decrease in the churn of high-value customers
Increase in LTV for high LTV customers
Projected savings from this campaign for the full year
When Steve Simitzis, CTO, WildEarth, needed to center efforts around identifying and retaining long-term, high-value customers, he didn’t think twice about using LTV as the metric to lead the charge.
With customers churning monthly, WildEarth faced higher acquisition costs and profit forecasts were varying month to month making it a challenge to effectively scale business. By identifying and motivating customers with a high potential lifetime value (LTV) to stay, retention efforts show greater outcomes due to the most profitable customers being retained.
Wild Earth did a lot of proactive subscriber outreach to try and reduce churn while also building rapport with their new customers.
In all of these efforts, Wild Earth did not know who its high-value customers were, and then was unable to target those customers individually. As a result, the marketing team sent out identical promotions to high-value and low-value customers, which can sometimes push high-value customers to unsubscribe and also wastes precious internal resources.
Their prior efforts had them targeting 20% of their customer population with churn prevention, 10% of these were retained that otherwise would have been lost, an overall count of 11,000 customers. But only 23% of these were high LTV customers, which ultimately meant $1.4M of revenue left on the table for the year.
In an initial bid to increase retention, Wild Earth invested in a churn tool, but it predicted churn at the purchase level, not the individual level. Wild Earth knew they needed to refine their targeting to customers with the highest LTV, so they segmented their customers based on the purchase value and frequency, but that simply wasn’t enough data to accurately predict who was at a greater risk of churning so they could prioritize efforts.
Wild Earth wanted to send out handwritten letters to customers in an attempt to reduce churn, but needed to have a very specific audience identified to make the efforts worth it. To do so, they wanted to identify customers with the right personality for such a personal touch and cater to the customers who were worth more. In the current setting, they simply did not have the data to know who or when to target with their custom approach.
Wild Earth set a goal to understand which customer segments were most profitable, identify VIP customers independent of purchase history, and accurately identify profitable customers at risk for churn that can be retained with intervention, but they needed a solution to support these efforts. Enter Ocurate.
We know that not all customers can be retained and some of these reasons are out of Wild Earth’s control. For instance, some customers will churn because their pet doesn’t like the taste of Wild Earth’s food. However, there are customers who, with learned efforts, can be retained and kept for the long term.
Ocurate identified Wild Earth customers, ideal for intervention, based on predicted LTV and additional behaviors Ocurate maps in its database of 290+ million Americans. This allowed Wild Earth to maximize profitability without wasting resources on customers who would churn no matter what, or on customers who would stay with Wild Earth regardless of a promotion being available.
In their first retention campaign, Wild Earth ran an A/B test to understand what form of outreach would encourage customers to purchase a second time or maintain their current subscription status. Ocurate identified an audience of high LTV/ at risk of churn customers and a test was run against the regular outreach sent.
Group A received a special promotion – in this case, a free sample of dog treats and a tote bag with their next purchase– while Group B was treated normally and went through the cadence already in existence. When compared, the customers in Group A who received the promotion saw their churn reduced by 16%, and the individual LTV in the group was increased by $32. The losses in revenue incurred by the treatment group decreased by 28% due to prevented churn. This amount does not account for the additional savings in promotions not sent to customers who exhibited no churn risk. Projected for the full year, Wild Earth could see savings of at least $221,705.60 from this campaign.
Ocurate leveraged its deep learning framework and unique data on 290+ million adult Americans and applied it to Wild Earth’s customer base to create a profile of Wild Earth’s highest value customers. The profile includes insights tied to foundational personality traits (such as neurotic or compassionate), behaviors (such as geographic distribution), and attitudes (such as political preferences).
By matching Wild Earth’s customer data with the Ocurate database, Ocurate can create nuanced, well-rounded profiles of a brand’s ideal, profitable customers. This is a unique differentiator Ocurate provides to brands who are looking to better understand who their ideal customers aren’t.
Taking action on the correct segment of high LTV customers is incredibly important because individuals react differently to the same promotion depending on insights that most brands simply don’t have from their customer data alone. Ocurate generates such detailed insights and identifies more than who’s at risk of churn; they work with brands to identify specific actions to take with each customer segment.
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