Ebsta with Adam Roberts

Outline Summary: Ebsta Platform Deep Dive

Intro This transcript presents a detailed walkthrough of Ebsta platform, featuring Adam Roberts, the commercial leader, and Anthony Lean Scale. The conversation centers on how EPA aggregates data from multiple sources within Salesforce to deliver unified, actionable visibility into pipeline health, forecasting, and revenue performance. The discussion underscores a core mission: uplift the 85% of B-C sellers by translating top performers’ tactics into scalable guidance, enabling data-driven decisions across reps, managers, and executives.

Center

• Foundational data and single source truth:

  • Ebsta pulls from mail servers, calendars, CRMs, and historical closed opportunities to populate a comprehensive, enriched opportunity record.

  • The goal is to capture emails, meetings, and relationships that often remain missing in CRM, achieving near-complete data within a week of engagement.

  • A “Relationship Score” and its trendline are presented at a glance, signaling account health and closing likelihood.

• Opportunity-level insights:

  • The platform visualizes communication threads, key contacts, and relationship strength across accounts.

  • Qualification and call intelligence: Ebsta supports MEDDIC, BANT, CHAMP, and custom schemes; conversations are transcribed and analyzed to auto-suggest qualification scores and notes, reducing manual entry bias.

  • Integrations handle Gong, Zoom, Teams, and more, bringing transcripts into Salesforce with a single source of truth.

  • Key moments from calls are surfaced on the opportunity record, with playback for quick review.

• Risk visibility and actionability:

  • Opportunity dashboards surface time-in-stage, win benchmarks, and slippage risks.

  • Managers see why deals may stall (low engagement, poor qualification, weak multi-threading) and can prescribe next steps.

  • The system encourages reps to self-serve fixes, such as booking meetings or engaging additional stakeholders.

• Pipeline management at scale:

  • Ebsta pipeline insight visualizes all opportunities, allowing slicing by quarter, hierarchy, product, and revenue type.

  • “Smart Insights” flag deals with warnings or stall signs, guiding managers to intervene where it matters most.

  • A deal-score (0–100) tracks progress through stages, influenced by positive/negative signals and historical benchmarks.

• Forecasting and governance:

  • Bottom-up forecasting is championed to maximize attainable quota attainment and forecast accuracy.

  • Reps submit weekly forecast updates; managers can hedge or adjust commitments as needed.

  • The forecasting tab enables rollups by team, with visibility into required coverage and pipeline sufficiency.

• Analytics and funnel health:

  • Funnel analytics provide velocity, win rate, cycle length, and AOV, with drill-downs to individual reps.

  • Time-in-stage analytics identify bottlenecks (e.g., value proposition stage) and suggest remediation with coaching or messaging refinements.

  • The forecast-change view reveals shifts, new opportunities, and reasons for slippage.

• AI and data strategy:

  • The experts emphasize an AI-first world contingent on solid data foundations.

  • Ontology and clean, structured data are prioritized to maximize AI tool effectiveness across models and platforms.

Outro Adam and Anthony emphasize that EPA’s strength lies in unifying data into a single, actionable Salesforce experience, empowering reps to close more deals and managers to drive performance decisively. The platform’s ability to pull in historical data, provide relationship and qualification insights, surface risk factors, and support bottom-up forecasting is presented as a comprehensive solution for revenue operations at high-growth companies. The conversation closes with an invitation to connect on LinkedIn for follow-ups and potential future discussions.

