No one needs perfect data

Do you really need perfect data to grow revenue?

Show Notes

Data quality. Clean data. Measure everything.

There's a lot of data available, and because it's very black and white, we tend to get stuck on the quality and cleanliness of the data. Can we even trust it?

We discuss why you don't need to chase perfect data to grow revenue - and at the same time when you really need to make sure you have solid data.

Creators and Guests

Host

Mikkel Plaehn

Marketing leader & b2b saas nerd

Host

Toni Hohlbein

2x exited CRO | 1x Founder | Podcast Host

What is The Revenue Formula?

This podcast is about scaling tech startups.

Hosted by Toni Hohlbein & Raul Porojan, together they look at the full funnel.

With a combined 20 years of experience in B2B SaaS and 3 exits, they discuss growing pains, challenges and opportunities they’ve faced. Whether you're working in RevOps, sales, operations, finance or marketing - if you care about revenue, you'll care about this podcast.

If there’s one thing they hate, it’s talk. We know, it’s a bit of an oxymoron. But execution and focus is the key - that’s why each episode is designed to give 1-2 very concrete takeaways.

[00:00:32] Mikkel: Yeah. I don't know. And we're gonna talk about one of my very, very, very strong suits: data
[00:00:45] Toni: Okay. yes, data. We're gonna talk about data. and we have some potentially different takes on this than, maybe many other folks. and I think really our approach is just be a bit more fricking pragmatic about the stuff.
[00:00:58] Mikkel: Yeah. I mean, everyone says they want to be data driven or are data driven, so we're gonna get a bit into that. And actually, the whole reason behind covering this subject is it's absolutely key if you want to be able to build a model at some point in time.
[00:01:13] Toni: Yeah. And, or if you just wanna run a good company.
[00:01:16] Right. It's kind of, both of these things are true. And I think there are multiple ways to use data. We're gonna go into this one of them. Sure. An operating model, which we obviously think is super important, but, many other reasons why. Data's important and, and some stumbling blocks in the way there.
[00:01:32] Mikkel: Yeah. So I, uncovered some pretty. good notes for us today. And I'm gonna thank you. I'm gonna use the first, the first one really, from the og Peter Drucker. And he has this very, very, very famous saying that, you can't manage what you can't measure. And I kind of said, I really wanna.
[00:01:54] Start pulling that one a bit apart
[00:01:55] Toni: Okay. Sure. You start
[00:01:57] Mikkel: well, okay. I can do that. It was kind of a tee up for you, but that's that's totally fine. So the, the thing is there are things you can measure.
[00:02:05] Toni: Yeah.
[00:02:06] Mikkel: And there are things you can't. And does that then mean you can't manage it? No.
[00:02:10] Doesn't mean you shouldn't do the things you can't measure. No. It really doesn't. Right.
[00:02:15] Toni: No, that's right. I think in principle and for the 80, 90% use cases or situations, I think it's still a really solid advice. You know, measuring the staff that you want to manage. And then there are things, where it's a little bit more difficult, especially our dear marketing friends kind of.
[00:02:32] Talk about this all the time. And, and you know, my, my, my way of talking about that thought by the way, is it's usually this demand, Jan, hey, we are kind of running ads somewhere. There's no direct link between those two, but our direct, direct traffic and our branded search goes up. So there must be a connection here, summer between the money we deployed and, and the, the outcome that we're seeing here.
[00:02:53] for me, it.
[00:02:54] you know,
[00:02:54] Again, I don't think you can, connect those two things causaly and logically fully all the time. So that is kind of the, hey, you can't measure this thing. But I kind of see it as, think about air 100 years ago or 200, I don't know, air was around. Everyone needed air. if it wasn't there, Everyone is dead.
[00:03:15] Yeah. but no one could measure. No one could be like, Oh, you know, I can, I exactly know how much air is in front of me or whatever. that was only figured out later. and, and that basically for me means all this demand and stuff, Don't treat it like air, but, you know, have the met, you know, the, the metaphor in mind that, you know, maybe eventually we'll be able to, to measure it, and then we will probably fully know that there's a connection between those two.
[00:03:37] Mikkel: Yeah. And I guess the, question is then really, there are so many things you can measure.
[00:03:44] Toni: Yeah.
[00:03:44] Mikkel: What really matters? What should you be measuring as a business? because you have data for everything.
[00:03:49] Toni: Yeah. Well, I. You should from a, I mean obviously you should manage and measure your cash in the bank account and your cash flow and, you know, let's skip over these things, Kind of the finances you should obviously kind of have on a, a good control and, and usually you end up having that because there are laws governing this, so you can't just not have that managed well
[00:04:10] Mikkel: winging it.
