4 Steps to create data trust

"I don't have that number!"... "where did you get that data from?".. Ugh, so many objections to data, and the worst part? You get stuck chasing data perfection (which is an endless endeavour). Instead, follow this simple framework to create data trust.

And the best part? It's self validating over time.

In the episode, we discuss:

• The problem with data (02:19)
• Biases that break data (04:00)
• How to build data trust (10:24)
• First step: Go on a data diet (11:18)
• Establish accountability for the numbers (17:45)
• Pressure test the system (20:52)
• Monitoring the data (22:42)
• Expanding the data (25:31)
• Wrapping up (31:03)

PS: No joke. Write a long review and get a book. Send a screenshot to [e-mail]

Creators & Guests

Host

Mikkel Plaehn

Head of Demand at Growblocks

Host

Toni Hohlbein

CEO & Co-founder at Growblocks

What is The Revenue Formula?

This podcast is about scaling tech startups.

Hosted by Toni Hohlbein & Mikkel Plaehn, 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.

[00:00:00] Toni: Hey everyone, this is Toni Holbein. You are listening to the Revenue Formula. In today's episode, we are going to talk about four. Awesome steps to take you from. Hey, we can't trust this data to data trust established. Enjoy. Okay.
[00:00:22] Hey, that was the intro.
[00:00:22] Mikkel: Yeah. So the thing is
[00:00:25] Toni: is,
[00:00:26] Mikkel: this one recording
[00:00:27] Toni: on this other thing? Yeah, yeah, yeah, yeah,
[00:00:28] sure. We're
[00:00:29] Mikkel: recording everywhere and the thing is, it started messing a bit with me ever since. Uh,
[00:00:35] Toni: Which of the 20 cameras that are recording here is, is the one that's messing with you?Tell me
[00:00:40] Mikkel: Well, it's actually the broadcast ever since it kind of decided to do a factory reset, the button to play the music used to be here and now it's here.
[00:00:49] Toni: It's also a different color.
[00:00:50] Mikkel: Yeah, exactly. So it's It's all wrong. It's all wrong. It's not even a Monday. You
[00:00:55] Toni: Do you know what? And let's buy another converter here because that's the only thing we can solve
[00:00:59] Mikkel: Let's get a backup broadcaster. Yeah, I think that's the solution.
[00:01:02] Toni: think you should you should educate everyone. There's actually not a broadcaster's actually,
[00:01:06] Mikkel: Hello,
[00:01:08] Toni: ER,
[00:01:09] Mikkel: roll caster. It's all this fancy equipment. I thought you were gonna take it in a different direction, but that's totally okay. That's totally okay. Uh, we'll collect the data and decide from there.
[00:01:19] Toni: everyone listening is waiting for the brilliant bridge that
[00:01:23] Mikkel: It was right there. You just blocked it. I was saying we are gonna collect all the data
[00:01:27] Toni: Oh.
[00:01:28] Mikkel: and hopefully we can make a decision given that we trust it.
[00:01:30] Toni: it.
[00:01:32] Mikkel: It's become a thing now. Terrible segues. This is like trademark of the show view. Yeah,
[00:01:39] Toni: I think it's you.
[00:01:40] Mikkel: It's me. Okay. I'm a trademark of the show. Ah, okay.
[00:01:44] Fair enough. Fair enough. But anyway, we are gonna talk about data today. We've talked about it
[00:01:49] many times before. Yeah.
[00:01:51] Not at all dry.
[00:01:52] Toni: Let's talk more about data. Please.
[00:01:54] Mikkel: we promise you listener. It's not gonna be dry. It's actually gonna be number one actionable. Not the data, but the conversation here and what comes out of it. And it is in fact gonna be interesting.
[00:02:03] Uh, we've talked about data quite a few times. It's a big part of revenue operations of really making the right decisions. But there are a couple of challenges with the data. And I think we should start delving into that piece first.
[00:02:19] Toni: The first challenge is, uh, bad. It's
[00:02:21] Mikkel: bad data. It's bad.
[00:02:23] Toni: bad data, uh,
[00:02:24] Mikkel: It's so mean and rude.
[00:02:26] Data quality
[00:02:27] Toni: and all of that stuff. Um, and it's being thrown around most of the time, right? It's, um, Data quality as an issue is, you know, when we talk to, to customers or prospects, you know, data issue always comes up. Yeah. It's always like, I can't do any of these things because my data, you know, doesn't work out.
[00:02:44] Um, and then we kind of look into this and we, we usually, we usually see that everyone is so indoctrinated because they've been slapped so many times that. You know, uh, your data is bad that they're kind of running around and always like, yeah, I know, I know my beta data is bad. It's bad. So, and it's actually not true, uh, in many cases.
[00:03:02] And, you know, sometimes we will, you know, taking through this. I think some of that we will actually touch up on later. and the, the reason why this is, you know, to largely be difficult to solve is because, Data quality as a problem is, is infinitely, yeah. Infinitely large. Right. Um, more on this in a bit.