Full Transcript

[Music] I'm really really pumped to go into the EPA platform today. EPA is my favorite revenue intelligence platform. We've been working with them for a few years and we have Adam Roberts here today to go through it. A few weeks ago, we had their founder CEO guy on talking about the state of B2B sales and all of the opportunities for improvement. And a lot of that data is coming from the platform itself. And today we have an opportunity to dive into the product and see exactly how EPA is helping sellers become the best versions of themselves. Adam, thanks for being here. Really excited to go into the EPA platform and appreciate you taking out some time to do this. Uh yeah, thank you Anthony. Uh it's great to be here. I'm very excited. Um guy uh guy guys told me how how much fun he had on the show last time um last time he was here. So yeah, really looking forward to dive into it. Should I give a bit of a introduction for the audience for myself? Please, please do you. Yeah. So, I'm Adam. I'm I'm the commercial leader here at Epster. I report into Guy. I've been in and around the the SAS ecosystem for the last decade in various contributor manager leadership positions. Um I have always been in a position where I've helped businesses do more with their data. Um, I'm I'm a a bit of a data geek at heart and um really re really kind of hope hopefully we can kind of share share EPA in a really really positive light today. So, if you're happy, Anthony, I'll I'll I'll dive straight in. Yeah, let's do it. And there's a lot of powerful data that comes out of EPA. Um, so I'm sure you have a lot of fun with it as well as leading the sales team with EPA. It's very meta to be able to do that. Um, but yeah, excited to see what we have today. Yeah, absolutely. Absolutely. Look, you you you you said yourself there's a ton of data and I think um that's probably a really good starting place. Um if I can um I can just bring up some slides here for a second. I hopefully it won't bore everybody by PowerPoint. It's the it's my least favorite thing to do. What guy would have talked about on the on the last show was the state of the market and the problems in the market. And we see that, you know, 80% of reps nearly a missing quotota. There's this huge delta in velocity between your top and your bottom performers. Uh and even though the the number of deals that is slipping um across the market has dropped, we're still at like 36% nearly 40% of deals all deals slipping in the pipeline. Um and we see that there's this huge inconsistency that that delta in velocity is an inconsistency of of seller performance. Um you know our our our A players for top 14% of sellers are a players are delivering 80% of the revenue and that isn't sustainable. And while there are tons of tools out there in the market that provide lots of features and functionality, there are businesses that are, you know, spending money on on on lots of tech and lots of platforms. And yet this is still the case. You know, there is still a huge disparity between top and bottom performers. And the way the way that Epster thinks about this is is really is really more about we we see huge gaps. we see hu huge gaps in the in the in the visibility and insight that sellers, managers, and leaders have into their pipeline. Um, they're able to understand signals, but they really don't have a real grasp and a handle on all of the data points that are influencing revenue. And what we strive to do here at Epster is bring all of that together into one place. We connect to multiple different data sources. And we firmly believe that Salesforce is and should be the single source of truth. And so what we've created in it in its you know rawest form is visibility and transparency in a single place inside Salesforce that is designed to kind of transform the way that people view the the risk and the health of their pipeline. It's really really common for people to just notice the top A players, the top performers, the top closers and really focus on just maybe making them better. But if you can get the 85% of your BEC players to just incrementally improve for an organization that has a decent sized sales team, that's massive improvement to overall performance. So I think it's a really strong mission to be on and if we can just emulate a little bit of what those top performers are doing with the bottom performers, the results could be massive. Yeah, you're absolutely right, Anthony. And and look, it's it's it's not like our BNC sellers are, you know, are lazy or they don't want to win. You know, we we're we're all in sales to win and to to close business and hit our numbers. It's a performance sport and sometimes we just need the proper guidance and the proper understanding. And when that information is siloed or I have to log into 10 different systems to really get an understanding of what's going on on every opportunity, it's a it's a it's a it's a barrier. It's a barrier for people using the insight and using the information. So, what we've done and what I'm about to show you is hopefully you can see my screen is is an opportunity record inside Salesforce. And what Epster's done in the background is it's connected to the mail server. It's connected to the conversations that we're having and it's connected to CRM. It's looked back in time over the history of all the closed one and closed loss opportunities and it's brought a ton of rich insight onto the opportunity record without anybody having to do anything that gives you real life visibility into risk into relationship into all the signals that are that are going on with your with this opportunity that are going to provide you insight into the health and the likelihood of this deal to close. So, what I'll do is I'll I'll start by um scrolling down and I I'll start at the bottom and I I'll work my way up. So, I mentioned earlier that we connect to the mail