[00:04:10] Toni: Yeah. and, and really then the other side is, let's just say product and your funnel. I don't think we will deep dive into the product so much today. also don't think we are massive experts in that area specifically, but, you know, let's just say you wanna measure what's going on on your commercial site, right?
[00:04:27] And there you really have, you know, the funnel itself, how that's performing. you have the, the, the micro pieces, meaning. you know, sales reps and campaigns and, and projects maybe that are running, you want to probably measure those. usually for performance management reasons, right? Hey, is this, person working out?
[00:04:46] Is this campaign working out and so forth. and I think, you know, in addition then to, you know, the micro, then you have to finalize a macro, and then you probably wanna have efficiency pieces around it as well, right? And those efficiency pieces then, are basically, they're called unit economics. So, you know, c payback, customer acquisition, cost payback, that's usually something that you wanna measure.
[00:05:09] And, you know, if we take this as an example, the question there, then you really, how deep do you want to go with that?, because everyone, everyone on this planet can measure, c payback. It's really not that hard. and simply because, Both of these numbers are finance driven. Finance usually has their, you know, their shit order.
[00:05:29] and basically it is the cost that you spend on sales and marketing in a quarter, and the revenue that you newly acquired in that quarter. You kind of put those two into a ratio and boom, you have your customer acquisition costs payback, where it gets tricky. Well, what if I wanna know, you know, us versus emea. What if I wanna know, inbound versus outbound?
[00:05:52] And in order to take that next step, which you really need to in order to. Be able to improve your C payback, you know, just randomly cutting across the board. We're just leading to randomly reducing your revenue. So you really need to kind of peel back the onion, just one more step in order to figure out, well, which channels are.
[00:06:12] Not working well, which you knows are working well. And really, I think unit economics and c payback and, you know, lifetime value and all of these fancy metrics bringing both the final side and the final side together. I think that's kind of the, the master class of, of measuring and, and then what you can use data for.
[00:06:28] Mikkel: I mean, we could almost do an entire episode on the, the metric that matter. I think that's, that's for another time. one of the things that keep coming up,
[00:06:37] that
[00:06:38] I think we should be addressing is clean data. This is something that surfaces again and again and again.
[00:06:43] And I know this because I have, you know, in the communities I'm in on LinkedIn, it seems to be a recurring topic. So I wanted to dive in a bit on this one. Is it really important to have clean data and is the issue really that big?
[00:06:56] Toni: So, and this might be, you know, some people might be thinking this is controversial. I, I don't think it's all super important to super clean data. I think they are probably different use cases.
[00:07:07] For some, you want to have, you wanna be very certain that the number that you are talking about is correct, and then you have other use cases where it's totally fine that you have 80, 90%, correctness. And by the way, 80, 90%, that's, you know, everyone is there. You know, I, I haven't, I haven't found someone that is, you know, far off from that measure.
[00:07:30] And, and the reason why I know is, you know, on the, on the one inside, I have never met anyone that had perfect data. Or that even, you know, claim to have perfect data. I have met a bunch of people that said they have terrible data. but you know, really looking into this and, you know, seeing kind of how you can still use it.
[00:07:48] There was no one ever that we couldn't work with because the data was too shit. Right. And that kind of tells me that there's a bit of a double standard going on in, in the community about, you know, what perfect data means and what you really actually need in order to, to run a good business. And perfect data for me means, everything is a hundred percent across the board all the time.
[00:08:09] every single piece is synced across multiple, tools perfectly. You have, you know, maybe you have a, so, a single source of truth in, in Salesforce. Some people might be laughing about that. Yes. And maybe then you have a, a cdp, a customer data platform where that maybe is the case or built something in between and so forth.
[00:08:28] Massive amount of work for, you know, what's the output potentially. well, you know, even for high level tasks, you might end up with like near perfect data. But do you really need that? You know, you need that, And we're gonna get into this a little bit. You need this for purposes, like, you know, letting go of someone.
[00:08:46] Yeah. You know, you sit down with a rep, you say, Hey, you made so many calls, you only booked so many opportunities. We told you five times. And, and now's the end of
[00:08:56] Mikkel: the
[00:08:56] Toni: the rope. And then you know what's really, and you know, that happened to me as well. What's really terrible is then the, the rep on there said, Well, but that number's wrong.
[00:09:05] Mikkel: Yeah,
