Hey everybody welcome to the stacking group podcast. I am Tori Kenlek and today. I'm joined by my colleague Matt Matt You want to say quick hello? Hello?
That's all I'm gonna do. Oh, nice. That was good. Well done So Matt and I have been having some conversations.
He's been doing a lot of great work lately and in particular on a Deliverable that we provide to a lot of our clients here at refine labs Which in my opinion is is an absolute staple in demand-gen marketing, especially, you know a lot of the the analysis work that you know That fills up a lot of the day-to-day for for demand marketers But the one thing that I've really noticed with some of Matt's approach with this specific item is that our clients have just been loving it and it has been really opening up a lot of eyes creating a lot of really interesting insights and One thing that I think has been really surprising to me is just how few companies You know are actually going through this this exercise So the big reveal here right is is I'm talking about a win-loss analysis for those of you that are unfamiliar right a win-loss analysis It's pretty self-explanatory right you're going into a CRM and taking a look at you know, whatever the time period I know we like to do things kind of quarterly around here But for a period of time looking at the deals that have been won the deals have been lost inside the CRM and trying to Identify any any trends or key insights, right? And so, you know, there's certainly the Quantitative aspect to this, you know that can come from you know having good standardized reporting inside your CRM But the qualitative insights I think are really the big unlock and where so much of the value is coming from and that is what I've seen You know, Matt able to uncover for a number of different clients at this point So I wanted to bring him on and see if we could you know hear a little bit more about like the the process, right? So Matt, I'm gonna just kind of see if we can pull you into the conversation here I'll get off my soapbox, but you know, I really want to kind of start with the basics here, right? Like what what do you think is so important about a win-loss analysis?
And why is this something that you know that marketers should be spending more time doing? Well, first off, thanks for having me on to talk about this. It's actually funny I had never done win-loss analysis before I got to refine labs and when I got tasked with the project I kind of went through and was like, oh my god, there's so much stuff you can learn from doing it It's amazing And so it just kind of got me down this rabbit hole of just building out as many different insights as I possibly can And so I'll go with like what I think most people think about when they think about a win-loss analysis It's okay. What are the reasons that we lose deals and then you know, we also use it to confirm our ICP, right?
It's like, okay, are we selling to the right people? And I think those are you know, the sort of the staples of what people fall back to when they look at a win-loss analysis But I tend to look at it very holistically because if you're using the CRM Properly and if and by using it properly I mean literally using it as your primary business tool by which all of your best information and cleanest information should go in there It should be informing a lot of parts about your go-to-market strategy And so to me it a win-loss analysis is great for Validating messaging because if you look at one of the things that I noticed with most companies when I'm looking at there They're doing the win-loss analysis companies are really good at tracking closed-loss reasons You know, they have it aggregated they have details to it some some companies are smart to require it both of those You know, it's like, okay, what was the big reason we lost a steal and then give me some notes on why we lost a steal also, right? But the other I think flip side of that the inverse of that which companies don't really look at quite as much is Why did we win the deal and what are the little reasons that we won that deal in the first place? And I think when you're a company especially when you're the marketing department But if you're coming just in general and you get asked by your PE firm or by the CEO and they ask you okay How are we growing right now?
And what are the reasons we're winning and if you can't look at something quantitative and qualitative to support that It means you have a gap in your analysis That's you know making it more difficult for you to figure out why you win deals So to me looking at and tracking close one reason It's just as important as tracking your close loss reasons and it helps to validate your messaging It helps it's something you should be looking at against all aspects of your of your go-to-market motion like pitch decks for sales You're your your homepage copy, you know, your content strategy and most companies aren't looking at close one reasons all that much And then on top of not looking at it. They're also not looking at they're also only trying to box it into like one reason why we win Right, so I kind of unearthed this with one client that I work with who was smart enough to track close one and lost reason detail And they were going in and they were picking really good notes on why they won deals and they weren't aggregating it They were aggregating close loss, but I kind of thought about huh What if I just went through each of these it was a pretty young company They only had about 45 close one opportunities I was like what if I go through each of these and just aggregate reasons for them and I just do I just do that little bit of dirty work And so what I was able to unearth was that there were really about three or four primary reasons They were winning deals and none of it matched any of the primary messaging that they had on their website And so that's kind of where I got the idea Well, gosh We really should be looking at close one reasons and with a lot more scrutiny and not just close one reasons But we should be allowing our sales team or our rev ops team to ascribe multiple close one reasons to a deal because there's never just one reason or You win or lose a deal in the first place. There's always multiple reasons Yes, there's a primary and a tertiary but you should have all of those captured So you can see what are the big reasons why we're winning and the big reasons why we're losing and then hey That gives us a lot of great data to take corrective action on and kind of look at the whole kind of Picture of our go-to-market motion and figure out is it congruent with the way we're winning customers right now So let me let me ask you um, there was a lot of great information there. Um, so Hearing you know the way that that you've kind of gone about this right?
