Richard Heritage’s Post

Transcript

Hi everyone. Rich from Infer here wanted to update you on some of the things that have been going on at Inferior over the past couple of weeks. Really, it's been very exciting times. So one of the the big things is we have just launched a partnership with Revolt Co-op here came out yesterday. So Revolts Coop, if you aren't a member, they are, in my opinion, the number one red OPS community out there. Membership is free and they have a brilliant Slack channel where you've got people that are doing DevOps day-to-day, asking each other questions, throwing out ideas. There's suggestions on solutions, tools, ways of going about things, all that sort of stuff. Really hands on with recommend signing up if you're not a member and you are in that space. And what we're hoping to bring to this partnership is, yeah, our sort of expertise within data science and how we're applying that to the revenue world. And for me it just starting to really cement us our place in the revenue space. We're building out the use cases that we're working with customers on. You know, it's great to see the traction that we are getting and it's clear that the product is solving some really key important problems in that space. So very exciting stuff. We've then released the newest update, newest episode sorry of the All Things Being SQL podcast, this ones with Andreas Dracos, Senior Director of Redbox Superside. Andreas has built the team from the ground up there and he, you know, he's what I really liked was how he really advocates for upskilling yourself, take responsibility and fighting internally for that seat at the go to market table. And you can see it's obviously worked out for him. He's now built a multi function revenue reports team that supports 100 people across sales, marketing and customer success. So great episode full of advice from a real leader. So I recommend giving it a listen. They wanted to show you very quickly some really exciting stuff going on in the product. So this for those that know the product, this won't be particularly new. So what we're looking at here is an analysis on lead scoring. So we've put data set from our HubSpot CRM, we've drawn it from HubSpot, we've given it to coworker said based on this data we can do lead scoring plus a lot of other use cases. I've chosen lead scoring here. You can see right for our leads, uh, these are the different industries that are particularly good at providing good quality leads. These are the types of revenue. This is the location. Number of employees, all that sort of stuff, that's great. That's what we had already so. What's new is then when we go to pipelines, pipelines is when we then take those insights and automate them back into your CRM data source wherever it is. And what we're doing now is providing suggested pipelines. So we've brought in this big data set and yes, we can do lead scoring, but we can also set up a revenue forecast. We can set up predictions on deal sites and that will be deal specific predictions. So we'll be able to say that each of these deals in your pipeline, we think they'll close. At this particular size or value really probability to close close date. And what's really cool is this is taking all data into account. So the probability to close and all that sort of stuff, we'll look at things like. Emails and notes and summaries of call recordings and not just look at the frequency of stuff that's going on, but actually run sentiment analysis on the text that is within the emails and notes and summaries. So we're then taking all of that into account when we're assigning deal specific probabilities and size and time to close. It's so cool. And you can just run all these now at a click of a button. So it's super, super quick. And then the next thing, because the product is continuously evolving, it's. Insane how fast it's growing is now suggested metrics. We've got some top metrics here, but. What we can now see is it's built out KPIs in the platform for us just by looking at the data. So it said this is revenue data. And based on that we can set up a KPI on conversion rate, win rate, days to close, close one amount. And then for each of these metrics, what you'll be able to do is not only monitor how they're performing, but for each of them you go in and we'll be able to see all of the factors that are contributing to. Change in performance and how much each of those are affecting that change. And that's now something that you're able to get in like 5 minutes. It's insane. So really, really exciting. And that whole sort of start to finish is all provided through suggested analysis now. So we're really opening up machine learning to a much wider audience, providing suggested analysis, suggested pipelines and automations back into your CRM and suggested KPIs. Yeah, I'm out of breath after that. That yeah, loads of really exciting stuff going on at the moment and across. Commercial departments across the product, across loads across, across it all. And so wanted to share that with you all. And as always, I hope you find it useful and yeah, hopefully speak to some of you soon. Bye, bye.