server. So, the mail server is the single source of truth for all the communication and it's a pain in the um proverbial to to get reps to log in to um to log every activity and every contact. Um and we typically see that when we when we work with clients about 70% of that information is missing from CRM. So you know when it comes to understanding things like how multi-threaded you need to be which are the right stakeholders to be involved in an opportunity 70% of that information is missing then businesses are blind then they're making decisions without the right information. And so we fix all that and we can fix all that historically within the first week of of of engaging. And what that looks like is we bring this onto the opportunity record, account record, lead and contact record inside Salesforce and you get this visual representation of all the communication that's taking place. You can see the contact, you can see the direction of communication. If you want to read the email, you can see what's going on. Uh if you want to add that to Salesforce as an opportunity as a as an object, you can. Um many of our clients use to use us to store all this information. Um, but you can get a quick look as a as a manager, leader, or seller as to all the all the communication that's taking place. You can you understand where your the strongest relationships are. So, so of all the the contacts that I'm talking with, you know, I I want to know who's who's the main contact there at a glance. I also want to make sure that my database my marketing database is full. So, if I want to add those contacts into Salesforce, I can. Um, and I guess one of the the the key things that you'll see there, Anthony, is this idea of a relationship score. Um, you know, this is uh this is something that we're really proud of and um one of the differentiators from us is that we we we're able to provide you that relationship score and that relationship trend um over time. And it's a it's one of the leading indicators of the health of an account, an opportunity uh and and a and a relationship that and it really kind of gives you the the clearest indication of the likelihood of this deal to close, right? Um, and not only that, because we um because we look back historically over all of your closed one, close lost opportunities, we're able to start setting things like benchmarks. And that brings me really neatly on to the next the next the next kind of set of information or suite of information that you probably see in front of you on the screen. Before you move on from that point, I I want to highlight for those watching how important and foundational that is that not only are you saying, "Hey, we'll begin to capture emails and meetings that are coming in right now so you can start to begin to do relationship score," but going back in time and going back in history and gathering all of that intelligence a lot. I know when you start an implementation, I don't know exactly what the percentage is, but it's a high percentage of past contacts, past meetings, past activities that have happened that never made its way to the CRM and you get to pull that in. It's it's absolutely gamecher when you have that data finally enriched and finally in one place where you can benchmark it and see the relationship score too. Yeah. No 100%. It's it is it is transformational and you know I speak with lots of um lots of revops leaders about about this and you know they are trying to do these kinds of benchmarks they're trying to understand you know who are the who are the key stakeholders that we need at each stage and how long has this been in the pipeline for and what happen what does good look like for our organization they simply can't do it because they don't have enough data in the system and that's one thing that we can fix immediately um and hopefully provide revops leaders the opportunity to get back and do more critical work than trying to pull together all this information. Um so yeah, really really good point. Really good point. Um and look, this is just an example, right? But um what we can see here is that again we're connected to the mail server. We're looking into the calendar. We can see that there's no future calls, meetings, or tasks booked. We've benchmarked this opportunity against um historical business, and we can see that look, it's been in the current stage for 24 days. And and when we win business, uh you know, the upper benchmark for us winning business is typically only 10 days. And we can also see that the opportunity is 44 days old, but typically the opportunities when we win, um they're typically only 20 days old. Now, that doesn't mean that this is a a disaster of an opportunity. But it does mean that as a seller, I need a I need a narrative as to why this is taking longer to close than usual when it comes to um my pipeline review. Um, and I probably should have a good answer because I know that my manager is going to see this and probably one of the first points that um, he's going to ask me about is why is this taking so long? And you know, we know that um, you know, slippage and and uh, you know, when when slippage deals slip beyond, you know, 3 to 6 months, you know, win rates at like 3%. You know, you can check out the benchmark report um, you know, go to the EPA website and download it um, if you want to find out exactly what that number was. But, you know, a huge impact on on on win rate on on win rate by deal slipping. And so, by having this visibility, we're surfacing all that risk in the pipeline and allowing sellers to, you know, make make better decisions, make their next steps, have more constructive conversations with their managers. We can also see there's been no activities. And actually, you know, the benchmark for uh Patrick here, um he his benchmark for closing deals is at 76. His relationship score is only 50, right? So, he's got some things to work