I think that there's probably a lot of listeners right now that are probably listening and trying to figure out like okay How do I get started with this? Maybe I don't have this, you know, this this in place right now Um, and based on you know your your your recent experiences I think that you know, that's exactly what we can help people get started with right now is is you know The the right way to kind of kick something like this off So, um, you know what you had just kind of suggested there right is is you know Going through each of these these closed one deals, um and trying to you know effectively kind of summarize or distill down The reasons why the the company wanted to deal. Um, do you think that there are any like, uh, High-level categories that people should be considering right off the bat or is there something that that really needs to be 100% unique to each business, um, you know, if you're if you're let's say setting up like picklist values or something like that inside CRM Yeah, it's honestly it sucks to say for people listening to this hoping for some kind of magic magic roadmap for this But it's always going to be unique because everyone's CRM looks a little different and they all have little areas of Walkiness that you just kind of have to deal with on a day-to-day basis So the first thing you got to do is look at the opportunity object in your salesforce or your deal object in your hubspot or whatever your CRM is Um, and then if you can look at account data also, you can also look at that in the account object But just look at all the different ways you're segmenting things within your company and that's kind of where I would start with right? So are we segmenting by you know, SMB, mid-market enterprise?
Are we segmenting by industry? Are we segmenting by you know number of? What have you number of widgets number of welding stations? Whatever does you want to you want to talk about like how are we segmenting deals overall?
And then those become fulcrums by which you can measure around and start to do analysis around and then you have to like, you know Put your executive hat on and think about the sort of go-to-market motion of the business And so one great example of this was like when I was doing one when floss analysis this company said we only want to sell the enterprise We're an enterprise company. We saw the enterprise since I was like, okay Well, you guys do a really nice job segmenting your data SMB mid-market enterprise So let's do this one loss analysis and it's found out like your pipeline velocity in mid-market It was like 8x what you're doing in enterprise from marketing source deals And it's like are you sure enterprises the motion that you want to go and mid-market is really not that much of a pronounced down The ACB is actually very similar and your win rate and your pipeline velocity was significantly higher than trying enterprise deals And so you know you have to look at your business and think about how you all are You know trying to grow and look at all the different ways that you're segmenting things within your source And that kind of answers the question for you, right? Okay, what can I do when loss analysis on to you? I just kind of look at it look at it as it's laid out Okay, I could do it off of this because we're tracking this because we're tracking this that can be industry That can be closed all the reasons that can be whatever and that sort of guides how you put together the the win loss analysis in the first Was yeah, that's um, that's awesome.
That's great advice. Uh, you said something really interesting just now that that I think um You might have mentioned, you know, a few minutes ago in the episode But it definitely, you know kind of perk my eyebrows up a little bit when you said it and so Um part of the you know, the exercise here, right isn't just understanding like why you're winning and losing deals Of course, that is the most important thing the overarching, you know, uh, themes and as far as like why you're winning and losing that that that is extremely important insights, but Um, the other thing that that you're kind of mentioning, right is like, uh, not just looking at overall why you're winning and losing deals, but you know Breaking these things down into, um, you know, into to different right different different segments Uh, and as you were describing that right like you were talking about, um, almost like, uh, ways to analyze things by Firmographic details or even by like technographic details, right? Um, here's what's interesting is that like These are also a lot of the same components that go into an upfront targeting strategy, uh, you know For what you're you know, what you should be doing for your campaigns, right? When you're thinking about building out your campaigns knowing who your audience is, right?