[00:09:05] Toni: I booked actually nine and before that I booked 10. And you know, now he let me go this, you know. That is a problem that you need to avoid, but do you really need to know on a team level of, let's just say, let's stay in the, in the argument of an outbound team or SDRs, do you really need to know on a team level that it was a 110 or 115, Do you really need to know on. You know, a VP level, whether or not the VP marketing in HubSpot says 261 M QLS and the VP sales and Salesforce only sees 259 M qls. It doesn't matter. It simply doesn't matter. And then, you know, having those, all of those things line up, that would be a hundred percent right.
[00:09:48] I totally would agree with that. but it doesn't matter for most of the conversations, that basically all of us are having every single day.
[00:09:57] Mikkel: Yeah. So I think the point is really if I, I think you had an example of if you're running a quarterly business review with a team and you're presenting a. He goes, So this is how we did.
[00:10:07] and whoever you're running the QBR with goes, Well, that's not the number I have. You will in most cases find that it's the same kind of trajectory they're on, so don't get fussed about, you know, that, that slide variance. So what I think..
[00:10:21] Toni: Sorry, sorry to interrupt you. I think it goes even a little bit further than that. I think there's even a little bit of a, evasive maneuver in there, by, by those execs that basically are trying to throw you off or throw the conversation off by pointing out those things.
[00:10:36] And it usually works really great. It's like, Hey, this number isn't right, and you say, Then the first three slides of the, the qbr and suddenly everyone is like, Wow. If those numbers aren't right, then we probably can skip the QBR because you know, what, what insights will there be?, and I think number one is very quickly when that happens and it will happen to you, there's just no, it will happen to you, is to basically shoot it down, and, and focus on, first of all, the.
[00:11:02] What's the difference really? You know, what are you having, what are we having? If there's a 50% gap, you have a problem, right? You, you have a problem and there's probably no way around that. if the gap is, you know, 10, 15% or smaller than that, then just skip. Usually what you will find is that the trend will be the same.
[00:11:18] Mikkel: Yeah.
[00:11:19] Toni: Right. And then you know how you know, especially the VPs or the execs that know that they will come under fire in this QBR and, you know, I'm not a fan of Ambushing or something like that, but you know, they, they might, they might.
[00:11:33] Ask some questions about the validity of the argument, and my, my reply back is then, well, is your data also showing that you're declining by 20%? Yes. Well, you know, then we should discuss that. Whether or not, you know, this is 5% plus minus on either side, doesn't matter. The trend is still minus 20%, and I think we all. That, that's really the problem here, right?
[00:11:53] And then you kind of overcome this, you know, Oh, you know, the data is the problem.
[00:11:59] Mikkel: So, the other thing I heard, Dave Kellogg talk about is the, most contentious QBR. It's usually the marketing one, and it's because there's so much data you can pull in and you need to kind of find a balance for what to then focus on as to, to your point, right?
[00:12:17] If you're off by 20%, you're off. And you need to find some very clear points where this is the focus. And I've been in this scenario quite, you know, in the past, working with a data analyst or a data scientist really digging into a problem and keep on going. Until you almost get to a point where, you know, the data doesn't make sense anymore.
[00:12:37] The, you know, data analyst knows it. So when, when should you start pushing back? If you're sitting in, in revenue operations or in in the data team, when should you start saying,
[00:12:46] Okay, whoa, whoa, whoa,
[00:12:47] Let's, let's slow down here now.
[00:12:49] Toni: Yeah. I think there's a difference between. One of deep dives and, you know, recurring, we're gonna look at those numbers.
[00:12:56] And I think the reason why Dave is saying that, the marketing qbr and B, those meetings are terrifying. He, he meant it predominantly from a CEO founder perspective
[00:13:06] Toni: because it's like all of those numbers and I don't know all of those numbers that I don't know what's important. And he basically kind of cut it down, was like, Hey, just did they create pipeline? Yes or no?
[00:13:15] Mikkel: yeah. That's all I want to know.
[00:13:17] Toni: That's really the question here. for, for other purposes though, I think the recurring meetings should be centered around, pieces of data. You could call them metrics that are leading towards revenue. That's how I would kind of look at this. So what would that be? It could be airs for some teams.
[00:13:38] It could be traffic on your website.
[00:13:40] Is that traffic number going up? is is the right quality of traffic going up? You know, is branded search direct going up or is paid social going up, whatever. So this, this, this is an important piece. If, if, especially if you're smb, you will kind of look at this a lot.