on. Um, and really kind of benchmarking, understanding all of these all of these factors that are influencing the deal is really, really important. And when you do this and you make you make it easy for reps to see what what needs to be done and what's going on in their pipeline, it makes it much easier for them to to take the necessary actions to selfs serve to to to fix these problems really really quickly. The next thing that I'm going to touch on, um, other bit kind of bits of visibility, you know, you you can you can get more context over the, um, over the activity, um, that's been going on as over over the over the duration of the opportunity. Um, if you if you want to visualize that activity in a different way. And another thing that we're really key, we're really hot on here at Epster is qualification. Um, you know, we Medpic for us is our gold standard, but this is just a method of capturing capturing uh information. And so we have businesses that use spin, that use band, that use medic, that medic um even have their own custom um qualification uh capture uh fields baked into baked into epster as well. I think a lot of the work we do at Lean Scale 2 is helping people set up a qualification method, making sure we're capturing the data stage by stage. Is this where people will capture notes for this so the rep can easily enter in the information here? Yeah, exactly. So, so look, you know, we we believe in scoring. We believe in scoring medic, right? and and if you score it, you can measure it and therefore you can understand patterns and you can spot deficiencies um in across you know a large broad group of sellers and you know you can you can manually you can manually add data and and and tweak this as you want. One of the really cool things that Ebster provides um with its call intelligence tool um is the ability to auto capture um qualification from the conversations that we're having um without actually having to do much work at all. Um so let me just let me just share a different tab briefly. So again, you know, we we we can do this with Gong recordings, we can do this with your Zoom calls, with Teams calls, bring everything inside Salesforce so you have that kind of single source of truth of all of your all of your data and all of your insights. And we bring these com we bring these kind of key moments onto the onto the opportunity record. But to touch on that qualification p you I mean like look you get all of the um you get all of the the things that you'd expect in in terms of a call summary um in terms of the transcript in terms of the you know we can identify key topics but the main use case here is really identifying and capturing that um qualification status. So what the bot what the EPster bots's done here is it's analyzed the call and it's recommending that look metrics we believe you know the the AI believes that Esters's uh that the metrics on this opportunity should be a three and the rep can have a look at that he can understand why and it's also recommended some notes as to as to what's driving that score of a three and the rep can update um or he can ignore it um you know it's it's important to give the rep license you know we the rep has to build this overall qualification over multiple calls, multiple emails. And so, you know, we do want to give we don't want to remove the the the kind of the license from the rep, but we're just trying to make it as easy as it possible for the rep to capture as much information as as as humanly possible. And I think like one of one of the big advantages for businesses, particularly those mid-market businesses that have got, you know, anywhere from 20 to 150 sellers, right? like your individual managers, your leaders have got to interpret, you know, different, you know, biases and different, you know, different um ways of doing things and capturing information from 150 different people. You know, some people lean negative, some people lean positive. What the AI does is when you're using this at scale is kind of remove all that remove all the bias, remove all the um you know in subtle interpretations and give you just blanket consistency of capturing information and of the the quality of information you're getting. And it makes it it means it's really really powerful for for for kind of then diving into you know which reps are are are underqualifying which reps are not proficient at you know uh maybe implication of pain you know all all of those kind of things that we we bring that and make that really easy for people to see um because we we're capturing that data consistently at scale. No that's incredible. So I just want to I just want to clarify. So any call recorder they're using, you have a native one in EPA if they want to use that one, but if they're already using Gong or something else, you'll capture the transcripts and then you'll automatically populate qualification methods from the transcripts of the call. That's yeah, absolutely huge timesaving and like you mentioned just getting it accurate and unbiased. Um because who knows what reps are typing into these fields sometimes or like you know I don't want to say anybody's doing anything with mal intent. Maybe they're just uninformed but like are they actually gathering the right qualification methods or the right qualification information and are they putting in the right data um or are they just thinking that they're qualifying and moving something along when maybe they didn't actually have that conversation that needed to be had. Exactly. That's exactly it. You've hit the nail on the head. Let let me jump back to the opportunity record here and I'll I'll wrap this bit up and then we'll get into some of the more sexy stuff. The fi the final piece of the puzzle we've just touched on call intelligence. Yes, we we're looking for insight from the conversations that we're having uh in order to be able to inform our um insight