WITH INSTAP.AI RECONCILE PAYMENT, LOYALTY AND CUSTOMER KNOWLEDGE
The instap.ai platform leverages transactional data for the benefit of brands / retailers and consumers.
Retailers can access transaction data directly from bank accounts in a secure manner (DSP2 compliance). And this in a way that respects the privacy of consumers (GDPR compliance) via anonymization and declared consent.
Loyalty and re-purchase can be optimized and developed with Personalized Rewarding.
In the end, Customer Lifetime Value is boosted quickly and sustainably.
how does the solution works and what are benefits for customers and retailers?
The instap.ai solution provides a technology platform around PSD2 (ALO + PISP) that enables:
– Reward customers at their fair value.
– Access new data from the DSP2 (all bank account debits and credits).
– To better know the customers and their behaviors with the competition.
– Personalize rewards according to the consumption of the customers of the brands/retailers and also allows to differentiate from their competitors.
– Increase the average basket, the repeat rate & lower the churn rate.
– Reduce and optimize marketing messages to customers.
– To propose a new payment method without credit card and irrevocable.
A business cases
The challenge was to increase the shopping cart during a slow month and to win back customers who had left for the competition.
The result after using the instap.ai solution is a 58% increase in the average shopping cart and a reactivation of churned users: 14% in 24 days.
Instap.ai is a young start-up whose ambition is to give back the power to retailers and consumers.
Its ambition is to give back the power to retailers and consumers on three main axes:
– Loyalty and commitment: with discounts or rebates based solely on the purchase, to reward customers.
– Payment: with the arrival of the PISP, a revolution enabled by the PSD2 directive, there is no need for a bank card.
– Data: with access to ALL customer consumption habits: where and when they buy, but especially from whom.