[00:03:18] and then, you know, um, when it's, when it's really in a more applicable format, it's when you either have a report or when you have a QBR or when you, um, do an analysis or when you, you know, maybe even do something that someone doesn't like. Mm-hmm. Um, then it's like, where did you get this number from?
[00:03:38] Yeah. I see. I see a different number on my spreadsheet. If you have siloed ops. Yeah.
[00:03:44] Mikkel: Yeah.
[00:03:44] Toni: By the way, Then, uh, then, then the, the next thing is like, uh, my ops person
[00:03:50] Mikkel: Yeah, yeah, yeah.
[00:03:50] Toni: Sees a different number. Yeah. Uh, and actually it makes the analysis go green instead of red. So, you know, it's super, you know, basically enough what's happening is data's being opinionated.
[00:04:00] Yeah. Uh, basically, and that's a problem. And then you have a bunch of just human, uh, fallacies, uh, also, you know, in the mix. Right? So what is that? Um, recency bias. Yeah. Basically, you know, sometimes I call it, it's a last touch attribution.
[00:04:16] Mikkel: Yeah.
[00:04:18] Toni: It's the last piece of information that you received. Um, that's going to be the, the, the thing that you model the future or your future expectations around.
[00:04:27] Um, and then, uh, a really good one is confirmation bias. Yeah. And to a degree you almost can't fault it, but confirmation bias really means is, okay, I want to go, uh, to the left. Yeah. And now I'm only looking at data that, confirms that I should be going to the left. If I see data that says, actually you should go the other direction.
[00:04:50] I'm like, ah, you know, I don't trust this. I don't think we can trust this. You know, let's rather cherry pick this one piece here that would help me on the other side. And based kind of making these kinds of. Uh, you know, tricks. Yeah. Uh, work in order to just confirm what you really want to hear.
[00:05:05] Mikkel: I mean, I use confirmation bias all the time when it's anything to do with budget or salary negotiation on my behalf.
[00:05:11] It's like, you know, you wanna find that confirmation.
[00:05:14] Toni: Yeah. I usually, I usually help you to go the other way then. Um, but I know for example, those are, those are, those are things and you could. To a degree you could throw in groupthink, you could, you know, throw in a couple of other things. So groupthink is really the, uh, that there's a consensus building in the team.
[00:05:31] And, uh, no one is, uh, trying to argue even against it because there's so much force pulling you in one direction, which then leads you into completely crazy land. But
[00:05:40] Mikkel: But you know what's also really funny about data? Because it's so binary, it's considered the truth. When you make real world decisions without data, you gather some of the facts and have to assess, how much can I trust this piece of information? Then you end up making a decision, and somehow in those situations, often we just accept it.
[00:05:57] Right. But as soon as you have data, the whole thing kind of changes because it's supposedly supposed to. Uh,
[00:06:02] Toni: Yeah. I also think there's just been an industry of 20, 30 years of, hey, data driven.
[00:06:07] That's the only way forward. And, you know, data is the one thing you can really trust because it's, you know, not opinionated, it's not biased and. Uh, the, the, the complicated truth is kind of, is also, you know, it's, uh, you know, sometimes how even slice and dice the data, how you, the meaning that you give to it and so forth, right?
[00:06:25] It's, it's part of the story. So that's why, that's why I think, um, uh, seeing data as the end all be all for everything, I think that's also pretty stupid. Yeah. I think it's a mix. Uh, but if you use this instrument called data, Then, you know, ideally try and approach it in the most neutral and, you know what, intellectually honest way.
[00:06:44] Yeah. You know, that's, that's maybe kind of the better way to say it.
[00:06:47] Mikkel: Mm-hmm.
[00:06:48] Toni: So this is all the, the, the, the problem around bad data and uh, uh, and, and bad data quality. And what does it actually lead to while it leads to, uh, folks not trusting data? Yeah. You know, this is really the kind of the, the end result.
[00:07:01] And when you don't trust data, especially in high stakes situations, What's gonna happen is you simply won't lean on it.
[00:07:08] Mikkel: No.
[00:07:09] Toni: Yeah, it's, it's kind of cool when you, you know, see data on a dashboard and it's like, oh yeah, woo, that's interesting. Uh, but now basically put, you know, your career on the line for this number to be correct.
[00:07:22] It