into the health of the opportunity. And so, you know, every company, every company, every customer of Esters is different. And so these key moments that we pick out of the conversations, we work with our clients to define those prior to deployment. And they might be different not from client to client, they also might be different from function to function. So you know th those key moments if you're a you're in CS and you're working on a renewals basis be very different to you know hunter gatherer in um in net new. And so we can break it down right to that kind of really granular level. But what we're displaying here is the is the is the insight that we've picked out that matters most to the to the to the to the client on the opportunity. And so you can see here on the positive side, we've got um a sense of urgency and readiness for implementation. Um we've talked about uh timeline and the fact that they want a deal in place by the end of the quarter. Um and and and in the same on the negative side um we can see that a couple of competitors have been mentioned. Uh and so again we we we're really trying to bring this insight out to inform decision and inform leadership of um you know where the risk is what's the likelihood thing. And the beauty of this is that if I want to go as a manager and a leader and have a have a quick look, I can hit playback and right on the opportunity record inside Salesforce, I can view that, you know, you minute and a half, two minute clip on the key piece of information that I that that I that I want to see. Um, so that's really cool. That's so smooth. Such a smooth process. And giving the information that you need right up front, organized really well. It's really really intentional. Yeah. Yeah. No, honestly like you know from a leader you the last you know I've used call intelligence tools before you know I think they're great I I one of the things that you know I just found I couldn't manage was like trying to scroll through you know managing six seven 10 reps scrolling through hundreds of gone calls or uh you know other calls to um to really kind of find out like what are the key bits where's the bits that I'm going to have the most impact or make the most difference to me or how do how do Iident identify what those what those where those where those where that gold is? Um, and this really does that for me and it means I don't have to kind of leave Salesforce which is which is brilliant. So, I guess look that that that wraps up the um the opportunity stuff, right? We've we've we've we've gone through a lot of information. We've we've sucked data from the mail server. We've sucked data from the conversations. We've pulled historical opportunity data from Salesforce to provide you all this insight. Um, and this is on an opportunity record, but how do how do people manage this at scale that and that's that's what I want to dive into next. So, what hopefully you can see my change of screen there, Anthony, but what what we're looking at here is Estster's pipeline insight tool. And what we've built is a visual representation of every opportunity that exists in the business. Um, and you can slice and dice this in information in any way you want. You can look at deals that are um uh that are you know that are current for this quarter. Uh you can look at uh the you can log in by various different hierarchies or individual users by product types, revenue types. You can use EPA's smart insights function which will tell you all the deals that are stalling or that have warning signs. But it's a really easy way to manage a lot of opportunities at scale. We're logged in as Wayne who's an individual contributor and Wayne can manage his pipeline a lot a lot more easily right he gets an initial glance of of all his opportunities and you can see look he's got a ton of opportunities where he's really high engagement this relationship score kind of acts as that first gut check um and you can see how that relationship score is trending as well on the flip side of that if he wants to interrogate the lower end of his pipeline he can see it's got a bunch of opportunities in here where there's no engagement or or very little engagement um these these these deals are realistically they're clogging up Wayne's pipeline. They're they're they don't appear to be real. Um and he should probably just close lose these deals and move on and focus um where he's got high engagement. Um and and he's got he's got, you know, a real chance of winning these deals. So that's kind of the first thing. The second thing you'll notice is this idea of a deal score. the deal score is um you know a 100 deal score would be a close one opportunity a zero deal score would be a close lost opportunity and the deal score should increase as we move through the stages of the pipeline but the deal scores impacted by all of those positive and negative factors. So all of those signals that we um have identified by looking at all the data sources by uh mapping those those to how you know what the the benchmarking of of what good looks like when you win over the last 12 months worth of closed opportunities. All of those all of those signals all of those positive negative factors are going to influence the deal score. So you can have a look. I've got a good relationship score. I've got a good deal score. However, look, I've got some warning signs and you can click on those and it takes you into the the sidebar tab that pops up and you can see, look, I can see all my negative factors on these deals. I can see the risk factors. Um, I can see what I'm doing well, which is great. My relationship scores increased. I've had activities in the last seven days. Um, however, I'm not multi-threaded. I'm not as multi-threaded as I should be. I need to get more colleagues involved. Um, I've got a close days in the past. Unforgivable if you ask me. Um but but you know there something that