How a Retailer Can Automate Google Review Responses with Make, ChatGPT and Notion

Responding to Google reviews is one of those tasks every retailer knows matters, yet never quite finds the time to do properly. Between the till, inventory, and customers in the store, reviews pile up and often go unanswered for weeks. The business stakes are real: a recent 2025 study on customer reviews shows that a single one-star increase in a local business's average rating can lift revenue by 5 to 9%. And 56% of customers say they're more drawn to businesses that take the time to respond to their Google reviews.

That's exactly the problem solved for Sophie, who runs an organic cosmetics shop in central Bordeaux. Before setting up this system, she spent roughly 3 hours a week replying, as best she could, to her Google reviews, often in the evening after closing. Her response rate plateaued at 20%. Six weeks after automating the process with Make, ChatGPT, and Notion, she now responds to 95% of her reviews within 24 hours, spending about 20 minutes a week on the task.

Why automating Google review responses makes economic sense

The broader context favors retailers who act now. According to the Bpifrance Le Lab barometer published in late 2025, 55% of French micro, small, and medium businesses now use generative AI in their operations, up from just 31% a year earlier, a 24-point jump in twelve months. Globally, McKinsey's 2025 State of AI report found that 88% of organizations now use AI regularly in at least one business function, up from 78% the year before. The shift is broad, and it reaches small operations too.

This momentum is set to accelerate in customer relations. Gartner predicts that agentic AI will be able to autonomously resolve 80% of common customer service issues by 2029. For a retailer, that means waiting another two or three years to look into this means letting competitors build a lead in perceived responsiveness that becomes hard to close.

The actual workflow: Make, ChatGPT, and Notion

The system built for Sophie relies on three complementary tools, none of which require any development skills.

1. Make collects new reviews automatically. A Make scenario connects to the shop's Google Business profile and checks every hour for a new review. As soon as one appears, Make pulls its content, star rating, and the customer's first name, then passes that information to the next step.

2. ChatGPT drafts a response. Through the API, ChatGPT receives a structured prompt that specifies the brand's tone (warm, professional, never robotic), examples of past responses Sophie approved, and the review to address. Within seconds, it produces a personalized reply that might reference the product purchased or a detail the customer mentioned.

3. Notion centralizes validation. Rather than publishing the response automatically, the scenario creates a row in a shared Notion database, with the original review, ChatGPT's draft, and a "to validate" status. Sophie checks this database from her phone, tweaks it in a couple of clicks if needed, and approves it. Once approved, a second Make scenario automatically republishes the response on Google.

This human validation step isn't a minor detail, it's what keeps the retailer in control of her brand's tone, while sparing her the blank-page problem with every single review. That combination, more than the automation itself, is what makes the difference.

The numbers after six weeks

For Sophie, the change translated into concrete figures: the review response rate rose from 20% to 95%, average response time dropped from several weeks to under 24 hours, and the monthly time spent on the task fell from 12 hours to about 1 hour 20 minutes. Over a year, that adds up to nearly 130 hours recovered, roughly equivalent to three full weeks of work.

Beyond the time saved, the most visible effect was on foot traffic: the shop's average rating climbed from 4.2 to 4.6 stars over four months, with a noticeable uptick in store visits that Sophie herself attributes to the new responses, which now appear faster and more personal under every review.

How to get started in your own shop

If you want to replicate this system, here's a realistic week-long plan:

1. Day 1: connect your Google Business profile to Make and test pulling an existing review automatically.
2. Day 2-3: write 5 to 10 sample responses that match your brand's tone, to feed the ChatGPT prompt.
3. Day 4: build the Notion validation database with columns for review, proposed response, and status.
4. Day 5: connect all three tools in Make and test on a real review in "draft only" mode.
5. Day 6-7: approve your first responses, adjust the tone if needed, then turn on automatic republishing.

This is exactly the kind of diagnostic and implementation work we structure in a TransformAudit: over a 90-day roadmap, we identify repetitive tasks like this one, the ones that eat the most time for the least added value, and automate them one by one with the right tools, without unnecessary complexity.

If managing your customer reviews, follow-ups, or sales tracking is eating into time you no longer have, now's a good moment to talk it through. Get in touch to find out what in your business could be automated in the coming weeks.