The Noodles Dilemma That Sparked an AI Product Idea for Google Reviews & Businesses

Today, I was in the mood for some Chinese food after work and was looking at a couple of nearby restaurants to try out. But when hunger strikes, you need to make decisions fast – ideally, have food in front of you within minutes. Still, I wanted to try authentic Sichuan cuisine and experience bold flavors and spiciness in every bite.

Normally, I start by searching for restaurants, checking their menus, and reading reviews. If someone hasn’t personally recommended a restaurant to me, I do my own “due diligence” before picking one. If I’m grabbing a quick meal alone, I definitely want to try their best dishes. If I’m out with friends, we usually order different items to share so we can try everything.

But alas, I wanted to check out a couple of dishes for myself and found myself combing through countless reviews. After what felt like “one billion years,” I finally decided on a restaurant and what I would try there. I headed out to enjoy my cheat day. The staff was amazing, the vibe enjoyable, and the environment welcoming, with lots of families enjoying an early dinner.

While waiting for my food, I started wondering - why do users have to spend so much time answering such basic questions?

• Is the food authentic Sichuan cuisine?
• Do they have vegetarian options?
• What entrées are must-tries?
• Do they have boba?
• Is the food spicy or bland?
• How difficult is it to get a table in the evening?

While I eventually pieced together answers from different reviews, I realized I had wasted a lot of time - and my hunger prompted me to imagine something better.

Why Not Use Gemini to Make Reviews Smarter?

So while waiting and watching happy families enjoy their meals, I started thinking about an update to Google Places reviews to enhance user experience using Gemini.

In my months of using the Gemini API and being consistently impressed by its context length and capabilities, I’m confident that something like this is absolutely possible.

Alongside the standard list of reviews, users could query a chatbot that uses the past few months of reviews as context.

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For example, Want to know if the portion sizes are decent? Several reviewers mention that prices are high compared to the portion size - but the taste is excellent.

This feature would effectively introduce a Gen-AI layer between the reviews database and users, benefiting restaurants by:

• Reducing redundant queries
• Improving customer decision time
• Using AI to amplify business appeal

But What About the Risks?

Of course, like every update, this comes with risks. Some businesses may not appreciate how they’re represented. For instance, if a business has mostly negative reviews, the AI summary may reflect that heavily, which could feel biased to the business owner. While this may be fair to users, it could raise regulatory concerns and even lead to legal challenges.

This risk could be mitigated with a two-step approach:

1. Allow businesses to opt out of the review-chatbot feature.
2. Cite every AI-generated answer with the top relevant reviews used to formulate the response.

Another concern is spam reviews. It’s not uncommon for businesses to face unethical review manipulation - either overly positive or unfairly critical. This could skew the AI’s responses.

Fortunately, Google’s automated spam detection and review moderation system already helps address this, and businesses can report suspicious reviews. Nonetheless, the review monitoring system would need to be especially robust to support this user-facing feature.

I explored some options to develop this as an external tool, but Google Places APIs are very restrictive. If anyone has experience using them, let's connect.

💡 AI assistants like ChatGPT, Claude, and others are changing user behavior.
These standalone apps now effectively answer local discovery questions, something traditionally dominated by apps like Google Maps. But here’s the catch: as users migrate to these AI tools, their engagement with platforms like Google Maps is likely to decline.

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📊 Current Market Share in Local Reviews:

• Google Reviews: ~73%
• Yelp: 6%

To stay relevant and maintain market leadership in local reviews, Google must consider integrating similar AI-powered capabilities directly into its Maps experience.

The shift is already happening. The question is: who will adapt fast enough — users or the platform?

The Takeaway

Considering the benefits and risks, I strongly believe Google Places should explore incorporating this feature into Maps and Reviews, at least through A/B testing.

Users would love it.
I know I would.

Thanks for reading! I hope this idea is something which would be welcomed by users. If you have any thoughts, or any experience with using Google Places API, or just want to continue the conversation, feel free to reach out to me.

Always happy to hear from you!