before a pipeline review I'd probably go and want to address that immediately. Um and look this we've got no future calls meetings or tasks booked. Again that's a good next step for me as a rep on this opportunity. Go look get that next step in place. Get that I mean what they really should be doing is booking a meeting from a meeting. Um I spoke a lot about bam fam in my time. Um but we haven't got a meeting in. Let's go get our next steps in place. Um so again as a as a as a seller it's guiding you what to do. as a manager, it's guiding me. What questions do I need to ask? What do I need to be looking for? You know, here's all the risk. Um, you can see your qualification. Um, you can see the contacts that you've got on the opportunity. Um, and again, you can see that activity timeline or from the insights tab. Click on any of these opportunities. Um, and you get that visibility. Yeah, this is great just to be able to see especially the intelligence of looking at what's being qualified, be able to slice and dice it. And this is such a better view for a rep to go through their own pipeline before getting ready for that pipeline review. Hopefully they catch um opportunities with close dates in the past and things like that before they get in front of their manager. Um but it just gives you all the information you need right up front. Yeah, absolutely. And look at that. We've built we've built we we've built this in mind for the rep, right? You click on the smart insights tab, you click on has a closed date in the past, and it's going to show you all the opportunities that have a closed date in the past. There's nine of them. Yeah. And if you're managing a high volume of opportunities, sometimes it's not a about negligence or something, you just may not have realized like, oh, it has been two weeks since I've reached out to them or, oh, I forgot to book a call on the last call that we had. So, just empowering them to manage a bigger book of opportunities to help expand their level of effectiveness. Um, it's really, really important to help them close as many deals as possible. that absolutely couldn't couldn't couldn't agree more. Um so how does how does all this roll up into forecasting right like we we've provided you all this data you can slice and dice it at scale um you can look at it you know it it maps to the hierarchy that sits inside Salesforce so if I'm a manager I'm going to get a roll up of all my reps opportunities I guess look what what we what we say is that look we we believe in bottoms up forecasting right if you if you take this approach from bottoms up we get the reps involved and and and committed to submitting a forecast week in week out backed by data, backed by information. Um, the managers will then come and submit their forecast. Um, if we do it bottoms up, we get a bigger number, right? Our job in in, you know, as revenue leaders is to make sure that we're forecasting accurately, but that number's as big as possible. And there are tons of tools in the market that will look at signals and go, you're going to hit that number. But if you do it this way, if you give everybody in the organization access to the data and the metrics that matter, we drive better performance and we drive we, you know, here at Epster, we're able to guarantee that. We guarantee that we will improve quoter attainment. We guarantee you that we will improve your forecasting accuracy. So, yes, we want to get you to that accurate number, but we want that number to be as as as big as possible. We want you to we want you to win more deals. We want you to um we want your reps to achieve more of their quotota, and we've built this tool to help them do that. So, like as as as we segue from kind of that to forecasting, the the idea here is look look, you come in as a rep, you have a weekly forecast cadence, I can check out my deals. I can see that I've got a good relationship score. I've got a reasonable um deal score. Um I can see the warning signs. I can see how wellqualified my my deal is. Um and I'm going to make a forecast submission, right? I'm going to put this this is either going to stay in pipeline, I'm going to move it to upside, or I'm going to move it to commit. And on a weekly basis, we'd expect our reps to be making a forecast submission. Um, and they can submit their forecast by very very very very easily. They can submit their commit forecast. Um, they can they can make some notes. They can adjust the numbers. They can, you know, they can account for a pipeline that's created and closed in in period. All of that kind of kind of good stuff. But what we also say is look, the manager needs to have license to forecast as well, right? So, the manager might come in here and say, "Look, you know, uh, Wayne here, he's got decent relationship score. He's got great deal score. Um, but he's not he's he's not qualified enough on on the paper process and he's got this deal in commit. So, as a manager, I'm I'm going to hedge that. I I think that's an upside deal. I'm going to do everything that I can to help um help Wayne close that, but I can't forecast that yet." Um, and then the manager will submit their forecast at the at the same time. So, how do how do we then view what the you know, view the forecast? How do we view the performance of the business as a whole? What you look here is Estster's forecasting tab. Again, everything's inside Salesforce. Um, I'm logged in here as James Worthington, who's the uh VP of sales. So, he's responsible for the whole business. He can see his Q2 quotota. He can see his attainment to quotota to date. He can see his all of his team members. And you can drill into this information. You can see how Helen's team members are performing. Jacob's and Josh's. James is going to look at this and say, "Hey, look, Helen's smashing it. I need to spend most of my time with Jacob and Josh and figure out how we get them to quot." Um, you