[00:07:22] increases the stakes quite a bit. Um, and then if there's not enough data, uh, trust in it, then it's like, you know what, I, I see the number going up, Michel, I see it, I understand it, but, uh, But it's, you know, maybe it's not enough evidence or something like that, or I'm not still not sure where this is coming from and is it really the right thing and so forth.
[00:07:41] Right. Um, and, and this is then basically the reason why, uh, why people then end up not using data for, uh, decision
[00:07:48] Mikkel: It's like you have this hammer in your toolbox, but you don't really trust it because it got hurt once and then use a saw instead and completely breaks.
[00:07:55] Toni: Yeah, I mean, it's, it's a little bit, so I was joking about this, so this is maybe.
[00:07:59] Uh, it was a popular TV show in Germany, I don't know, 25 years ago.
[00:08:03] Mikkel: Oh, we're going back. Yeah, go on. It's like
[00:08:05] Takeshis
[00:08:05] Toni: Castle. Is that something that, you know,
[00:08:07] Mikkel: oh, is that the, is that the Japanese show? Yeah, yeah, I know it. Yeah, Yeah, yeah,
[00:08:11] yeah.
[00:08:11] Toni: like, uh, game show. And they had like one game where there's like this serene lake, with, uh, stones.
[00:08:19] Yeah. And you need to, you know, jump from stone to stone to stone to kind of get to the other side. Uh, yeah. Well, true. the, the thing is though, uh, and you couldn't judge this, obviously some of those stones were solid, some of them weren't. Yeah. Right. So you, you couldn't know which, which would actually support you and which wouldn't.
[00:08:35] And it's a little bit the same here. It's like some of the data stones are kind of solid, some of them
[00:08:40] Mikkel: Yeah.
[00:08:40] Toni: And if you then jump on it, boom, you're in water, you're out of the game show. Um, and I think this is, this is, you know, fundamentally what people are really kind of struggling with. Right. And kind of, I think another, uh, you know, angle to take or kind of to, to, you know, go about it.
[00:08:53] Right. So you don't trust the data. You start, uh, you know, second guessing it and, you know, kind of push a little bit. And especially if someone is trying to disprove you or challenge your beliefs and, you know, going against your confirmation bias and, and all of that pull that pulls you in one direction.
[00:09:09] If someone wants to change that, um, the first thing that's gonna happen in everyone's mind is basically this typical, you know, so this, I don't know, some. Law and Order kind of TV show on, uh, okay. There's a trial, there's a witness and you know, whoever site the witnesses for the other side is basically gonna go in and, and try and discredit
[00:09:31] the witness. Yeah.
[00:09:32] Right. It's like, ooh, we know that person lied once,
[00:09:35] knows? Might lie about this right now as well. Um, and basically this is then the, the other way of, uh, how to kick this. Witness in case you didn't capture it. That's the data to kick this aside, especially saying, oh, I can't trust it. Right. Kind of, you know, what's wrong runs, uh, is gonna be wrong again.
[00:09:53] Um, and uh, that's, that's how people kind of will then probably kind of push against that. And then if you then try and, you know, try and win that argument, you probably won't because. Yeah, your data is wrong in many, many, many places. Um, and, and since it's kind of one large thing, it's basically gonna be like, well, but this data point over here in the corner that we are not talking about and haven't ever talked about.
[00:10:15] But it's wrong. And therefore I can deduct that. Maybe this one is also wrong.
[00:10:20] right.
[00:10:21] That's how this works. And you can't win this game. You simply cannot.
[00:10:24] so how do you get out of
[00:10:26] Mikkel: Yeah, I
[00:10:27] don't know, Really
[00:10:28] Toni: what should you do? Um, stop measuring. Yeah. Just, uh, you know, got, yeah,
[00:10:32] Mikkel: yeah. No, but there, there's the saying, you know, if we have data, let's go with data.
[00:10:36] If we have opinions, let's go with mine.
[00:10:38] Toni: Yeah. Who was, that was
[00:10:40] Mikkel: Yeah, I can't remember actually. I
[00:10:41] Toni: think the Good Data CEO or something like
[00:10:43] Mikkel: Yeah. We'll put it in the credits if we find it.
[00:10:45] Toni: maybe. so what we think, uh, you should be considering doing, um, and it's a bit of a mouthful, um, but we'll, we'll take you through this, but basically what we are thinking about is.
[00:10:57] A system of self-validation, creating data trust, right? So creating data trust through a system of self-validation. Maybe that would be easier to say it like that Mikkel going forward. I'll put like a, like a little exclamation point here, but, uh, so what are, what are, what are these points really, right? So I think, in order to get to data trust, what are the different steps you would need to go through,
[00:11:18] Right? I think number one, um,
[00:11:22] Mikkel: uh,