[00:13:56] Because you will probably look a lot between traffic and conversion and you will have conversion rate optimization going on and so forth. So that number needs to go up, otherwise the leads won't go up. Right? If you're a bit more mid-market enterprise, you know, we'll start looking more into leads and then, you know, why do you look at leads?
[00:14:13] Well, because leads is highly indicative of how many opportunities you will get. By the way, pro. Separate, handraiser leads. So demo request trials, quote, request from non handraisers, which are, you know, webinars, white papers and so forth. Focus on these things and, you know, stay at first at the, volume metric level.
[00:14:35] How much traffic, how many leads, how many opportunities broken down into the regions. Broken into, some of the different streams and use, processing steps, for example, conversionrates, or lead time between those stages and later on in the opportunity stages, acv. So average contract value, use them as, as a second order, to explain some of the issues that are going on.
[00:14:57] Otherwise, you will confuse everyone. Focus on the volume stuff. And then, you know, as a, as a next layer, peel back the audience and say, The reason why we are behind here is because not the volume piece, one level app is broken, but the processing between those is broken.
[00:15:11] Mikkel: Right? Yeah.
[00:15:12] And I think one of the points you made, recently was, So yes, you need to focus on revenue, but that happens very late. Usually. And you need to have an indicator, a step before that where you can start seeing ohoh or we are, we're trailing off costs here. Let's, let's now go and do something.
[00:15:29] Toni: So I think a lot of folks talk about, hey, you know, lagging indicators, leading indicators, and, and I know, and you know, I listen to this and say, Okay, cool, but in the end, revenue matters. Right?
[00:15:40] the, the way, the way I would try and have everyone kind of think differently about the leading indicator piece is you see something going off on the leading indicator side, you still have time before it hits revenue before everyone sees you screwed up. That's, that's how I see it. And, in, in some cases you might have three to six month time of either fixing it or preparing the organization that something is not gonna work out.
[00:16:08], recently talked to a, VP sales like medium company. and he was walking into Q4 and basically had to tell the organization that they're not gonna hit Q4 because he, he already knew, right? So he was in q3, he saw the opportunities and, you know, Q2 was soft, Q3 was a disaster. So what do you do with the gap?
[00:16:27] You put it on q4, but obviously q3, really weak opportunity generation. And then you walk into Q4 and maybe you can get decent Q4 normal ways, but not, not in this one, right? And, and those are the leading indicators that he should be leaning into in order. Fix and course correct. Without anyone noticing, which is fantastic.
[00:16:46] Or, you know, preparing the organization, Hey, there's, you know, maybe we don't need to hire that many sales reps.
[00:16:51] Mikkel: So this is where there's something you can measure and you can effectively manage it at the end of the day.
[00:16:56] Toni: No, exactly. And I also think, you know, we are talking about data and data quality.
[00:17:01] I think there's one step before that actually, which. Yeah. You know, do you, do you need to measure all of that stuff? Do you need to collect, you know, all of those pieces of information? Many times especially and, you know, we, we have this theme of, Hey, Revs ditch the tool talk many times our field days, Oh wow.
[00:17:21] We have the Salesforce thing. We can measure everything and anything, and now we go off and try and achieve. And let's start a big war with the AEs and the sds, you know, that they need to put every detail in and we can maybe measure it. And, and, and the, the, the result is, first of all, they're not gonna put it in.
[00:17:39] So that's an issue right there. And, and second of all, even if they did, would you really be able to, you know, pull something useful out of that? That, that's really my question. And, and many times you can actually probably, Half of the stuff that you wanna look at. and the way I would approach it is what do you, what do you want to use it for?
[00:18:01] If you don't have a good answer to that, skip it.
[00:18:03] Mikkel: Yeah.
[00:18:04] Toni: And the, the, the other way around, which is the, I'm falling in love with the data approach, which is let just measure everything stored and then we are gonna look back and, you know, see patterns and, and, and, and all exciting stuff. I was part of that camp for a really long time.
[00:18:19] We measured everything. We started, and guess what? We never looked at it. We never looked at it. We never went back and was like, Ooh, let's look into those. call starts from two years ago of that sdr. No, no one cares about any of that stuff two weeks after it's over. So really be purposeful in the data that you collect.
[00:18:37] Then it's also, first of all, less data in general, but also easier to maintain, easier to get to those 80, 90, maybe even a hundred percent of, of data quality. And then, really use that for a purpose that ideally in our mind should be revenue driving. As a revenue operations professional.
[00:18:55] Mikkel: I think sometimes also, so there's two ways you can take this clean data conversation.
