{PODCAST} In-Ear Insights: Selling The Value of Data To Stakeholders

{PODCAST} In-Ear Insights: Selling The Value of Data To Stakeholders

In this week’s In-Ear Insights, Katie and Chris tackle how to sell the value of data to stakeholders like the C-Suite. How do you convince people of the merits of data, of investing in data programs and projects, and ultimately to become champions for the analytics work you do? Tune in to find out!

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{PODCAST} In-Ear Insights: Selling The Value of Data To Stakeholders

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Machine-Generated Transcript

What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.

Christopher Penn 0:17

In this week’s In-Ear Insights, let’s talk about getting buy in.

For data science, how do we prove the value of our data of our marketing data? So one of the things that has come up as a topic recently, is getting people in the C suite execs to recognize the value and importance of data, particularly data science within not just within marketing.

But in general, a lot of folks understandably, are a little confused by what this thing is what value it does or doesn’t provide.

And the folks on my side of the table and the the data science crowd, have a tendency to be a little too technical, and what we talk about that that read over the heads of people who don’t care, honestly, they just want to know what it’s going to do for them.

So Katie, helped me help you as a CEO, how do I talk to you about the value of data and the value of data science?

Katie Robbert 1:13

You know, it’s funny, I was thinking about this.

And I have always played the role of mediator between the two sides of the house.

And I feel like that a big part of what needs to happen is, you is there needs to be and it’s a lot of times it’s a PM, or an account manager, you know, sort of that like product owner, who can advocate for both, you know, audiences who can advocate for the technical team for the data science team, and also advocate for the C suite and sort of bring the two pieces together.

And so what that really means is understanding where both sides are coming from.

And so if you don’t have that mediator, you know, so Chris, let’s say you’re bringing to me, like, I want to do this, you know, GPT-2, 12, lingo, Ringo, r squared, whatever.

And I’m like, I don’t get it.

Why do we need to do this.

And you’ll say, because it’s cutting edge, because it’s this because it’s that what you haven’t told me are the benefits to the business, the risks if we don’t do it.

And with that, the risk if we don’t do it, in terms of losing audience losing money, losing clients, the risks can’t be, because we’ll fall behind.

And so that’s part of the challenge with communicating these things, communicating the value to people who need to make those decisions, is you have to meet people where they are now the flip side of that with the C suite, what I’ve experienced, is, they try to get too in the weeds, they try to understand too much of the technical feeling like that’s how they’re going to make better decisions.

And the whole purpose of the conversation gets lost, I used to work with a stakeholder who would try to get so far down into the weeds with what the development team was doing, that he would get so confused.

And we spent so much time trying to educate him on what the team was doing, that we couldn’t get him to make a decision because he didn’t understand every single component of what was happening.

And it was a complete distraction, from just getting him to make a decision.

And so that then became my job to sort of pull him up out of the weeds and then decipher what the engineering team was doing in a way that he could understand it.

Now, Chris, in your experience, you’ve primarily been on the side of the technical folks, but you haven’t always had that intermediary.

Right?

Christopher Penn 3:49

That’s true.

I mean, when you first joined my team, back at the old shop, I was the person who’s talking to executive stakeholders within the agency and with other clients as well.

Katie Robbert 4:02

And so what challenges did you run up against?

Christopher Penn 4:06

All manner, I mean, from it’s been sort of an ongoing story of my entire career that no one actually knows what I do.

And therefore, no one can effectively measure.

Which means, among other things, you know, I never got promoted for anything, I got to quit jobs to to move on to whatever’s next.

And it was really difficult for other people to sell what I and my team had to offer because they didn’t really understand it.

They had sort of a checklist of buzzwords that they felt comfortable using and even attempts at really dumbing it down.

Still, were challenging.

Like, I had trouble with folks.

explain to them why they needed Google Analytics.

Just that something that is very straightforward, hey, you’re doing all this marketing.

You should be Measuring your marketing, so you know what to do more of or what to do less of.

Even that was a stretch for some people to like, we don’t measure things here.