Like what let's say segment of the market that you know, the company operates in, um, more details around the firmographics, right? More details around the technographics, what tech installs do they have that might help us targeting, uh, you know, these These, um, you know, this way that we're effectively trying to identify like the right iCP to target with our campaigns Many of these insights can come from just looking back and understanding how you've won, um, or perhaps, you know, where you've lost Uh, and can be, you know, probably really telling as far as what you should be doing with your, um, you know, with your next round of campaigns Or even, you know, your your larger overall marketing strategy, uh, you know, in the in the intermediate to longer term here So, um, yeah, that's pretty interesting that, uh, you know, that that's that's something that you've come across here because, um, the other thing that I I want to kind of, you know, pivot into right now related to the win loss is what do you do with the output, right? So we've identified right now, uh, you know, that it absolutely has a play in your your campaign targeting But what are you seeing as some of the other kind of, um, use cases here around, uh, you know, around some of these these data and the insights, um, you know, what do you see as, as, you know, realistic expectations that marketers should have, uh, as far as what they can do with this information once they've conducted the analysis? Yeah, so again, that's always unique to your instance overall, but I think a couple big things that I think first off one big thing that you should just take away with you if anything, let's say you have the worst CRM in the world And you still want to do it when loss analysis and you're like, oh my god, I did this and there's nothing that I can do with any of this data.
Terrific. You can go back to your executive team and go, guys, our CRM is so f-ed up. I can't even do an analysis like this for us. We totally need to track stuff better as a result of this.
And that's also a good thing, you know, even, even figuring out what you can't track is still a benefit and you can, of course, correct that. So, you know, I've had instances where I've run it and it's like, okay, well, I can't, I can't track this, although I would like to. So this is something to maybe add to your roadmap of something to, you know, including your CRM instance and then require your, your sales team or whoever's in charge of maintaining your CRM to add it in the future. So we can do this again in a quarter or a half year and we have this data now and we can look at it.
So identifying gaps in your CRM, I think is just one of the big, one of the big pluses of a with loss analysis, whether or not you get actual insights from it or not, but it does do a good job between that for you. One thing is messaging, I went back into this. So like, you know, if you're tracking close one deals, look at the reasons you win. Look at, you know, where look at messaging on your website.
Look at content strategy. Look at, look at pitch decks. Listen to what your sales team is saying in calls as well when they're doing the elevator pitch and say, okay, is this one is an aha moment? Are they getting an aha moment off of this?
Are we mentioning this in these kind of pitches? Does this jibe with our customer research? And if not, there's just some gaps you need to show up. You know, you got to do a little bit of gap analysis.
I'm like, okay, why is the reason we're winning deals? Not the reason why people are excited about the product and discovery. And then you have, that's another kind of rabbit hole you can go through. It's almost another top and all into itself.
The other thing that I like to look at is, and we will get into job titles in more detail because that's probably the most complicated part of one loss analysis is looking at job titles. But what job titles most portend to close one and close loss? And then I think even more important, figuring out the ones that you can't avoid as part of the sales process, but who are most associated with close loss deals and then saying, what are we saying to this particular job role or job title or job function that just isn't resonating? You know, we need to figure this out.
Like, if we know that IT directors are a major part of the process. But our winning percentage with these people when they're involved in it is like 16%. And the sample size is such that we can't avoid not having them as part of the process. We really need to do a better job of understanding that persona.
You know, we haven't done a good enough job. We need to understand what what's important to them when they're looking at a solution like this, even if they're just someone who's in like the purchase stage at that point. So I think looking at job titles is just a major, major benefit of that as well. And then figuring out, you know, are we messaging correctly to keep personas that can involve in the sales process.
Another one is confirming, you know, second industry segment like, Hey, we're an enterprise company. Should we be an enterprise company though? Or SMB? But we have good success going with this?
Source to get these kinds of deals like, you know, we want to be, we want to be an enterprise company, but we're only good at SMB. But our marketing motion does a pretty decent job bringing mid-marketing, you know, great. Maybe we should leverage that a little bit more in campaigns. And then the other one's looking at industries, you know, let's say you're a company and you were like, you're tied in, you feel like you're really strong as certain industries.
Well, maybe there are other industries that you're actually better at than you thought. And if you look at it more closely, you figure that out. And then you can say, okay, well, why are we good with those industries? What are they fine beneficial to us?
Is there room to expand across that industry a little bit more so that we were even thinking of in the first place? So those are the main things that I'm looking at. If and when I can. And then how I'm trying to apply it once the data sort of tells me what's going on there.
So that those are just, I mean, I feel like I was just going through several instances. But it's really very expansive because like, you know, your serum is just such a black box of information, you could just kind of make it what you want, right? Yeah. I think I've got one more for you too, as far as, you know, what you should probably know when there's no way I got it all in there.
But again, you know, one that I've definitely noticed, you know, that there is a great amount of appreciation for is you take the output and you put it in front of the sales team and you put it in front of your product team somehow, some way, like I said, like, you know, there's, there's just, there's so many. It just blows my mind how few companies are doing this and doing it regularly. It should be a staple in your process. Like put, go put it under calendar the first day of the quarter.
