a customer data platform to fuel growth

The customer data platform (CDP) is a newer technology that has the potential to transform marketing. CDPs have gained adoption as a tool for marketers, but the ability to get value has still proven difficult. Implementations have still been complex, and often organizations can't garner the right resources. When deciding whether or not a CDP is right for your company, it's important to do some groundwork and understand what sets them apart from other technology solutions in the business and which use cases make sense with a CDP. That's what we will accomplish here.

At first glance, a CDP might seem similar to other eCommerce marketing tools that also deal with customer data and manage complex profiles. Customer relationship management software (CRMs) has many of the same functions as DMPs. Still, there are some key differences you should know about if your company needs one or both services for its business needs.

The three different types of marketing platforms are CRMs for sales teams, DMPs that advertisers or brands can use to build their advertising audiences, and CDPs, which are primarily intended as a tool in the hands of businesses looking for more information about customer behaviors.

There are more differences between the three platforms than function. What can be a bit confusing is that they have in common the ability to manage identities and provide personalization for all channels. CDPs only do this on an omnichannel level while the others focus more specifically on one channel.

For more clarity, the table below summarizes how each tool's functionality compares:

Three electrifying eCommerce Marketing Use Cases

1. Build a product recommendation engine

CDPs are specifically designed to connect and unify created a single source of customer intelligence. For recommendation engines to work well, it needs to aggregate massive amounts of data. Recommendations get better with better data than any information solution, and a CDP can provide that data in spades. For example, customer data on past purchases, the timing of past purchases, communication preferences, and loyalty status can help you hone in on what the customer may need next.

Some CDP vendors even offer product recommendations as part of their platform others may use other tools to get personalization done. Shoppers that click on a personalized recommendation are over four times more likely to complete a buy from your brand, so lots of stores send product recommendations via SMS or email, especially if they are using Shopify. No upsell or cross sell strategy would work as well as one powered with a CDP.

2. Utilize Customer Segmentation and Personas

First of all, not only do CDPs collect but data, they offer powerful segmentation capabilities. These capabilities make it easy to find out who your highest value customer segments are. Then personalize your customer experiences on their preferences - note, not all CDPs have this capability, though, so make sure you check if cross-channel campaigns are one of your priorities.

Marketers are always looking for ways to make their products more appealing and personalized, but the process of tailoring everything can be time-consuming. They do this by dividing customers into different groups based on what kind of targeting seems most effective. Target an individual's preferences or needs with ads—and even though it might seem like there would only ever exist one perfect customer segmentation strategy, there isn't. Allow data to play a huge role in how marketers choose which types go into each classification because sometimes just knowing who has already bought from you helps give clues. In an AI-driven CDP, such as VIEWN, clustering can help you identify factors to create powerful customer personas. Especially when selecting target customers for retention, segmentation insights can come especially handy. Look-alike models can also be developed from your most valued customers as well.

3. Predictive engagement scoring

One of the most important concepts in marketing is lead scores. Lead scores are used to determine where a prospect stands on their buying journey, and then you can send them targeted messages or even qualify them to your sales team. Marketers have started trying out new ways to score customer behaviors and engagement in predictive scoring.

Engagement scores are used to understand better what is going on in a marketing funnel that seems to have many entryways, different speeding lanes, and a bunch of swirls before exiting. It weighs and measures the customer's perspective to gauge whether your customer has a good experience or whether the customer will repurchase. Engagement scores can be applied to predictive algorithms and a weighted average of different interactions tied to campaign types. This approach is predicts marketing qualified leads and even factors that impact customer retention. In other words, a CDP can be used to predict whether or a customer will repurchase from you.

Since digital commerce is showing no signs of slowing down, marketers need every advantage they can get to retain their customers. eCommerce stores that have their customer data connected and unified can remain advertisers or brands can compete by constantly rolling out improvements, campaigns, and promotions. Indeed customer data becomes a business's most valuable asset once it is all connected to a CDP.

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