Hi Climbers, we are planning a new feature around employee tracking, and before building it we want to collect your feedback in detail, because we think this could become one of the most powerful ways to help local businesses generate more reviews in a natural and consistent way. The idea is this. The business owner will have a dedicated section called Employees Links, where they can add the employees who are responsible for asking customers to leave reviews. Adding an employee will be very simple: the business just inserts a photo, a name, and an alias, which can also simply be the employee’s real name or nickname. Every time an employee is added, the platform will automatically generate a dedicated review link for that employee. It will also be possible to download the related QR code. Technically, this employee link will simply be the general review link with an extra URL parameter, something like employee=alias. In this way, we will be able to track the unique visits to each employee’s review link. So if an employee asks a customer to scan their own QR code or open their own review link, the business will be able to measure how many unique visits that employee has generated. On top of this, we want to build a leaderboard, inspired by the Skool style, where the business can see the ranking of employees based on the number of unique visits to each employee’s review link. The leaderboard will be viewable for the last 7 days, the last 30 days, or all-time. This would already create an interesting use case for businesses. For example, the company could decide that, on the last day of every month, the employee with the highest number of unique visits receives a bonus in payroll, because that employee made a stronger effort to ask customers for reviews. But we want to take this feature much further. Our idea is that if, inside the text of the review, the customer mentions the alias of the employee, then that review will be automatically assigned to that employee. For example, if the review says “Luke was very kind with us”, the review will automatically be associated with the employee whose alias is “Luke”.

I was just testing out the feature, looks great but few things I notice and my 2 cents on that : 1. When we put the star rating and the AI generates the review I see that there is a 10 sec timer with a Go Now button to go to the review site. Great. But when the 10 sec is over and if the button is not clicked it goes to the thank you page by default. We are not sure if they clicked on go now or not? I think it should just open the review link when the 10 sec is over or if they click on go now. 2. Thank you page should only be visible if they click on the go now button or any review site based on the setup. 3. We need to have statistics on this clicks so that we can track how this is performing. The feature looks good but it takes like 10+ clicks before they even post the review. I know it will help generate good quality review but the conversions will be low I think. and I'm happy to be wrong but I'd like data to prove it. Thanks,

Hey @Giacomo Chinellato Can we possibly get a Last updated date on the Ranking & Competitor tab and Sentiment Analysis tab? Thanks,

Hey @Giacomo Chinellato Is there a possibility that you can remove the /#/ from the review link URL? This may be a very niche use case and may be only for me I guess. I have a system built on GHL that leverages GHL URL redirects and self activates NFC Cards. Previously I was using GHL funnel for the Review link. But moving forward I'm planning to use Climbo's review link. The challenge is that GHL's redirect doesnt accept the # in the URL. so I am not able to automate and activate the NFC cards automatically. So, curious is it possible to remove the /#/ from the review links. I've also reached out to GHL team to add the feature so that it starts accepting the # in the URL. The reason I am wondering if you can do it is so that my system doesnt break and may be I can win some agencies to join Climbo. I have more than 150 GHL Agencies using our NFC Card System. Thanks for consideration. Cheers.

Hi Climbers 👋 This week we’re focusing heavily on one main thing: making review collection simpler. One of the biggest additions will be AI Review Suggestions. The goal is simple: remove the “I don’t know what to write” friction customers often feel before leaving a review. The system will generate a ready-to-copy review based on simple rating inputs. The end customer fills a set of custom evaluation criteria and rates them from 1 to 5, with an optional note for extra context. The AI uses these ratings and notes to craft a natural-sounding review text. The business can also define specific keywords they want the AI to include in the generated review. This helps strengthen local SEO while keeping the review authentic and readable. The generated review is then simply copied by the customer and pasted wherever they prefer — Google, Facebook, Trustpilot, etc. — keeping the process flexible and platform-agnostic while removing friction for the customer. We’re also restructuring an area that many users found confusing: the difference between Reviews and Requests. From now on, Reviews will only be the place where clients read and reply to reviews. Every action related to sending review requests will live inside Requests. Whether it’s a campaign to a list or a quick request to a single contact, the flow becomes identical: choose a template and send. No editing text mid-process, no multiple entry points — just one clear place to ask for reviews. Auto-campaigns are getting simplified as well. The current “time + frequency” logic is not intuitive for many business owners. The new model is event-based: you enable the auto campaign, choose a delay (for example 10 minutes), select the template, and every new contact automatically receives the request after that delay. Easy to understand, easy to explain to clients. To make timing even smarter, we’re introducing a Service Date field on contacts. You’ll be able to base automations either on when the contact was added or when the service actually happened — meaning you can send requests like “2 days after the appointment”, which is much more natural and improves response rates.