Katie Robbert 5:09

So it’s interesting, because I’m hearing the challenges and the way that you’re saying it, because you haven’t given me concrete, like, dollar values, you haven’t given me solid reasons, like, you know, Katie, you should measure the amount of flour that you put into your bread.

Okay? Why? Because that’s what you’re supposed to do.

That, to me is not a big enough reason for me to start to do something.

However, if you say, Katie, you need to measure correctly the amount of flour that you put into your bread, so that you can have good quality bread and not waste your time and burn down your kitchen and ruin all of your pans.

By not doing things correctly, you’re gonna waste money, you know, you’re gonna, you know, cause, you know, a big insurance claim, because there was a fire in your kitchen like, now I’m listening.

Now I’m understanding why it’s important.

Okay, if you go back to that example of Google Analytics, how, let’s say I knew nothing about it, how would you phrase that differently? To me, Chris, why do I need Google Analytics?

Christopher Penn 6:18

You don’t? And here’s the thing, I actually want to push this back towards you.

Because this is a really good example.

How would you explain the value and the necessity of upgrading from Universal Analytics to Google Analytics 4.

We know all the technical reasons, we know what’s going to happen with people’s data.

But given that we see a whole bunch of people not using their data anyway.

I need advice.

How do I convince somebody that upgrading migrating to Google Analytics, which is not a painless endeavor is something they should do? What do you what would you tell me to tell somebody else? So

Katie Robbert 6:57

I do like how you push this back on me and didn’t answer my initial question.

So we’ll come back to that in terms of advice, you know, so let’s say, you know, you’re using Trust Insights as the example.

The reason why we upgraded from Google Analytics 3 to Google Analytics 4, was so that we wouldn’t have data loss in terms of Universal Analytics being cut off.

And, you know, Google and Google rolling out, you know, version four.

And so Okay, great data loss.

Who cares? Are you looking at your data, we internally make decisions around, where to focus our effort, where to focus our time and our marketing and our money, based on the data that we get from Google Analytics.

So we are making decisions that have monetary value attached to them with our data from Google Analytics.

So the advice I would start to give you in terms of, you know, counseling clients is, you know, we always ask, what decisions are you making with your data? Oh, I don’t know, you know, what’s working? What’s not working? Okay, but what do you do when you find out something’s not working? I mean, I kind of ignore it.

Okay, then why are you looking at it in the first place.

And so you need to keep going down that line of questioning to really get to the root of the problem someone’s trying to solve because I think one of the mistakes and we can dig into this is we assume we know what we think the value is from the other person’s perspective, but 10 times out of 10, we don’t actually know what the other person is thinking.

So that’s actually where you need to start.

It needs to be more of, you know, almost like an interrogation.

Without it being sort of like scary, but interrogation of like, what is the real problem you’re trying to solve? And then I can help frame the conversation around that.

Christopher Penn 8:53

Okay, so pretend I’m Bob, the arrogant CMO, which is not a stretch I know best with my customers.

Why don’t need analytics anyway, and you’re trying to tell me we’ve we’ve this Google Analytics, 4 business, whatever, what why do I care about this? I, you know, I know what’s best for my customers.

Katie Robbert 9:15

And so I would actually start that conversation with like, trying to understand So Bob, how try to get inside his thinking process a little bit.

So Bob, how is it that you know, best? Like, what is it that you do that helps you understand what’s best for your customers? And well, actually,

Christopher Penn 9:32

Katie, let me tell you.

I know what’s best for my customers.

I’ve been in this industry for 30 years, and I’ve seen everything and all this newfangled stuff doesn’t matter.

I know what’s best because I see it.

Our company is the best.

Katie Robbert 9:46

Great, and so continuing that line of you know, not quite honestly continuing that line of questioning like, Okay, so in your opinion, what is the best course of action for our marketing? What’s our next step?

Christopher Penn 10:00

Our next step should be to build a flywheel.

We should build a market.

I read about this in a magazine when I was on a flight from Las Vegas back to Boston.

And it sounded really good.

