Retain to Reign
Time to Next Purchase
In a world where businesses are vying for customer attention, timing is everything. Getting it right, along with offering the right product (which we'll cover in the next chapter), is key! By accurately predicting when a customer is likely to make their next purchase, companies can optimize their marketing strategies, avoid wasting resources on unnecessary communication, and target customers with relevant messages at just the right moment.
And the impact is sizable! Implementing a communication strategy based on TTNP prediction improved the ROI for a leading ecommerce player by ~2x.
Determining the Optimal Time Window
But how do we determine this optimal time window? At a customer level, this is a function of:
â–ª Past Customer Behavior: Is the customer an occasional buyer or a frequent shopper?
â–ª Demographics: Gender, income level, job type and age group all play a role. For example, salaried individuals tend to buy at the beginning of the month.
â–ª Last Purchase Details: Items bought last time affect the timing of the next purchase. For instance, personal care product buyers may return sooner for replenishment.
â–ª Behavioral Signals: Interactions like website visits, email opens, and wishlisting indicate interest and intent, helping predict future purchases.
â–ª Lifecycle Stage: Time between orders decreases as customers engage more with the brand, reflecting their evolving relationship.
Technically, we've got plenty of options for building robust TTNP models, from survival models like Kaplan-Meier Estimation to more complex ensemble learning approaches.
Putting TTNP into Action
So, once we've got the prediction, how do we put it into action? Here are some examples of what retailers are doing:
â–ª Personalized Communications: Focus on content for customers not yet due to make a purchase, and offer discounts and reminders to those nearing their next buying window.
â–ª Progressive Discounts: Offer increasing discounts or rewards as customers approach their next purchase time.
â–ª Reactivation Campaigns: Personalize the “Churn” definition and retarget customers who have lapsed in their purchase activity based on the TTNP model predictions.
â–ª Tiered Loyalty Programs: Reward customers based on their time to next purchase, encouraging them to move up the loyalty ladder.
Furthermore, pairing this strategy with predictions for the next best product or category can enhance its effectiveness even further.
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