5—10%
reduction in churn and protection of long-term value
SHAiPE: the LTPlabs framework
Set the Decision
Define the retention objective
reduce churn, protect margin, stabilize key segments
Set the decision level
customer, segment, product line, contract
Define the intervention timing
real-time, periodic, renewal-based
Highlight what matters
Define the retention levers available
discount offers, service upgrades, contract renegotiation, proactive outreach, experience fixes
Identify the churn predictors and signals
usage decline, service complaints, payment delays, price sensitivity, contract maturity, engagement drop
Design the retention operation
contact scripts, message variants, channels and ownership
Augment with AI
Combine behavioral, transactional, pricing, service, and contract data to estimate churn probability and timing.
- DataCustomer behaviorHistorical transactionsPricing and serviceContract termsAI ModelChurn %
Simulate the impact of different retention actions to quantify incremental uplift and ROI, accounting for campaign cost, margin erosion, and churn risk.
Prototype your solution
Pilot targeted retention strategies with treatment vs control groups, testing different levers,
Expand to scale
Productize into a retention intelligence tool integrated with CRM and service workflows
Train teams on value-based retention
Establish monitoring cycles to refine strategies, models and scripts
Nutshell
What this means for your business
Higher retention ROI by focusing incentives where impact is greatest
Clear visibility on value at risk and drivers of dissatisfaction
Faster, more consistent retention decisions embedded into daily operations
InsightsConteúdo
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