[00:11:22] Toni: Data diet, and we can, we can go the nutrition route, we can also go the, you know, crawl, walk, run kind of route. Yeah. Um, but try and limit what you're looking at. Yeah. And, um, I think instinctively this is what. People are doing already, everyone who needs to put a lot of pressure on the data points.
[00:11:41] That's kind of what they're doing. It's like, okay, I trust the opportunity object. Okay, I trust kind of the MQL thing I trust, uh, closed won stuff. Um, that's usually, by the way, then how the conversation goes. Well, I trust the people that actually paid us. Uh, you know, that's, that's a trustworthy data point. And the, uh, the idea here is to basically, instead of looking at every single piece of data that you could, you know, think of. Try and limit yourself to, I would say five for your funnel.
[00:12:10] five simple steps.
[00:12:12] And this could include, you know, uh, maybe mql, maybe s sql, uh, your opportunity, you know, close, close one opportunity of course.
[00:12:22] could be something obviously on the renewal upsell side and so forth, right? Yeah. But take five.
[00:12:27] Mikkel: So core steps in the funnel,
[00:12:28] Toni: Yes. Yeah. Um, Take five of those, um, and say, okay, these, these are the items, those are the steps in the funnel that we trust. Yeah. Uh, you know, you can almost imagine like a little.
[00:12:39] Uh, Twitter validated checkmark that you couldn't buy, um, that kind of sits behind those. Um, and then th those, those are the four or five that you trust instinctively, right? And, and you will have this already. Right now, I can promise you that. I can tell you that the CMO will look at this MQL thing and you will trust that thing.
[00:12:56] You know, and someone on the inside sales side will look at the opportunity count that they created and they'll trust this one thing. So there's already some of these kind of pieces already built in, uh, where this then, you know, becomes more so useful. But a little bit more tricky is you wanna obviously, uh, okay, this is the us this is the EMEA right?
[00:13:13] Kind of. Goes super soft on how many dimensions you want to add to this whole thing. Keep it super simple, right? So now that you have those volume steps that you can trust and super crosscheck and you know, I see 251 here and I see 251 there
[00:13:27] and I'm gonna pay commission on 251 to you, right? Kind of really to have that simplicity.
[00:13:33] Now the next thing you kind of need to do is to, um, uh, connect these with one another through, um, agreed up on ways, right? And there are really three processing steps or processing metrics that, um, uh, we advocate for, um, one super easy, uh, average contract value.
[00:13:52] Mikkel: You
[00:13:52] Toni: You know, it's, I haven't seen many competing ideas how that should
[00:13:57] be calculated. Let's just say there's one. Um, the next one is, uh, sales cycles. Uh, so how many days does it take to go from one stage to the next? They also not saw so many ways to kind of think about it. Uh, you know, a simple one is just to take the average, yeah. A more complex one to take a distribution to kind of be a bit more, you know, but you know what?
[00:14:18] Take the average, that's it. Or the median, you know, one of those two, I don't care. One of those two. Same for the average, uh, contract value, actually. Um, the one where there's lot of. Uh, chatter around and sometimes confusions on conversion rate. Yeah, they're around five different ways you can calculate it.
[00:14:35] Uh, some of them make a lot of sense, some of them don't. there's a LinkedIn post too, actually for me. You know, that kind of goes through this a little bit. I don't wanna kind of bore everyone with this right now. Uh, but you would need to decide, yeah. What, what is the way we are kind of calculating the conversion rate between step one to step two.
[00:14:50] Yeah. Yeah. Um, and, uh, those, those calculations now, uh, they're derivatives of your trusted main, uh, data points. So by default they're trusted as well. Yeah. Right. That's kind of pretty cool. Uh, you start with five metrics and suddenly as you add the other pieces in, you're kind of at 15 or something like that.
[00:15:10] and that, that cloud of metrics is actually trusted by definition. Right. Then a couple of other pieces, how you can add. Trust to it is, uh, be very clear on the, uh, definition. So, uh, you know, it's not just in created opportunity. No. It's a, uh, meeting booked. Yeah. That was, I don't know, accepted and held already.
[00:15:31] You know, something like that. That is what we are kind of measuring here on the mql. It's, well, it needs to be in those geos. They need to have clicked this button. They need to have checked out the pricing page, whatever it is. Yeah. Be extremely clear on what that means. And then the other piece is, in our, I think in the data world and the actual data world, not our like commercial kids version of it.
