Promi

Promi addresses a familiar ecommerce trade-off: discounts lift conversion but erode margin, and most stores solve it with one blunt sitewide promotion. Promi instead personalizes discount depth shopper by shopper and product by product. Its AI model ingests signals such as visitor views, traffic source and transaction history to estimate how price-sensitive a given shopper is, then applies the smallest offer likely to close the order — factoring in the product's profit margin and conversion rate so the discount does not simply give away profit on items that would have sold anyway.

On top of the model, Promi gives merchandisers direct control over who sees what. You can build targeting logic around views, orders, traffic sources, UTM parameters and tags — for example member-only discounts or offers shown exclusively to paid ad traffic — and then choose how the discount surfaces: automatic price strikethroughs, pop-ups, or discount descriptions that appear when a visitor follows a link. Klaviyo and similar CRM integrations extend the same personalization into email. Every campaign can be measured through built-in A/B tests covering revenue, gross profit and conversion rate, with raw experiment data available for export.

The company positions itself for both small stores and nine-figure brands, and publishes case studies reporting average increases of +24% revenue per visitor, +22% gross profit, +26% conversion rate and +20% ARPU. It is a B2B platform sold primarily through demos rather than self-serve signup, which makes sense given that the AI model needs your own traffic data to become useful. The site offers a 40-second discount analysis to give prospective customers a first read on their current promotion strategy.