You know, every single, every single quarter throughout the year, first day of the quarter, go do a three month look back and run this analysis, right? And then after you're done, right? After you've, you've kind of, you know, started digging through everything and it will get easier each time, right? The first time is probably going to be the most difficult.
First time to work. That's always a bunch of the, you know, the cracks and like Matt suggested, right? That's when you, you, you find these gaps within your CRM process. But as you're fixing these things, it will get easier, like everything does with repetition.
But the next thing you do is schedule that meeting with your sales team and say, hey, you know, this is why you're winning and losing deals because while they might have some suspicions, you know, oftentimes there's a little bit of like, recency bias or just overall bias as far as like how the sales team likes to remember, you know, their, their track record, why they're winning deals, why they're losing deals. And when you put the raw data in front of them or the aggregated summarized data in front of them, it's a lot harder to dispute those things and just kind of rely on, you know, selective memory or something like that. And then the other thing, like I mentioned, is the product team, right? There's a lot of insights that the product team would appreciate in all this as well.
And it very well could influence the direction that they might take your product. If they see that, you're continuously losing deals because we don't have this specific feature or this specific integration, guess what? The product team needs to know that information because they're going to be the ones that can fix that, right? And so, yeah, I think that those are some really critical use cases to, you know, to make sure that you're considering when you're figuring out what to do and how to socialize this information around.
So now, before we actually get into the nuts and bolts of this, was there, it looked like, you know, you felt like you might have missed something there? Yeah, so, yeah, missing product feature was supposed to, you kind of took the words out, I forgot about that one. But it's actually that's another one that I've run into where like, companies put missing product feature as sort of like the drop down select and then go into detail and tell you the product feature that's missing. But if you see a trend overall about like, hey, it's missing mainly these three, four, five things.
I mean, at that point, it's like, let's get out of the details and let's just make it aggregate. Like, to me, missing product feature is way too broad of a close loss reason. And if you're able, if your, if your RevOps team is super dynamic and is looking at stuff like that, or if you as the demand generator marketer can surface that up, you all can get, like, make a real quick course correction action there and say, okay, like, we know it's these three or four things. Let's see which one is actually the most common and let's prioritize that product roadmap.
So, missing product feature is a great one. So, there's be careful about just having that as a kind of catch all close loss reason though and see if you can kind of get even more granular if your product has a specific use case. So do you think that company should be using a pick list for something like this? Like once they've gone through the exercise and have figured out the product categories, do you think it's a required pick list or required open text?
What is your first? So, I think you should have a required multi pick list where it's like, okay, here's the aggregated bucketed reasons, multi pick list, not single pick list, and then likewise you should still have the detail in there because maybe there's even more stuff there so you should have both, but even your bucketed one should not be a drop down select or even a pick list that should be a multi pick list where they can pick a few different options. Awesome. Cool.
So, okay, the other thing that I want to talk through here right is like your process. So, you know, we get to do this for a lot of clients. And so we get a lot of practice with this stuff, which is awesome. I know our team and Matt is playing the key role in this.
We're going to start publishing kind of our playbook on how to do this in the vault sometime soon in the, I believe, the month of September, that's going to be going live. So, for all you vault customers out there, keep an eye out for that one. I think it's going to be a great piece of content that you're all going to enjoy. But, yeah, I think it would be pretty helpful right now, Matt, if you can kind of give a rundown of the process that you follow, right?
Knowing that we don't have a CRM up in front of us to kind of walk through. And so, as best as you're able to, you know, verbally articulate this process. Yeah. What can you share with our listeners right now about how to actually go about conducting these the win-loss analysis?
Yeah. Alright, so full disclosure, everyone listening here wants to do it. This shit is hard and this is time consuming. So, I mean, I just, there's no way around it.
Okay. I think first off is to just pick a time frame. Like if you're doing this for the first time, going 12 months back, you don't want to pick through 800 deals and neither do I. Okay.
So, find a good sample for yourself. Find 100. Find 200. But that's going to go back two months.
That's going back four months. If it's looking back across the entire existence of your company, you know, find a, it's not about how far back you go in time. It's about how good of a sample do I get where I feel like I can draw a relevant conclusion from it. So, and that's for the first exercise.
Okay. I wouldn't go longer than 12 months, but, you know, if you're, you know, if you're a startup and you've been in existence for just a couple years, it may be worth it, you know. So, first is just figure out how far back you want to go. All right.