[00:15:51] Um, they call it data lineage. Yeah. So where's that piece actually specifically coming from? Is it coming from Salesforce? Is it coming from kind of this field? Is it this filter and so forth? So you kind of wanna know that, uh, complications sometimes can be. Um, your data warehouse? Well, it's in the data warehouse.
[00:16:09] Okay. Well that doesn't tell me anything. Um, so then you need to understand what's the data lineage from data warehouse to then, you know, the, uh, the source and so forth, right? Yes. So this is really on the, on the, on the data diet. And because it's only, uh, really five metrics you need to kind of, uh, monitor and understand, you know, creating trust around those much easier Yeah.
[00:16:31] Than all the other stuff. Right?
[00:16:32] Mikkel: So what if you have a scenario where, You already have a bunch of metrics that you're using, maybe even reporting on.
[00:16:38] Toni: Yeah.
[00:16:39] Mikkel: But there's no trust. So are we really saying, well then consider data diet. Should you just remove all the other or put them to the side and then focus on the core?
[00:16:47] Toni: Yes. Uh, you know, you will still have them there for insights, monitoring reasons. Yeah. Um,
[00:16:52] Mikkel: you know, maybe
[00:16:53] Toni: Maybe for yourself, maybe you trust them, but not the others. So this is really kind of creating consensus on trust around kind of the core. And, you know, we'll get to adding more stuff back to it, right? This is where this crawl, walk, run analogy works a little bit better, right?
[00:17:06] Start by crawling, uh, just a, just a few pieces and then later on you can always add,
[00:17:11] Mikkel: Yeah, yeah,
[00:17:12] Toni: yeah. but again, what you don't, what you really don't want to have happen is, you know, you, you know, do a project. It's like, hey, There's our data quality, shit lake.
[00:17:21] Mikkel: Mm-hmm.
[00:17:23] Toni: And, and you wanna, uh, you know, create this nice clean pool over here of stuff you can trust.
[00:17:30] What you really wanna avoid is that, that trust also gets eroded suddenly. Yeah.
[00:17:34] Mikkel: Yeah. It's like the first five stones in Takeshis Castle. You can, you can firmly place your foot on
[00:17:40] Toni: Was
[00:17:40] that the case? Actually,
[00:17:41] Mikkel: I dunno.
[00:17:42] Toni: I don't know.
[00:17:43] Wouldn't make
[00:17:44] Mikkel: sense though.
[00:17:45] Toni: But anyway, so you, you wanna make sure that this is really trustworthy and in order to achieve that, you want to have as little, uh, you know, data in there that basically could kind of screw this up, right?
[00:17:54] So that's what you should start with then. you can and should use these data points and they very often will already be used like that. To assign owners to those metrics. Yeah. And, uh, and that sometimes happens by a way of, uh, a bonus or commission kind of agreements. Yeah. Uh, you know, in worse, in some bad cases, the CM CMO might have an MQL target that he's being comped against.
[00:18:22] That's, by the way, some of the reason why this MQL thing is happening. Uh, inside sales director will have the outbound opportunity piece that they're responsible for, yada yada. There, there will be areas that people are commissioned against. Um, so therefore it gets triple checked and therefore it can then be trusted.
[00:18:39] But the other piece is also you should, um, be assigning, uh, some of these surrounding metrics also to a owner, right? So you wouldn't pay anyone on a conversion rate. But you should, make the, uh, CMO, in this case, the owner of the conversion metric from MQL to SAL.
[00:18:57] Mm-hmm.
[00:18:58] Right. Because, and you can disagree here, obviously, but, um, if, you know, the, the CMO can decide what the definition of the MQL is and can kind of move it up and down in the funnel.
[00:19:09] Yeah. and if then the conversion rate corresponds in, you know, a good or a bad way. He or she is the one that owns that. Yeah. To be honest. Right. And then there will, you know, everyone kind of from a marketing angle kind of listening and we be well, but what of the sales guys, you know, screw up with.
[00:19:24] That's why of the s a l stage, by the way, that's actually the reason. Um, but let's, let's not get too deep into it. I, I would kind of say, you know, out of those 15 to 20 data points that you come up with, um, you should try and give those to people and maybe even create goals around
[00:19:40] Mikkel: Yeah. And maybe we can provide an anecdote because I had, um, I had responsibility for the marketing number actually when we worked together last time. Mm-hmm. Um, and I would always end of quarter, I. Run through every single closed won deal.
