Ricochet

@nebulalab @djmckee Thanks Dylan, appreciate your support through the many iterations of Ricochet along the way!

Hi @jd - our roadmap for the next couple of months will first see us double-down on the data; so you'll see us experiment with some new data sources, such as the markets a business operates in, who their competitors are etc. We'll then try and drill down into the fundamentals - we want to make sure sales teams have as much of the right information as possible for researching and qualifying. After that, we're hoping to get into the really interesting stuff - how you can use this data to start automating research and qualification; opening Ricochet on any website and knowing immediately if the business fits your customer profile. Once we better understand the (anonymised) behaviour of users, we can then start utilising some of the deep learning models we've developed to automate lead generation and qualification.

@iamashley Thanks Ashley!

Hey @eamonncarey - great question! I'm going to write up what went on during beta-testing another time, because parts of it ran like clockwork, while other aspects radically changed the product. The biggest change we made was to pull out all the functionality around personal email addresses. The beta version presented a lot of information like emails, but not neccessarily the context, like names or job titles - it's hard to identify non-formatted information at scale without a lot of cleaning up. But without that context, users told us we were missing data from whatever we displayed - so lists of email addresses became "noisy" rather than useful. To do people data really well - to the point that there are so few gaps that customers don't doubt the credibility of your product - that's a product in itself, or you have to make the decision that you're going to spend your days scraping LinkedIn. More to the point, there's no need for another extension or database that does that - there are plenty already. So what we took away from the feedback was that unless we executed brilliantly on people information, users would never feel we were doing the job well enough, and always feel Ricochet was broken or missing "obvious" information, so we stopped doing people data altogether. In terms of trusting our gut, there were a few users adamant we needed functionality around use cases we'd never seen before. I understand how founders get nervous, and start thinking of user feedback as a to-do list of features they must build to keep everyone happy, but we've talked to enough sales teams in the past few months to recognise what edge cases look like, so where stuff didn't fit behaviour we'd seen before, we put it to one side and tried to focus on solving the problems we had plenty of evidence for.

Hi @petejsc - for the next few weeks, we'll be doubling down on improving the quality of data, so making sure we're not getting tripped up by JS sites, starting to think about non-UK company registers etc. We'll also be introducing some more data sources around markets and competitors, and there's some exploration to do around hiring and location. After that, we'll start poking at some of our plans around automation. Lots to do, but we're keen to get more signal on some of this from early users before we move on.

@paul_a_smith sounds great, excited to see this evolve 🙌🏻

@petejsc thanks Pete, so are we!

Hi @daz_lester - we've found during beta-testing that the tool is useful in all commercial settings: - SDRs doing outbound and needing to qualify new leads - Marketing managers doing inbound and needing to sensecheck leads before passing them onto BD - BDRs, AEs and Customer Success managers wanting a quick brush-up on what a business does before contacting them However, we're intending to focus our data efforts and the automation tools on sales development, which in turn helps us start to automate discovery and qualificaiton.

@paul_a_smith Thanks