So, and it was by some guy had a Harvard who was at Harvard Business Review.

So that’s what we’re going to do, because clearly he was an expert.

He was in Harvard Business Review.

Katie Robbert 10:19

Okay, so help me understand how we’re going to execute that, you know, plan that you have what what is the flywheel going to do for us?

Christopher Penn 10:26

Well, I told my marketing director figure it out, we need to have a flywheel buy in 30 days.

That’s, that’s what I told them.

Katie Robbert 10:32

All right.

And so, you know, I can certainly work with the marketing director to put together this flywheel.

So my question to you so that we can better you know, execute your vision is? What is your ideal outcome? In terms of what do you want to get from this flywheel? What kind of decisions do you want to make with this flywheel?

Christopher Penn 10:50

I told the board, we’re gonna have 20% more customers, we get 20% More customers by this time next year.

That’s what this is going to do.

Because that’s what the article said.

The article said that you could improve your your your revenue up to 20%.

Like that’s what we’re going to do.

Katie Robbert 11:05

And so Bob, what happens if the flywheel just for sake of conversation, what happens if the flywheel isn’t, you know, giving us enough information? Are there other places that you would look to supplement that information?

Christopher Penn 11:19

No, I’d say it was one marketing director.

SWOT analysis, fire them get another one.

Katie Robbert 11:23

Okay, cool.

Christopher Penn 11:27

Now, to be clear, I’m not Bob.

Katie Robbert 11:29

But we have literally been in this conversation.

Exactly.

Christopher Penn 11:33

We’ve both been in this conversation.

We’re like, Oh, my God, you’re an idiot.

Well, yeah.

But it’s not uncommon to see somebody with that.

Data, immune and fact proof screen around.

Katie Robbert 11:49

And so in that situation, how do you sell them data science, the best course of action is to actually work with the marketing director.

And so basically, so you’re never going to get around the fact that you’re going to be asked to do things that you think are asinine, and ridiculous, great.

You can use that to build out almost like a business case, basically, to say, Okay, if we go down this road of, you know, a flywheel, here’s the likely outcome.

And here’s the reasons why, here’s the research I’ve done.

And you can give that to Bob.

And Bob’s gonna be like, Yeah, forget it, we’re going to do fi will anyway, you’ve already documented why it’s probably not going to work.

But then you also have over here, and here are the other things that could work.

So you know, I know I’ve talked about before, but I used to run a steering committee of about 12 people who had PhDs in psychology, and they were trying to make decisions about a commercial software product.

It was a huge mismatch, because what the product did, and what they wanted were two different things.

And so once a month, when I got them all together, if they all showed up, my job was to get them to make one single decision, just one.

And so in the, the way in, which I would do that is I would spend basically, the entire month leading up to that next meeting, laying the foundation, gathering information, trying to understand from their perspective, like where their heads were, why they wanted something to move in a direction.

And so in the instance of, you know, Bob, the dolt of a CMO, which, you know, we’ve all run into them.

It’s less about you saying, Bob, you’re wrong, this is never going to work, because that’s going to fall on deaf ears.

I would not try that tactic at all.

It’s really about you trying to get inside Bob’s head of where is he coming from? Why is this the shiny object? Because there’s always going to be a few layers down? The real answer is in there somewhere.

And so your job, whether you’re a data scientist, or an intermediary is to understand the other person.

Now, you’re probably thinking, Well, why is it my job to be the understanding one, why can’t they be the understanding one, because that’s just not how humans work? I can’t I’ve been I mean, this in all seriousness, like I’ve lost track of how many times someone has said, like, Why do I always have to be the bigger person? Because somebody has to be, so you need to choose? Do I want to keep moving things forward? Or do I want to be stubborn?

Christopher Penn 14:25

How much does hijacking someone’s psychology take into account because when I think of Bob, this wild person, we clearly know that Bob is not a particularly well informed marketer, right? He reads airplane magazines, which are, you know, six to 12 months out of date at best.

But he’s also clings on to buzzwords like, you know, flies on manure.