[00:19:58] I would also look at a ton of opportunities that weren't closed yet to see how they were distributed, right? And I would see things like, hey, this one is marked as outbound, but it clearly isn't inbound. And hey, why was this opportunity closed and then opened again? And you know, why is person X getting all of the inbounds?
[00:20:17] It doesn't. So I, I think that's where you actually ensure that someone cares about that efficiency metric at the end of the day.
[00:20:24] Toni: And so this is a really good point, right? On the one inside, this accountability piece has this, okay, you give this number to someone and you make them care about it.
[00:20:32] Mikkel: it. Yeah.
[00:20:32] Toni: By maybe money. Um, uh, but then the other thing is also once you start, have someone caring about, you know, achieving it, you will also. Uh, have, have a person that's gonna be its own little policeman Yeah. Or a woman, um, to make sure that that data definition and the quality of that is, you know, as, as high as it should be.
[00:20:50] Mikkel: Right? Yeah. Yeah.
[00:20:52] Toni: So I think then the, the next step might, you have some data pieces, you maybe have owners, maybe goals around it. The next step is to pressure test the whole, the whole system a little bit by using it to, create a plan that leads you up to your revenue target. Yeah. So, oh, surprised the global guys are talking about this, but, uh, uh, but it's, it is, it is extremely powerful to not just say, here's a.
[00:21:17] It's a target that just hangs and you just, you know, get it. And again, people won't be comped on conversion rates. I've never seen this. Um, and it, you know, that's why, you know, I don't think it's gonna happen, but it's super important for your funnel that your conversion rates check out, right? For many reasons.
[00:21:33] If you put the whole system now into play in order to um, say, okay, we want to get to that revenue number, those would be the things we would need to do. Those would be the goals we need to set ourselves on each day, in each stage, in each kind of whatever in order to get there. Suddenly, uh, this whole collection of random. Uh, metrics is just not so random anymore. Suddenly there's a logic that goes through it. Suddenly it feels like, oh, you know, uh, damn if we don't do this, then we won't be able to do that, and so forth. You have all of those wonderful knock-on effects. And suddenly the, the whole system that you have built now is ex much more pressurized.
[00:22:09] Right. Um, and it's, it's really leading. Not, you know, Again, it's not this, ah, we need to, you know, 4K MQLs, you know, that's why we need 4,000 MQLs. No, it's, we need 4,000 MQLs in order to hit this revenue target that's, you know, down there. And if we don't do that, well, we actually have a big problem here. Right?
[00:22:27] So really kind of putting that pressure on the system, um, again, increases how many people care about it. Uh, instead of how many people care about their one specific number, they then suddenly start also caring about the conversion rates and so forth
[00:22:40] Mikkel: Right. Yeah.
[00:22:42] Toni: And now getting to kind of the last piece here, and we touched upon it a little bit on the accountability part is basically, uh, monitoring.
[00:22:49] Mikkel: Mm-hmm.
[00:22:50] Toni: Uh, so you have now people caring about it. Uh, you have people maybe making sure that the, um, you know, data is, is clean and proper and doesn't slide you pressure tested with a, uh, with a plan. What's now going to happen is that, you will have more and more people look at those numbers all the time.
[00:23:08] Mikkel: Mm-hmm.
[00:23:08] Toni: Right. You can call it transparency, you can call it, you know, bit tougher, uh, monitor. But that's what's going to happen. And um, as more people look at it as more people that are responsible for it, look at it, uh, there will be more and more cases where someone is like, wait a minute, why did this one actually not count in?
[00:23:25] Uh, did we, did we drop one here? Why would we drop on? Yeah. And then you kind of get into this whole like, um, making sure that. These things actually kind of stay correct because things are changing all the time. And this is, you know, now kind of getting back to this mouthful of a system of self validation, this is what this is basically creating, right?
[00:23:45] You start very simple, you know, data, diet, you know, easy stuff. You, uh, ditch it out to people, Hey, you should be caring about this because I pay you for it. Uh, you pressure test the whole thing to connect it to a plan. Guess what? Now a lot of people will look at this, will basically now kind of enhance the data quality of the whole thing again, again, and again and again.
[00:24:04] And you can, uh, you know, over time put more and more and more and more pressure on, on those metrics to use them.
