Marketing LTV: why your best future customers aren't in your VIP segment today

Your best future customers aren't necessarily your top spenders today. Allocating exclusive perks based on historical revenue means you're rewarding the past and overlooking high-potential profiles that your competitors may already be nurturing.

It's one of the most common use cases for predictive AI in CRM, part of a series breaking down, one by one, the concrete uses of Batch AI Predict. To understand why a predictive score only creates value once it's activated, start with our framing article.

Why does rewarding the past make you miss your best future customers?

This logic rewards the past. It favors customers whose value may already be behind them, and ignores recent customers with strong future potential.

This connects to your best customers quietly disengaging without you knowing, from a complementary angle: past value versus future value.

How does Batch prioritize customers on future value?

With Batch AI Predict, you allocate the perk on projected value, not past cumulative spend. For each customer, the score predicts their future value over a defined horizon.

What is the Future LTV score and how does it work?

Future LTV predicts the amount each customer will spend with the brand over the coming year. The model learns to recognize trajectories that lead to high future value, including among recent customers with still-low cumulative spend.

What results do we see on this type of use case?

The future-value selection outperforms the past-spend selection:

• +8% in purchase frequency

• +10% in basket over the 6 months following the event

In short

Batch AI Predict's Future LTV score predicts each customer's future value and lets you prioritize on that projection. A better-invested perk budget generates more revenue at equal cost.