Reply to Google Reviews automatically with AI and boost your local SEO. Start for free.
Handle Google reviews with AI and boost your local SEO.
Reply to Google Reviews automatically with AI and boost your local SEO. Start for free.
Such a much-needed tool, especially for agencies managing multiple local clients. Good job 😍
Hey PH! @vincent_imhoff1 and I are launching FullReviews: an affordable, easy solution to reply to your Google customer reviews. ⏳ Save time replying to reviews and focus on your business ❤️ Increase trust and make your customers feel cared for 📈 Get more visibility from Google and Google Maps in exchange But it's not just that: you also get manual replies, stats, and a module to request new reviews through email and SMS. In short, there is no other tool in the market which is as cheap and deliv
Congrats on the launch, Vincent and team! 🎉 FullReviews sounds super practical — honestly, replying thoughtfully to Google reviews is so important but so easy to neglect when you’re busy running a business. Love that you’re making it affordable and lightweight, especially for SMBs that don’t have big marketing teams. The built-in review request module is a smart bonus too — feels like it could quietly drive real growth over time. Wishing you lots of success! 🚀 Curious: any plans to expand it to
Love how simple it makes everything. No more stress replying to reviews.
This AI tool for automatically replying to Google reviews is incredibly useful! It saves a ton of time and helps boost local SEO effectively. The free starter option makes it easy to try out, and its powerful yet simple features are highly recommended for businesses managing a large number of customer reviews!
A measure of community engagement at launch. Higher means more people noticed and interacted with the product. It's a traction signal, not a quality rating.
Discussion threads divided by interest score. Above 0.30 is strong. Below 0.15 suggests the product got clicks but not conversation.
Categories come from the product's launch tags. Most products appear in 2-3 categories. The primary category is listed first.
The scores reflect launch-period engagement. Historical data is preserved and doesn't change retroactively. The build date at the bottom shows when the index was last refreshed.