[00:24:10] Mikkel: I think also it just reminded me of one of the cadences you and I would have is you would sometimes at this stage just send a screenshot of a graph Yes. Of one of those, you know, metrics and whether it was, you know, overperforming or underperforming, doesn't really matter, but let's just say it was underperforming.
[00:24:25] Toni: It was always underperforming.
[00:24:26] Mikkel: Yeah. Yeah. I was trying to be kind to myself, you know, so, uh, you wouldn't have to say anything I would already know. This was the case, I would already have plans to remedy it. And in some cases my rebuttal would be, you know, a graph back later showing, you know, oh, on track.
[00:24:44] Toni: But no, I think so. You know, this was, uh, Toni's wonderful, passive aggressive approach. Yeah.
[00:24:51] Mikkel: No, but you know what I, I heard of a CRO who did the same, I think it was at Divvy weekly email. He would, he would pull some of the graphs of their, you know, to highlight their performance, obviously with just a couple of bullets along with it.
[00:25:04] So it is a thing.
[00:25:05] Toni: Okay. So I'm not, I'm not, I'm not the only psychopath. That's what you're saying. So wonderful. Um, so, uh, uh, yes, right. Kind of, I think kind of sending this screenshot in a slack and then no other message. This was not always so aligned and this No, this was like,
[00:25:19] Mikkel: like cheeky. I
[00:25:20] don't need to
[00:25:20] Toni: it. no. This is kind of obviously one way to go about it and I think, uh, what happened, we, we created a culture that very much cared about these numbers, right? Yeah. Um, and not just the revenue number, but everything leading up to it.
[00:25:31] So now we come to almost the last piece, which I think is actually pretty cool.
[00:25:35] So you have all of these things in place, your system is running, people are caring about it. Um, now it's actually extremely, it's much easier to add to the pool.
[00:25:44] Mikkel: Yeah.
[00:25:45] Toni: To add maybe another step, uh, why would you add another step in the first place? Well, number one, operationally speaking, there might be other parts of the organization that are responsible for that, right?
[00:25:55] It could be this SAL to sql, maybe there's an inbound rep that's responsible for that. Um, but the other reason why you might want to add, you know, additional steps here is to, uh, have better root cause analysis, right? If, if your only two steps are website visitors to closed won revenue, yeah.
[00:26:13] Mikkel: Yeah.
[00:26:15] Toni: You literally need to scream at the whole sales and marketing organization when something isn't working out.
[00:26:20] Yeah. As you add more steps in between your, your screaming can be more nuanced, I
[00:26:26] Mikkel: targeted.
[00:26:26] Toni: Yeah. Um, to a specific part A, it's, it's breaking here. What's going wrong here? Yeah. Uh, which makes it extremely, much more actionable. And, um, and for you to, you know, go, go about it.
[00:26:37] Mikkel: Yeah.
[00:26:38] Toni: So now that we covered the wide, so how now, well you would actually add that specific metric probably within this tree structure or this fun structure that you have built now.
[00:26:48] Right? Let's just say you only have lead and SQL and you want to add MQL into it. Um, and this is almost two use cases. Either kind of comes in. From nowhere into being, or it has been there before, but the definition is changing. Yeah, right. It's kind of almost the same thing. What you will now find is that the, uh, overall conversion rate from lead to SQL will actually not change.
[00:27:10] Um, you will add the MQL piece into it, and obviously, kind of depending on where the MQL now floats further, closer to the lead or closer to the uh, uh, SQL. Which really means, um, really the conversion rate steps between lead to MQL, MQL to SQL. Um, you know, as, as it floats, it will actually then also dictate that your goals around the MQL need to be updated.
[00:27:36] Right. You can have an assumption that, uh, the conversion rate for MQL to SQL is gonna be 50%. Great. Uh, if it turns out that is actually not the case, it's actually much lower, aka floats high up in the funnel. I'm not sure if that makes sense for everyone. Then actually, instead of, you know, 4,000 MQLs, it's actually now, you know, 6,000 MQLs need create.
[00:27:58] Right? Um, and because it's not part of a system, uh, you can less so. Rely on, you know, trusting that specific number, but because it's governed between, you know, a rock and a hard place, so to degree, yeah. Uh, it's, it's getting much easier to kind of get to that point. Right. And then as that metric kind of finds itself, you know where it actually should be sitting, then the goals that you need to kind have come out of this in order to hit your revenue target again, all of this things connected that then also kind of increases, right.
[00:28:27] And makes it then extremely clear for everyone. Right.
[00:28:29] Mikkel: Mm-hmm. Yeah.
[00:28:31] Toni: So
[00:28:31] Mikkel: they end up trusting the witness.
