An optimized strategy for recapturing inactive customers.

The case: Retailer aiming to target inactive customers.

Re-engaging existing customers is a lot more cost-effective than customer acquisition. Still, the re-engagement of long-term inactive customers could prove to be very expensive if not approached correctly. used advanced Customer Analytics techniques to design and implement a successful re-engagement strategy. 

The methodology: applying advanced Customer Analytics.

In order to help our client target and reactivate its inactive portfolio, we followed a three phases approach: 

  • Phase 1: Segmentation & Testing
  • Phase 2: Scoring & Strategy
  • Phase 3: Full-Scale Rollout

Phase 1: Segmentation & Testing

Identifying, segmenting, and targeting inactive customers

As a first step, we performed a Portfolio Deep Dive to properly define the inactive universe.

In-depth analysis of consumers’ past behavioral patterns enabled us to categorize the inactive universe into appropriate segments. We identified four actionable segments based on the history of transactions and interactions. 

The success of a re-activation strategy depends on targeting members with a higher probability to respond and providing appealing offers that can revamp their relationship with the brand. So, we designed and executed a set of Pilot Campaigns testing different:

  • Price offers.
  • Communication channels. 
  • Promo durations.

Phase 2: Scoring & Strategy

We evaluated the results of all the pilot campaigns and identified the offer and the communication channel with the maximum revenue and profit potential for each customer segment. 

The next step was to develop a propensity model in order to calculate the probability of a long-term inactive customer to generate revenues. As a result, we segmented the inactive portfolio into 11 segments, utilizing the characteristics of the positive and the negative responders of the pilot campaigns. 

The data we accrued from the pilot campaigns enabled us to design a Business Strategy by Segment detailing both the offer and the appropriate communication channel. 

Phase 3: Full-Scale Rollout

The long-term inactive customers’ re-engagement strategy rollout was executed in bursts based on our client’s available resources. Following the completion of each burst, we ensured that proper results tracking vs. self-reactivation and set benchmarks took place in order to record the bottom-line impact for the business.    

The Results

The data-driven omnichannel re-activation strategy we implemented achieved: 

Results: 12% growth, 4 times increase in revenue, 2 times increase in annual profit

Thanks to customer analytics, companies can now design their long-term inactive customers’ engagement strategy in a more effective way, making better use of the available resources and increasing the initiatives’ ROI. Customer Analytics: Reactivating existing customers. 

With customer acquisition becoming increasingly expensive, businesses realize the value in reactivating existing customers and even reactivating the long-term inactive ones, which often represent a significant part of their portfolio. An inactive portfolio is an ideal prospect database, and at, we leverage the power of customer analytics and enable companies to: 

  • Identify & segment the inactive universe using machine learning techniques.
  • Design & execute efficient campaigns. 
  • Establish a proper evaluation mechanism utilizing benchmark success criteria. 
  • Generate incremental revenues for the business. 
  • Maximize the customer lifetime value. 

With Customer Analytics & CRM Strategy Services, companies can optimize customer engagement and ensure that they achieve their objectives with precision and at scale.