And so thinking about something like Bob, I could almost use it make the case of saying, You’re right, Bob, a flywheel is a good idea, but Wouldn’t you love to have a Data driven flywheel, but that’d be really cool.

You could you could talk about that and, and showcase that to the board.

It’s just how how smart a marketer you really are.

Katie Robbert 15:09

If for those who can’t see on the podcast, I’m shaking my head.

Now, the reason is because when you’re dealing with a Bob, you know, someone who’s in that power position who definitely is uninformed.

They need to feel like it’s their idea.

So a better approach to that is okay, so, you know, I know what my end goal is, I know that I would rather have Bob, using data to make decisions other than wasting all of our time on a flywheel.

So the foundation that I started to lay is, oh, hey, Bob, you know, I love this flywheel idea, or that’s a really interesting idea, you don’t have to outright lie to Bob, like, that’s probably not a great idea.

But the conversation is, you know, that’s really interesting.

Let me do some research on flywheels and send it to you so that you can sort of like, help me understand a little bit more about your exact idea of where a flywheel fits in.

And so then it’s an opportunity to not outright say, Bob, a flywheel or something, but to educate Bob on, you know, other case studies of how flywheels have worked and other ways, so that Bob can start to come to the same decision that you’ve already come to.

So when I was managing that steering committee, I already knew the decision that I needed them to make, I already knew what the outcome was, my job was them to get them on board with it.

So I wasn’t manipulating them.

I was educating them, without them feeling threatened, that they didn’t know enough to make the decision.

So by the time we came to the decision, 30 days later, they were like, wow, this is the best decision I’ve ever made.

And because I my role as the intermediary was just to facilitate the conversation, my ego wasn’t in it, it wasn’t Oh, but it was my idea, guys, I need all the credit, it was, I had helped move everyone in the same direction, that is my measure of success, the decision in a way almost becomes irrelevant, doesn’t matter what the decision was supposed to be, we got there.

And so as a data scientist, as a developer, as an engineer, you already have more insight into what the decision needs to be made, is that needs to be made.

The challenge is, then you need to take your ego out of it and stop saying, but you’re doing it wrong, just do it my way, that’s never gonna get you very far, it’s start to lay that foundation of why the decision that needs to be made is the right one and helping people understand and see the different examples of that, but also the risks of that, you know, Bob, you were talking about a flywheel.

That’s a really interesting, you know, path that we could go down.

What I need to understand for my budget is, you know, is if we invest in this, and it doesn’t work, and let’s say the marketing director is like, oh, and we need to hire a new one.

Is that a risk you’re willing to take financially? And so those are the kinds of questions that are more useful.

Versus Bob, that’s a dumb idea, it’s never going to work, because Bob’s not going to hear you.

But Bob will hear, Oh, it’s going to be really expensive to replace the marketing director.

And none of my ideas as Bob will get done until we replace that person, who I should probably not get my marketing director fired, because I’m selfish, and I need someone to do all of my bidding.

Christopher Penn 18:29

So it sounds like digging into the impact of decisions is the easiest way to showcase to somebody, here’s, here’s what’s going to happen.

If you go on this road, here’s what’s going to happen if you go on this road, and ideally, to the point where it’s obvious which road they should take.

And if it’s not, you should probably update your LinkedIn profile, because you work for an idiot.

Well,

Katie Robbert 18:55

yeah, that’s.

So going back to Chris.

So let’s say I asked you the question, why do i Why do I care about Google Analytics? Why do I need to upgrade to Google Analytics 4? Now, given this conversation, what would you say to me?

Christopher Penn 19:11

So the here’s the thing about this, we use Google Analytics to make decisions about where we’re going to spend our money.

We because we only have a certain amount of marketing budget, and we want to spend it as smartly as possible, we want to get as many leads generated as possible.

That’s what we’re all.

We all agree that that’s that’s the outcome we need to generate leads so that sales has somebody to sell to.

If we don’t upgrade to Google Analytics 4.

We will lose the ability to know where we’re overspending and underspending which means we will not be able to generate as many leads will burn through our budgets faster.