[00:28:33] Toni: So I think where this will lead you to, if you get to execute this in the right way, you know, going back to the, the witness thing, I think, and, and I think this is where this trial thing is kind of really interesting because it's, uh, there is a jury sitting around.
[00:28:51] Mikkel: Yeah, yeah, yeah, yeah.
[00:28:53] Toni: And it's kind of true, right? So really think about you sit in an executive meeting, you're sitting in a QBR. It's not like you have a one-on-one with a person. You challenge a person, maybe in a public space, immediate defense goes up and immediately like, Hey, your witness is, you know, unbelievable. but now you have this whole thing in place, it's gonna be increasingly harder to discredit the data pieces.
[00:29:14] Like increasingly so, and then the jury sitting around will be like, um, no, I think the data probably checks out. Yeah. Right. Uh, so I think that will happen. I think what will also happen is that, the, you know, I call it the pause between objections.
[00:29:31] Mikkel: Yeah.
[00:29:31] Toni: You know, will just increase. So you present someone with data that doesn't confirm their, their worldviews, and now it's not gonna be to like, uh, can't trust the data.
[00:29:44] Yeah. It's gonna be okay. I need to, I need to know and now I need to find something else here to say. Yeah. And to dismiss that. Right. Kind of. I think that will increase. That will be a good sign for you.
[00:29:53] Mikkel: you.
[00:29:54] Toni: And I think once you kind of get through some of those pieces, and by the way, I think one really important item not to forget is try to not even.
[00:30:04] Get to this point where you, uh, you know, have the defenses go out for someone, try and, you know, avoid that as much as possible. But the idea basically is to try and get this conversation to be, uh, in an intellectually honest effort. Yeah. That's what you want to achieve. And that's, you know, if you get to that supreme level of talking about data, I think then you're gonna end up being able to leverage data really to the fullest.
[00:30:29] Yeah. Um, right. And it's kind of, The top end of the
[00:30:31] Mikkel: but I think, I think this, this point is so important, right? And we've talked about it before, not actually weaponizing the data. If you are responsible for actually making people trust the data, your approach really matters. So we talked about not ambushing people.
[00:30:44] Mm-hmm. You wanna make sure you have a, you know, a soft check-in before saying, Hey, you know, Toni, I'm. Look at these numbers here. They're not so great. Let's, let's, let's have a chat, right? So it's not an ambush in, in that scenario, right? Yeah. Um, so there are a couple of steps to how you basically, operationally speaking, use it.
[00:31:01] That matters quite, quite a lot.
[00:31:03] Toni: Just wrapping this up, uh, so bad data, common common stuff going on, and really what it means is people don't trust it and can't trust it for the decision making. The way you get to trust is basically by creating, number one, a data diet. Then creating accountability around the few data pieces you have created.
[00:31:20] Then by putting pressure on the system, by making it part of a plan of a revenue plan, ideally, and then, you know, as all of that ramps up, you'll have more eyes on the problem, which will basically then self validate Yeah. That the data is being tracked and so forth, right? Um, if you do all of that stuff, I think you will have a much easier time, uh, with those data quality conversations that you're gonna have.
[00:31:42] Mikkel: So we still haven't gotten any, uh, 500 word reviews yet.
[00:31:48] Yeah.
[00:31:49] I've been monitoring that daily. Yeah. And it ain't happening. So if you're listening to this, can we sweeten it somehow? Like Mm. Send us a screenshot. We'll send you a book. We can do that. I just decided for us
[00:32:02] Toni: Yeah, I was about to say let's send out more books here, but yeah, no, let's totally do that.
[00:32:06] Send us a screenshot. We're gonna send a book. I think that's funny. Uh, and for real. Um, and then I think if we're not missing messing this, uh, thing up here, there will be something special happening this Thursday. Oh,
[00:32:20] Mikkel: Oh yeah. Right. No, we didn't mess it up. It's all good on Thursday. We already, I think, teased it a bit.
[00:32:25] We have, uh,
[00:32:26] Toni: gonna be special. Let's not talk about it.
[00:32:28] Mikkel: Ah, okay. Watch, watch your podcast feed, I guess. Yes.
[00:32:33] Toni: And
[00:32:33] um, the big question is why is there Toblerone?
[00:32:38] Mikkel: Yeah. Answer that question Well, I don't wanna be bothered sending Toblerone.
[00:32:43] Toni: No.
[00:32:45] Mikkel: Okay, let's just end it here. Thank you so much for listening.
[00:32:48] Thanks. Thank you, Toni. Bye. I'm not gonna send a top. This is gonna be too complex.