Show each shopper the right thing, and let AI manage the volume humans can't.
A generic store shows everyone the same thing, which means you leave revenue on the table with every visit. The shopper who would have bought more never sees the product that would have done it, and your campaigns speak to an average customer who does not exist.
On the paid side, manual tuning cannot keep pace with the number of combinations that matter. There is simply more volume, in audiences, creatives and bids, than a human can optimise by hand.
Recommendation and personalization configured on your existing stack, plus AI-assisted paid-media and campaign optimisation. Everything framed in commercial terms, conversion and average order value, not technology for its own sake.
E-commerce brands with enough traffic and SKUs for personalization to actually pay back. If you have the volume, the levers here are some of the most direct revenue moves in the whole catalogue of AI work.
This configures proven personalization and ad tools. It is not a from-scratch recommender engine or a bespoke bidding platform. The value is in setting up and tuning the right tools well, not in building infrastructure you do not need.
We start where personalization pays back fastest, prove the uplift on a segment, then expand across the store and campaigns.
We find the highest-leverage personalization surface for your store, the place where showing the right thing moves revenue most.
We set up recommendations and personalization, and wire in campaign optimisation, on the tools your stack already supports.
We measure conversion and AOV uplift on a segment, confirm the lift is real, then widen across the store and campaigns.
Attributed results from published studies and other companies, what the approach is built for, not MetaGem's own results. Replace with owned results after first builds
One retailer reported a 9.4% revenue increase after adding AI personalization, the kind of direct lever a scoped build is designed to target.
McKinsey puts marketing-AI revenue uplift at roughly 3–15% and sales-ROI uplift at 10–20%, the range serious personalization and campaign work plays in.
Product recommendations have been cited as driving up to around 31% of e-commerce revenue, which is why the recommendation surface is usually the first place to look.
Yes, and that is the honest gate. Personalization pays back when you have enough traffic and SKUs for it to matter. If you do not yet, I will tell you and point you at a lever that fits your stage better.
It is configured on your existing stack using proven personalization and ad tools, rather than a from-scratch build. Most mainstream e-commerce platforms are well supported.
In commercial terms: conversion and average order value uplift, measured on a real segment before we widen. The number we are moving is agreed before we start.
No. It configures and tunes proven tools. A bespoke recommender or bidding platform is out of lane, and where a job genuinely needs that, I will refer it out.
Book a free 30-minute call. We will look at your store and find the personalization surface that would move revenue first.
Book a Potential CallFramed in conversion & AOV · measured on a segment · no lock-in