AI Integration
Cut through the noise & work out where AI helps your brand & where it doesn't.
There's never been more talk about AI in ecommerce, and there's never been more confusion about what to do with it. Every agency's selling an AI service. Every platform's bolting AI onto itself. And every founder's being told she's already behind.
Some of it helps and a lot of it's for show. So the work is telling the difference, and then putting the useful part somewhere it earns its keep.
What's in it for you
Done properly, AI compounds. It takes on the work humans shouldn't be doing, finds the patterns in your data nobody would go looking for, and shortens the gap between a question and an answer, which is where most of your week goes.
Done badly, it's an expensive distraction - tools nobody opens, outputs nobody trusts, a process change that put more friction in than it took out, and money spent on AI because everyone else is spending money on AI.
But everyone will happily tell you what AI can do for you. Far fewer will tell you what it can't.
How I think about AI
AI has to fix a real problem, one you can put a dollar figure on, inside a process you've already got, and that's the whole test.
Start with the problem. What's slow, what's manual, what gets done twice, and what's sitting in the data that nobody ever looks at. Answer those first, because AI is often the answer and sometimes it's a spreadsheet & a better process.
Put a number against everything. Worth $20k a year, or $80k a year, and anything without a number attached doesn't get built.
Automate the boring work & keep the judgement. AI is very good at anything with rules around it, but it isn't going to make the call on your brand, your customer or your next move. Nor should it.
Build it inside the business. AI living in a separate tool nobody opens is dead money, and AI running inside the workflow your team already uses is the AI that actually gets used.
Give each one ninety days. Treat every one of them as an experiment, and if it isn't paying for itself by day ninety, out it goes.
This moves every week and everyone is learning it at the same time, including me. Twenty years of knowing which problems in an ecommerce business are worth solving is the part that doesn't move.
What working with me looks like
Most of this starts with an AI Diagnosis, fixed scope and fixed price, mapping how the business runs now, finding where the time & the money are going, and costing each opportunity in dollars per year.
What comes back is an action plan with a number against every line. Here's the $40k a year win. Here's the $200k mistake you're about to make. Here are the three things everyone's telling you to buy that aren't worth your money.
Implementation then runs as its own engagement, embedded and built into the systems your team already uses, and measured closely enough that you kill what isn't working and keep what is.
And it goes in alongside the operations, the CRO, the forecasting and the platform work, because it's all one thing and a change here will change something over there. It doesn't need its own sign over the door.
The fundamentals underneath this go back twenty years. The dollar-costed AI case studies are newer, and I'm building them right now inside live client work.
Who it's for
Premium retail brands doing $3m to $20m who want someone independent in the room working out what's worth doing & what isn't. Founders tired of being sold AI as the answer to everything by people who can't put a value on it. Brands who'd rather build something small that keeps paying than something loud.
Who it isn't for
Brands wanting AI bolted on quickly, or wanting it mainly as marketing material. And anyone hoping AI will save a business that hasn't been designed properly yet, because it won't - it'll just get the mess to you faster.
Let's have a look at where AI helps
If you're trying to work out what to do about AI and nobody's giving you a straight answer, get in touch. The first conversation's free, and it usually runs to walking through how the business works now and pulling out two or three places worth a proper look.
Before you spend a dollar with anybody, mine included, go and ask them one question. What's this worth to my business per year, and how will we know? If they can't answer it, you've learned something useful for nothing.
Key points
- Fixed-scope, fixed-price AI Diagnosis, with every opportunity costed per year
- Implementation runs as its own separate engagement
- Built into the workflows the team already uses
- Ninety days on everything that goes in. If it's paying for itself it stays
- Twenty years of knowing what's worth solving underneath it, and honest about what's still being proven