can see the commit submission for the business. You can see the individual team commit submissions. You get two numbers here. So, one is the rep submission and then one is the manager adjusted submission. Um, you can see the upside submission. Um, and we pull some really cool insights around things like uh, you know, your required coverage and your pipeline coverage. So, we've done some analysis historically because we know the pipeline really well. We can see that um, Josh here has got 6.8x coverage and he typically based on historical performance, he requires 3.6x to um, to hit his target. So, what the message to Josh is, look, you're behind. You're behind on your um you're behind uh on Q2 relative to the rest of the team. You've got enough pipeline. I want you to focus on closing deals because we know that you've got enough pipeline to to to cover your gap. So, really at a quick glance, leaders in the business can see exactly how the business is pacing. Once you've got a visualization of exactly how the business is pacing as a leader or a manager, you want to focus on what's going to move the needle, what's going to help us get there. And that typically we find is focusing on the problem deals. Um, so I'm going to switch to our uh pipeline change tool. So the the pipeline change tool here is really a visualization of of of what's trending in the pipeline. we can see that we started the period um and where we where we're predicting on ending the period and we can see that you know as a as a leader certainly I'm looking at this right first up I'm looking at the deals that I've got in commit they're in commit for Q2 it's great that we've won some deals it's great that we've got some deals that are trending up some there's quite a few deals here that are idle and that that that that that's probably my second second priority but first and foremost I want to focus on these deals they're in commit for this quarter um there's 11 deals valued at $300,000 and they're trending down. And what I can do is I can click on that number. I can see immediately that I've got a bunch of these commit deals that are that have very low relationship score. There's a bunch of warning signs. We've got some okay deal scores and there are some good relationship scores. But what I want to do is I want to expand those deals out and then I can interrogate the pipeline in exactly the same way. So, I can see that, you know, I probably need to be having a conversation with Lucy, Neil, and James because these deals, they're in commit. Uh, we've got a bunch of warning signs. There's no engagement. They need to they need to come out and be closed lost immediately. Um, and you know, then I would probably start with uh, you know, these deals, there's we they might need some support in engagement. We might need to move those to upside and and and work on an engagement plan. But really as a leader within the space of you know 30 seconds I've identified exactly how the business is pacing. I've identified exactly um which opportunities are going to move the needle for me which are the problem opportunities and I've now got a a line of sight to exactly the conversations that I need to address that ASAP. So easy for a manager to just fly in high levels, see exactly where the forecast is, see where opportunities are moving, target. They have very limited time, so target the opportunities they need to and go figure out how they can help their reps. And this is what I think we were talking about at the beginning. How do we get those BC players to just perform a little bit better, get a little bit closer to that A player performance, and the results can be massive if you can focus that manager's time on where they should be. Yeah, absolutely. Absolutely. This is um this is something that we um we really care about and it's a it's a really good segue actually to um our funnel analytics tool. So we you know we we we we bench we talked about benchmarking time in stage time in pipeline. Uh and you said there like you know how do we improve those B and those C sellers. One of the this is one example of how we do that right but what you see here is is basically the funnel performance for the business. We can see and again you can slice that by quarter by um opportunity type by revenue type but you get a very um very quick view of you know the velocity your team's velocity um you know opportunities close win rate sales cycle average order value in a very quick snapshot and you can filter this by indiv you can drill down to individuals but you can see what's moving through the pipeline and how things are moving through the pipeline and obviously this is dummy this is dummy data right this looks like a beautiful waterfall I have never seen a client's client's funnel look like this, look this pretty. Um, obviously mine looks like this. Mine's perfect, but you know, that's that's for another story. Um, but look, one of those things is look again, you can drill into all of this information and you can drill into pipeline insight so you can see those opportunities that slipped or dropped out. Um, but one of the things that we're talking about around that benchmarking is look time and stage. So immediately what we've done is we've got visibility of um who's lagging, who's who's dragging. We can see Jacob here. His um his average time in stage is is um 24 uh in average time in the value proposition stage is 24 days. However, when he close wins deals, his time in stage is only 14 days. So that tells me that Jacob's team is hanging on too much, hanging on too long to deals because anything that's over that long time in stage, anything that's over like 15, 16 days is is probably not going to close. So that might be that might mean that I need to work with Jacob and his team on better crafting value propositions, better communication of business impact and outcomes to to to clients. And it's really just