How a CDP Can Help You Manage Your Customer Portfolio

Tech innovations give marketers more tools to work with. Beyond mere buzzwords, breakthroughs like AI and augmented reality (AR) allow marketers to be more creative, either by shouldering the burden of menial data crunching or enabling creatives to develop new kinds of experiences for consumers.

Yet, with all these advantages, marketers are still falling behind omnichannel shoppers.

From an organizational standpoint, advantages in data management make it easier for non-specialists to work with data scientists. These advances take place in the user interface (UI), or user experience (UX), of new software and cloud services for marketers.

I recently spoke with Omer Artun, CEO of AgilOne, about the development and effects of Cohort Analysis, a new addition they’ve made to their customer data platform (CDP).

Artun agreed that, these days, non-specialist marketers are working more closely with data scientists due to advances in data solutions, especially easier interfaces. And for data scientists, they can see their insights carried over to marketing teams, instead of withering in a data warehouse.

Artun told me that earlier in the history of AgilOne, their interface was a main draw. The new offering “stems from our strengths in analytics and has been in planning a long time.” Today, “our strength is analytics, and that now makes our CDP shine even more.” He added, “The activations module is now even more powerful, and the actions you take can be measured.” 

Speed and scalable data 

AgilOne is known as a leader for its use of AI in marketing tech solutions. Cohort Analysis, however, doesn’t depend primarily on AI for its data insights. Because of its self-service interface, it allows marketers to easily track the performance of a campaign or other marketing effort by segment or by a cohort of customers. (It should be noted that near-real-time data and segmentation are two key requirements within the more stringent definition of CDPs we’ve reported on.)

External IT support usually required to pipe this data to marketers is made accessible with the interface, enabling marketers to keep up with the customers they feel are most important to their business.

The core functions for this CDP extend the functionality of traditional CDPs. First, identity resolution stitches together data from different sources into a unified customer profile. This provides a springboard to gain intelligence about the customer and begin to formulate a plan of action on how to leverage insights to increase ROI.

Artun explained that marketers can try new ways of activating the data through different channels.

“It could mean segmenting customers and showing them different versions of a website,” he suggested. “Leveraging this data in front of the customer means findings ways to increase the value of the customer and to reduce marketing spend.” 

Closing the loop on KPIs 

Marketers import data into their analytics solution so that they can arrive at insights based on customer segments they’d like to see increase by key performance indicators (KPIs), such as revenue or conversion rates.

According to Artun, the Cohort Analysis capability of the AgilOne CDP “closes the loop” by showing campaign performance directed at a particular segment after a particular action is taken.

AgilOne’s enterprise customers include traditional retailers, DTCs and eCommerce sellers. The advantage they gain by being able to analyze the performance of segments allows them to reach goals specific to the consumer segments, as well as overall outcomes according to their retail strategy.

“People analyze segments of customers, but don’t take any action. They might want to conduct A/B testing, or track the segments over time,” Artun stated. “Let’s say a particular customer group always buys on clearance, then my goal is to get them to buy items full-price. Tracking this cohort over time is something retailers want to see. And the action they take with a campaign or program, they want to see the response.”

This advanced analysis creates a “conduit” between marketers and data scientists, Artun said. Immediate results from this kind of cooperation could result in changing a retailer’s content strategy.

Also, by measuring campaign performance, this could affect what channel is chosen to communicate with a specific customer segment.

“Tracking a cohort over time,” Artun added, “helps set more long-term goals. Whether your strategy is working or not can only be seen with a cohort over time. This results in more strategic management of your customer portfolio.”

Marketers aspire to gain visibility into long-term value over their business’s entire relationship with the customer. With data that enables this wider lens, marketers can begin to manage all of their customers and tweak strategies according to their different behaviors within particular cohorts, instead of focusing, for instance, on just high-frequency purchasers.

“Everybody thinks about focusing on high-value customers, and that’s not the right approach,” Artun said. “You need low-value customers, too, because they’re also buying stuff. You need to have a portfolio approach – you need to manage your portfolio.”

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