Hi, Shadab again. So let's talk about the results of revenue engine diagnostics. So this is the last video in the entire series. So if you haven't watched the series, we have four more videos before this. So you get to this point that covers the introduction to revenue engine diagnostics. We have the go to market and data model audit and discovery. We have the benchmarking dashboard and experience audit. We have the revenue mapping and quick will capture. Capture. And then we have the product roadmap design and the community behind it on how we think about the product roadmap and how we built it. We try to make it as actionable as possible so that we can create value as soon as possible. And then finally we land here the revenue engine diagnostics results. This is the final part of the series and this is the final step where we collect all of our findings, consolidate them only the vital findings for this demonstration purposes. I've kept it fairly short, but this can be very comprehensive as well. So depending on that we spend that much amount of time, this is where we consolidate all of the findings, share our recommendation, and then work will get to your desired outcome and ultimately help you grow your revenue and at the end of the day, retain more revenue. So very first thing is the agenda. So we wanna talk about the benchmarks. Within that, the volume, the conversion, the deal size, retention, the alignment, what we saw in terms of the discovery, what you told us and what HubSpot told us, and then the data reconciliation. So how do we think about the discrepancies that we are seeing? Because this is gonna occur and it's our job as the ops professionals and consultants showcase this to you, create visibility for you, and then we can move forward from there on with absolute transparency and just driving down into action mode. Finally, the recommendations where we recommend the solutions and prescribe solutions basically to fix those things one by one and help you get to the upper level of of maturity in your rev ops journey, in your rev ops maturity model. So let's talk about the benchmarks. So there are a couple of things. First is the volume, the conversion, the deal size, LTV, and then the retention. So let's talk about the volume first. So again, these are all example and dummy data and I've just deliberately kept it short because it can get super comprehensive, but this is for example in demonstration purposes. So inconsistent MQL generation, our hypothesis is the MQL generation month to month is often indicative in lead to MQL qualification is either broken or lead generation something is weird going on. So we see a lot of inconsistencies since it was high and then this sharp drop and then this start climbing, which was a good sign, then a sharp jump and then it did start dropping off. So the implication is your sales team cannot manage the resources and may not be seeing all of the qualified lead, which is a very bad and critical sign for missed opportunities and ultimately missed revenues. So associated epics that we showcased in the roadmap earlier and we have built in the roadmap is the lead life cycle stages and lead scoring, volume and conversion. So high MQL to SQL version, while on the surface, it may look like it's a positive sign since we are almost covering all of our MQLs to SQL. But there might be a very high barrier to entry for MQL. I think you might be missing out on very fairly qualified leads, but just because your qualification criteria is so tight, you're just missing out on all of them or something technically might be broken that you can think. So again, your sales team is again missing out on all of the leads, even though this percentage may go down a little bit. But if we can increase the volume up here in the funnel, then it will have a lot of positive downstream effect all the way to the customers. So think about that. And then associated epics are marketing to sales handoff and lead statuses. High kickoff time. So we have two stages before the kickoff stage in our case in this imaginary company. So five point five days plus eight point one day, this is like thirteen point six days. So we are experiencing like two weeks worth of delay from the time they close to getting things kicked off. So we need to take a look into that since they have already trusted us with their business. It's our job to take it to next level and provide excellent services. So associated epic in the product roadmap is sales to customer success handoff. Okay. Let's talk about alignment. So let's reconcile a couple of things that we already did. We did the discovery, what you told us, we did the experience audit, what we see is happening and the benchmarking dashboard on what HubSpot is telling. So let's talk about that. So discovery told us you have like average deal size of 13,000 across all products, but your average deal size in HubSpot is giving a very high number, like more than three times of that. This can be a sign of wrong product mapping, maybe like the way people process, like the way your sales team is handling deals in the pipeline is like not reflective of what you're saying. So we need to talk about that. This is for future discovery. Key data invalidity. So data status is missing and invalid. We see a lot of revenue, like 18% of revenue. We don't have like a product category assigned to it. So we don't know what we sold, at least in the CRM. Now we have to go back to the bookkeeping software to just know where it came from, or it's gonna be almost impossible to reconcile the closed won deals, the closed won revenue to revenue realized in the bookkeeping system, which is a massive item. Okay. Recommendations. So a couple of things we recommend, just made up example, but data migrations so that all of your historical data is correctly in HubSpot technical setup. So your settings and the core components, the admins of the back ends of the HubSpot are correctly set up. Lifecycle stages and your sales stages so that you can get conversion numbers and your volume numbers. Correct. Both in the lifecycle stage funnel and in your sales stage pipeline and conversion metrics. And then we wanna do lead scoring, sales to CS handoff, and original sources. So lead scoring is basically, you know, we assign positive and negative actions and attributes to help qualify your marketing leads so that we can improve those numbers from MQL to SQL once we fix what's wrong in terms of the threshold for MQLs, like the barrier to entry. And then the sales to CS handoff. And then original sources is an interesting one where we try to attribute the revenue to the original source where the deal came in. This is very robust and complicated, so I won't be able to discuss this. We can have a separate series to just discuss just this part or maybe someone else from my team can share more information on this. And then some quick wins we quickly identify. So lack of visibility is when NQs are passed to sales. So let's implement a Slack notification in the channel. Primary conversion form is currently broken. Okay. Let's fix and connect to HubSpot. Zoom app is not currently connected to your HubSpot instance. So let's connect Zoom for all users. And then these are some documentations that we share as a resource. What is the technical setup? What are life cycle stages? What are sales stages? What are original sources? And what is lead scoring? So that's pretty much it. I hope you enjoyed this series and I hope to see you in some other videos. See you.