a really good way of spotting, you know, trends and patterns in big data sets across across the funnel and helping you kind of root out those problems. Before we wrap up, Anthony, there's probably just one more thing that I I think I I would like to show you, but it's this this this um forecast change. So, this is this is where a lot of the sea level, a lot of the the the leadership will spend their time, you know, they they want they want to know what's happening to their forecast over over the period, and they want to know why, right? They want they want to they want to understand you know what's been submitted um at the start of the period versus at the end of the period and what what what happened in between. And again you can see that look in this case we've pulled in a chunk from um from pre from future quarters. We've got some deals that are new in forecast. Uh we won a load that wasn't that wasn't committed. Um and at the same time we've we we've had 181k um value slip and again you know all of this all of this data is drillable. Um and within a within a very few short clicks I can identify all of those deals that slipped right. They're in upside but they've slipped. Why have they slipped? We've got no engagement. We've got low deal scores. We've got a bunch of warning signs on the deal. So again, it's it's a it's another way of slicing and dicing this data. So I I I I think like from my point of view, Anthony, it's been it's been a whistle stop tour. Hopefully a meaningful a meaningful one. Um and uh hope hopefully it's added a ton of value. No, I think you covered a ton in a short period of time and especially because the Epster platform is so powerful and robust. But just to reiterate some of the things that I think really stand out to me and our team and to remind people listening, we're doing revenue operations for high growth fast selling companies all day long. You really hit the most important part starting with the foundation, getting the data in, getting the emails, the meetings, the contacts, the relationships. Everything we do is relational. Sales is relationships. So understanding the health of those relationships, going back in time, you have lots of tools that can start picking up where you are today, but being able to go back in history and pull all of that in now, that's super powerful. And that data foundation just gives you the opportunity to get started and is immense value day one. If you go with EPA, then integrating the call intelligence, autopop populating the qualification methodologies, getting the right information that a busy manager or busy rep needs to see on an opportunity. Single click into something positive going on with the deal, single click into something negative that's going on with the deal. Then seeing your whole pipeline in one place with your qualification, your uh contact relationship scores, being able to slice and dice your pipeline as a rep. So powerful. And then for managers and executives, the funnel analytics and funnel waterfall, huge insights packed into really, really easy to consume visualizations. And you make sure you have all the data there. So it's accurate and it's actionable. You can click right into any of those charts and start actioning any of that data. It's not living in some, you know, data warehouse plugged into a BI tool where the drill downs are tough to deal with. you can hop right in and start going from top level, boardroom, executive level reporting, diving deep into a specific conversation a rep had with a specific deal. So that's why when people are in market for a revenue intelligence platform, EPA, I think you really have put together all the components you need where a lot of them maybe meet one or two, but you really cover that full journey. And I love the mission. Let's get those B and C players performing at least a little bit more like your A players and then see the results that'll happen in your business. Yeah, I love it. Absolutely amazing summary. And look, you you the the point is is that you can't do the the last thing you said, which is improve your B and your C sellers without data. And I'd also like as a side note, we're moving very very quickly into an AI first world. And having that foundation of data is probably one of the most important things to getting business's AI strategy right because AI is only going is only as good as the data that it has access to. And if your data is in different silo, disperate silos all over the place, not structured, um the AI is going to provide meaningless output. And it's one of the things that I think businesses really need to focus on in the next 6 to 12 months is to get their that foundational data piece right because if they don't any AI that they layer over the top of their business unless it's within specific tooling is going to have a really hard time. Oh, totally agree. And we talk about this all the time at lean scale. It you can swap in and out AI models, AI platforms all day long. Don't focus so much on which AI tools you should be getting. focus more on we really like the term ontology. So focus on the data the accuracy and how you structure your data in order to train a model. If you do that really really well don't worry there's going to be plenty of AI tools on the market that will be able to read that data but you have to start there. Yeah couldn't agree more. Well Adam this has been awesome. Thank you so much for sharing so much in such a short period of time. Um, we really appreciate having you on the Lean Scale podcast and we can't wait to see what you and the team at EPA build next. Amazing. It's been an absolute pleasure, Anthony. Um, if anybody would like to know more, find out. Yeah, hit me up on LinkedIn. I'm I'm on there 97% of the time. Um, so yeah, it's been great fun. I've really enjoyed it and yeah, hopefully we can do something like this again. Would love to. Thanks, Adam. [Music]