[00:19:00] At the end of the day, there's the, you know, reporting insights, trends piece. There's also, we wanna automate things and we do in fact need somewhat clean data in order to do So, If you had a close one and you wanna try and resurface them over time. And so I think there's the, tactical side that probably also takes up a lot of mental sp, you know, capacity, but those are tactics.
[00:19:27] Toni: I think you're right though. I think for some of these things, you simply need better data in order to try and create a process and automate something like that. And, we had, we had, I forgot the, the specific example of we had something around churn and customers and we wanted to use some of the data to maybe even, you know, send emails automatically and.
[00:19:51] Then we realized, hey, we, this is so high stakes to send an email like that to a customer and we don't feel comfortable sending something like that out unless we know 99% that the data's correct. So there are a couple of things, and you're right on the automation side where you wanna have perfect data.
[00:20:10] But that does fall into my way of describing him in terms of purpose, right? If you have strong purpose, cool. Go. Let's do that. And, and again, I recently saw a post, Some rev ops, li influencer, you know, someone.
[00:20:23] Not so, not myself. I was kind of talking about, hey, you know, don't start a rev op project unless blank, and then everyone should fill in, right?
[00:20:32] And, and it was so hilarious. It was, I don't know, 30, 50, I was jealous, but 50 comments or something like that. And everyone was like, alignment and, you know, you need to kind of have buy in and these kind of things. I was the only one saying, revenue impact. Yeah. don't start the epic project if there's no revenue impact.
[00:20:54], and I think this, this is the same approach you should probably have with your data. if there's, if you, if you can't see how to cut costs and, you know, cutting costs, I usually see this as you can deploy the cost somewhere else and maybe generate more cash from that, or if it, you know, it helps in other ways to generate revenue, then consider maybe not doing it.
[00:21:13] Mikkel: Yeah. So what I'm thinking is we've, we've talked a bit about some of the cases, briefly where you, where you need Perfect data.
[00:21:25] And one of the things in the, the preparation was like, One of the places where we do need perfect data, obviously is gonna be in the board.
[00:21:34] When you talk with the board and you're like, Nope. Like actually no, you don't need, but, So can you elaborate why? Why is, why is that? I was a bit shocked to be honest.
[00:21:45] Toni: So first of all, maybe you, you explain why you, why you think it should be in the board.
[00:21:49] Mikkel: Well, I think, so conversations are gonna be, Hey, there's some proposals, there are some things we do need to discuss beyond just proposals.
[00:21:56] And for that discussion to be productive, we are gonna need some data. At the end of the day.
[00:22:01] Toni: Yeah. So the truth about boards, they're usually very much removed from the actual stuff that's going on. The financial data. They don't really care about hundreds of thousands of euros show on like a governance oversight way of, is the CEO spending it in the right way?
[00:22:24] But really what they're looking at is how much money is left on the bank account and how much more time and growth does that buy us? And that measures in the millions, not at the hundreds of thousands. and then when you go into funnel data, number one, sadly many people sitting on the board don't really fully get it, get it, and sometimes also don't fully care.
[00:22:47] I think there's a. There, there's a, there's a cool breed of, VCs that have operational operating backgrounds and then bring this in and that's helpful. And then there's a breed equally cool. I, by now even think even cooler, of VCs that don't have any operating background and they just realize I just stay out of it.
[00:23:05] I think that's a kind of good approach. And then on the, on the funnel data, number one, you know, how are they going to crosscheck that?
[00:23:16] Toni: you can give any number, my friend, any number. And they were like, Oh, well that looks like a big number. and then you move on. And then even worse, and I've been, I've been doing this myself sometimes, you might either change the metric that you show to completely confuse them, or even worse, you change the definition of the metric without letting anyone know.
[00:23:37] And, and that's why, you know, on the board level, usually you end up. Fairly fluffy numbers. I think everyone around the table understands that, some of that is simply due to difficulty collecting this in time. It's always a scramble, those bot meetings, and you need to send it out 48 hours before and it happens and, and stuff like that.
[00:23:56], and, and then there's also just, so little, let's just say a risk that some of this is wrong. I think where it does make a big difference. It's not when you're in the board, it's in the process of getting a new investor into the board. So when you go through a due diligence process, you usually have, depending on the size of the transaction, you have, you know, investment bankers.