So, I'm going to do this as if I was building it in Salesforce and then I'll put some aside for HubSpot. Okay. First off in Salesforce, you're really running two different reports because you want to run a opportunity report and then you want to run an opportunity report with job with contact rules. And so those are two different reports and you do the one with contact roles to do the job title analysis and you do the raw opportunity one to go find everything else.
It's not exactly the most convenient thing in the world. So, first I do, I just take my, you know, when I have, when I have my bull skin out or sometimes I use an envelope. I just write down all the different properties on the object, on the opportunity object, where I'm like, I can report this, I can report this, I can segment off of this and so list out all the different things ways you can segment. Those are going to be the things you put in the outline, right?
I want to put, you know, industry in the outline. I want to put employee band in the outline. I want to put market segment in the outline. I always want to put opportunity amount in the outline.
I want to put, you know, industry in the outline open AR on the outline. I want to put, you know, geography in the outline. If that's something that's important to me, if I'm going to look at things geographically. And then at that point, you're just doing the criteria.
So the criteria is simple. It's all deals closed within the timeframe you want to do, three months, one number. And then the deal stage has to be close, one or close, there's really nothing else, right? So sometimes it'll be closed and closed once and there's only closed, closed one, but you don't want any open deals in this.
Okay. It's just ones that are closed. At that point, you take the outline and then out, like the way it went with all the different properties that you can spin inside and reporting off of, obviously, close one or close loss reasons or other things you want to put in there, get the detail in there. And then you're exploring that report into Excel.
And then at that point, you're building pivot tables. And when you get into the detail area of it, if you don't have closed one reasons, but we're putting the detail in there, just add another column in your Excel sheet and start reading through each of the each of the close one reasons and start aggregating yourself. If you really want to do the dirty work, I've done that a couple of times. I found it to be worth it if you want to do that.
And then you're just doing pivot tables and some pivot tables, you know, it's pretty cut and dry, like, okay, we're doing well here. We're doing bad here. Usually what I'll do is on that pivot table, I'll have the filter for close one and then I'll just copy it and paste the paste the same pivot table right below and just change the filter to close loss. I can look at it side by side.
I can literally just start putting formulas to the right and just, you know, adding it up and doing ratio analysis myself, like right on the same sheet. That makes it pretty clean for you to kind of look at it. And then at that point, you're just kind of looking at it like that. And so that's kind of the way that I do it.
Now, for job roles, that's even that's harder. And so you do an opportunity with contact roles. And first off, if your company's not assigning contact roles to opportunities, you can't really do job-side reporting. It's just so you'll figure that out pretty quickly.
But that's how you do it. And then one of the first things I'm doing with job roles is figuring out one, is this company's product focused enough that we really need job titles? Or is there like eight, nine, ten job roles we sell into all the time and we can normalize this for ourselves and make it a lot easier? Sometimes that's the case, sometimes it's not.
And then I'm doing the same thing. You know, I'm looking at close one and close loss associated with job roles. And then I'm literally just listing it out to the right. And then I'm summing it up, close one, summing it up, close loss, and then doing ratio analysis.
And I'm saying, okay, like this one is X% associated with close one. This is X% associated with close loss. And then just looking at it sort of through that lens. Now, that's a bit of a walk-y way to do analysis, I might say.
But to me, it's actually the churros representation representation of data when you're looking at job titles associated with opportunities. So that's how I do it. So I do my own normalization even after I process it, just so I can try to bucket and group things together in order to under insights on a persona level. And so that's a little confusing and I would encourage you to check out our whole piece because that actually has a visual aid to that.
But it is very useful definitely. Now, I mentioned HubSpot. HubSpot's actually a lot easier to do all of this in because you can just run a cross-object report and basically get all of that stuff in one sheet and export it. And HubSpot makes it a hell of a lot easier in my opinion to do that kind of analysis.
You don't have to run two different reports. You can just run one. You can get all the deal object data in there you want. You can get the contact object data you want in as well.
You basically build a pivot table in HubSpot, export it, and then you're able to go do the exact same type of analysis. So I know that sounded like word soup because there's literally no visual aid, but it's literally just building summarized table or un-summarized table reports in HubSpot and Salesforce, exporting into Excel, doing or Google Sheets, designing the pivot table for yourself, doing a little bit of post-pivot table processing within the pivot table itself for some of the things that you may need to do like Jot title, and it pretty much becomes cake after that. Yeah, yeah. And I think the straightforward part is building the report inside the CRM.
