Retail Digital Marketing, AI & MarTech Consulting
I help retailers join up their online and in-store data, make loyalty actually pay, and hold margin as ad costs climb. The common problem is customer data spread across point-of-sale, e-commerce, email, and ads, so no one can see the full picture or what a customer is really worth.
The challenges retail faces
Disconnected channels
Online and in-store run on separate systems, so the same customer looks like two different people.
Loyalty that does not pay
Programs collect data and points but rarely change what customers buy or how often.
Margin pressure
Rising ad costs eat into thin margins, so spend has to be sharper, not bigger.
No single customer view
The systems do not talk to each other, so lifetime value is a guess.
The approach for retail
Join the data first so you can see a customer across every channel, then put loyalty and AI to work on the segments that drive repeat spend, rather than chasing reach.
Questions
Straight answers. If yours is not here, ask it directly.
We have online and in-store data. Why can we not see the full customer?
Because the systems were never joined. The fix is connecting point-of-sale, e-commerce, and marketing data so one customer is one record, with a real lifetime value attached.
Is our loyalty program worth keeping?
If it only collects points, probably not in its current form. The aim is to use what it knows to change buying behaviour, not just reward it.
Where does AI fit in retail?
In segmentation, demand forecasting, and the repetitive campaign work that eats your team's time, not as a gimmick on the storefront.
Advisory only, or hands-on?
Both. It can be a data and margin diagnostic on its own, or the hands-on MarTech and automation work that follows.