[00:24:19] On the other side, you have, someone like pcg, McKinsey, Bain on the other side. you have, finance teams where there's clearly their career depends on this. On the other side, Yeah, they will, they will be very, very accurate. And it's like, why is this number different than the spreadsheet that you gave us yesterday?
[00:24:37] And, you know, how, why did it change? Tell us exactly why it changed. that is, that is, that's a whole different level. You know, that's a whole different level of a conversation. But usually in the bottom of directors and the reporting that's going on there usually very low fidelity.
[00:24:52] Mikkel: So when you go to the other side where you don't need as much. You know, accuracy in the numbers. One of the things we have, we've talked about is, building an operating model. Why is it you actually don't need precise data?
[00:25:08] Because don't you wanna be as certain as you can about being able to produce, whatever revenue you aim for?
[00:25:15] Toni: Yeah, sure. I mean, better is always better in that sense, right.
[00:25:20] I think there, there are two approaches. One, You know, what do you really wanna get out of it and what can give you that information without needing all the details? So one thing that we have actually discovered is you don't need to know, all the specific, MQL definitions and, you know, opportunity.
[00:25:38] You know what is where, when in the stages and the funnel and all of that stuff. What you need is the pillars of your funnel. And depending on where you start, the pillars. traffic on Google Analytics, which is, you know, being outlawed in, in Europe apparently. you have unique users or something like that.
[00:25:58] think it's called. You know what, you can't change that definition. You, you cannot.
[00:26:11] Toni: So it's, the same for lead created. and the lead creation might still have Hazarded demo. Is it a, is it a, white paper? Is it a webinar? can't really screw with the lead creation.
[00:26:22] Mikkel: Yeah.
[00:26:22] Toni: Because again, all of those are system fields. You will have a lot of fun playing around with the MQL stuff. but I'll get to that in a second. You can't screw around much with the opportunity creation in Salesforce the date stamp and all of that stuff. You can't, again, you will have, attribution pretty quickly on outbound, inbound and so forth.
[00:26:40] That's really then important. And then you, I, I suppose you could probably screw around with the, opening closed one definition in Salesforce. I. Seen anyone yet doing that though, it's like it's close to one when there's a signature and or when there's a PO or we've got a verbal, you know, that kind of stuff.
[00:27:00] But not all. This means it now progresses to next stage or something. It's, it's usually not that. And then the last step of your funnel is, is revenue. And revenue by the default is something, you know, people have different definitions of ARR and churn and how you, you know, calculate that stuff. But at the end of the day, it's your money in the bank account.
[00:27:20] and, it's to a degree, derivative of that is, you know, what you're putting on your profit and loss statement.
[00:27:27] Usually people have this under control, right?, so if, if those are your pillars, then now, you know, filling it in between, you might have an mql. and the MQL piece, might just indicate some things, but it's really just a reporting on the lead stage because really what you're talking now about is.
[00:27:43] You know, lead to op conversion rate that is fixed because lead creation, opportunity creation, if you now insert a fluffy MQL piece in the middle, you basically have, a drop off conversion rate from lead to MQL and then MQL to op. If you redefine the mql, you really just changing the conversion rates between lead to MQL, MQL to opp, and you know, the list goes on for, for tweaks like that. And, and then really the important piece.
[00:28:09] Which everyone has under control are the different, we call it dimensions. So the segments that are important to you, which might be, the different markets you're operating on, which might be, inbound, outbound partnerships and right? So whatever is important for you as an organization, what we found is also what you have managed kind of nicely, in your CRMs.
[00:28:30] Mikkel: Yeah, so I guess the point is there's, there's certain areas where. You just can't mess it up. It what, what is, what number is produced? You can, you can believe in, you can actually use it and that will get you far enough At the end of the day. So, so don't get too fus about, data quality. don't overwhelm yourself with hundreds of, and hundreds and hundreds of data points. it's back to the purpose as you said. What is it you are trying to achieve? and then go and, do it.
[00:29:00] Toni: And be pragmatic about it. And, you know, does, does getting from 90 to a hundred percent, does that change the impact on revenue?
[00:29:07] If that is true for you and your organization, go and spend that time. If it's not true for you and your organization, then don't spend the time, spend the time on something else. Yeah.
[00:29:16] Something that drives revenue. Wonderful lies.
[00:29:21] This was a bit technical actually. Wow. I didn't know I had it still in me, Mikkel.
[00:29:25] Mikkel: Yeah, it's been a while. But it was nice. And we have, you know, a new sign kind of illuminating our studio, which is wonderful.