Like we mentioned, you very well might identify some gaps in your CRM, in your process by going through this exercise. That is natural, that is normal, and that's okay. And it's a good thing. You and your team will be better off in the long run for having exposed those gaps as long as you fix them, of course.
But the real work in all of this is once that information is exported, you got to grab a cup of coffee and for those of you that wear reading glasses, go strap those bad boys on, and that is really the big leg work with all this, is you have to read through all of those qualitative insights that are coming from the people that were working that deal. And you know, do your best. You also have a beer, by the way, if you get through that data, and it makes you feel like having a beer, it's totally fine. Yeah, yeah.
Maybe one during and a few afterwards to help wind down from all that. Well, I don't know. Maybe it'll be a little bit more celebratory if you're analyzing the close one than the close loss. Yeah, I think there is one other item that I think is important to include in that sales source report that I'm not sure that you mentioned, and that is the opportunity to close date.
Right? So, you know, that effectively, you know, could be a filter on the report itself, right? When you're looking back for a period of time, but the reason that it's important is let's say, like Matt mentioned, you know, you're a startup scale up, you've only got like maybe a couple dozen, a couple hundred deals or something like that in your company history, and you want to analyze all of them, having that opportunity to close date on there could be pretty interesting as well. Like if you start to see trends over time of we used to lose deals this way, but you know, now we're losing deals this way, right?
That's a good insight. And so, you know, you're going to be able to see the things that you're looking for, the things that are not going to show up on a dashboard, the things that are not going to necessarily get, you know, bubbled up by way of just kind of offhand conversations. You're really digging deep for insights. And yeah, the only way to do this is manually and with a fine-tooth comb and really kind of doing that grunt work.
But in time, you will start to identify trends. You will start to, you know, see these things popping up more consistently. And, you know, each time you run through this analysis, potentially every quarter, you know, that's when you, you know, you're going to just keep getting better at it. It's going to become a quicker process.
And ideally, you know, you're just going to be seeing less of those close-loss deals and time, hopefully, you know, that's the next question. Yeah. Well, one other thing to mention because you were totally right to talk about putting the close data in there. Also put the age of the deal in there too, because you can't, if you want to look at pipeline velocity across your different market segments, can't do that unless you know how long the average deal cycle is.
So just a couple of other things you want to make sure you add there too. One other note on the date, because actually I didn't know this and I feel like an idiot for it, but if you run into the date and you want to run the pivot table off of it, and it's like, oh my God, I have all these different dates. I can't organize it. I can use the Excel formula, like equals text, parentheses, click on the cell, and then put in quotes like, mm-y-y-y-y-y-d, quotes, and then you'll be able to just give you the month in the year and then it's much easier for you to segment off of that.
So that's something that can hang people up and it's not exactly straightforward to fix that in your pivot table. Yeah, good. That's a good tip there. And yeah, for whatever reason, you know, Excel likes to assume everything is a date, except for actual dates when you need them to figure that one out.
Yeah. Let me shout out Evan for giving me that one because that was literally about to cry one day when I was doing that. And he was like, oh, just do this. I'm like, oh, yeah.
So Rob's around here, which very much comes in handy. So if you have one of those on your team, you might want to go by and drain yourself to say that, because you might need to help it. So you're running pivot tables bottom tabs on top of pivot tables and top pivot tables, but well, awesome. I think that this was a great conversation even having gone through these, having watched you present these to our clients, um, I'm even learning new things, just kind of, you know, continuing to.
Talk through it. And that's the point, right, is that you can continue conducting these analysis and you're going to continue learning new things and raising, you know, great insights for your colleagues, for the sales team, for the product team. And, you know, this is just kind of one more way that you can prevent your marketing team from being looked at purely as a call center and said, you know, position your company, your team as a strategic partner in the business and one that is bringing new information and new insights to the table. And that's what it's all about, right?
So awesome. Matt, any final words before we wrap it up? Yeah. Always have your business head on when you're doing the win-loss analysis.
Because it's always exactly right. You're doing this to elevate yourself beyond pretty pictures and emails. And it's more about like, hey, strategically, are we on the right track here? And let's let this analysis help guide that decision making.
And that's really, whenever I do a win-loss analysis, I'm always looking at it through that lens. Like, like, what do I know about this company and where they want to go? And is this win-loss analysis supporting that hypothesis as a company? Or is it flying in the face of it?
And then we need to ask ourselves very hard questions on the back end. Great stuff. Great stuff. Matt, thank you.
And for everyone that was listening today, thank you as well. Until next time. Peace.