And we all get beaten up by sales for you know, essentially not helping them generate the revenue that our company needs to hit as target.

We need to hit a million dollars in revenue this year.

If We don’t upgrade, probably 50% of our decision making is going to get messed up.

So we’re going to potentially lose half a million dollars if we don’t upgrade.

Katie Robbert 20:08

And that’s a more useful conversation.

It’s speaking the language using the terms that the person you’re trying to get a decision from cares about.

So Chris, you know, I care about revenue, I care about having a filled pipeline, I care about making smart decisions, you have just framed the advice in terms that I’m going to hear that are going to resonate with me personally.

And that’s the, you know, not so secret secret to demonstrating the value of things is it you know, it’s classic marketing, it’s help, it’s meeting people where they are.

And so, you know, if we’re selling vacuums, we’re not just going to say, this is the greatest vacuum in the whole world by it, we’re really gonna dig into the problem that our audience is having have, you know, do you have long haired dogs, and you struggling to keep up with the tumbleweeds that roll across your floor, you’re now speaking language that resonates with me personally, and I’m like, oh, then yes, that is a solution.

That’s you, it’s the same thing with when you’re trying to demonstrate the value of the work that you’re doing.

You’re basically marketing, what it is you’re doing to the unaware audience and trying to, you know, address their pain points.

That’s really all it comes down to.

Christopher Penn 21:32

It’s interesting, because, you know, we talked about selling data science into the C suite.

And selling really is the right word, there it is, this, it is solution based selling here, your here’s the problem that you have, here’s the impact, here is the features and the benefits, that will make your pain go away, right, or will will make you happier, as opposed to just saying, here’s the thing, here’s, you know, here’s, here’s all the things, what the thing does, it’s no, here’s how buying this thing will make your life better and make your hair grow longer.

And you know, remove five years off of your, your nose, or whatever the thing is that people pitch.

And I guess the question then is, so for folks who are in a data science role, in addition to the steps we’ve outlined, should they be thinking about taking a little bit of sales training to understand how to solution sounds?

Katie Robbert 22:28

Not necessarily.

Um, you know, because that I feel like it’s going to be, I mean, that sort of like, that’s a whole different arena, I think that really what it comes down to is, you know, using things like user stories to understand the pain point of the person that you’re trying to talk to.

And so, Chris, you know, we’ve been talking about this a little bit behind the scenes.

But, you know, if you’re saying, you know, I want to spend money on Google ads, my first the, where my brain goes is like, well, what’s the problem you’re trying to solve by doing that? And so I’m asking you, essentially, for a user story, as the, you know, chief data scientist, I want to spend money on Google ads for whatever the outcome is, and then we can have that conversation of, you know, is that a priority? Is that the right problem you’re trying to solve? Like, where does that fit into the overall, you know, strategy for us.

And so user surveys are a great way to start to have those conversations.

So as a data scientist, you know, you don’t need to have a solution selling background, to be asking me, the CEO, you know, why I do or don’t care about using data.

You can say, Hey, Katie, you know, if I were to say I had a whole new dataset for you, what would that mean? You know, and can we put it in turn? Can we do sort of like a little bit of a workshop of putting it in terms of user story? And it could be like, as the CEO, I don’t care about data, because I’m going to make whatever decision I feel like, or as the CEO, I need even more data, because I’m struggling to make decisions about where my audience is, that then gives you those cues to say, Okay, I know what kind of data can solve that problem.

And then you can start to get that ball rolling of the solutions.

Christopher Penn 24:16

So let’s do this, because I think it would be really fascinating to do a walk through of that, and then maybe the next episode or two, because I would like us to try Spotify radio advertising for Trust Insights.

So maybe in a future episode, we can walk through live how to do that business cases construction, what are the pieces that I would need to make a case to you? That yes, we shouldn’t try this or no, we shouldn’t try this.

Katie Robbert 24:41

You just want me to do your homework for you, Chris.

Pretty much.

But yeah, I do think there’s value in it because basically what you’re doing when you are trying to demonstrate the value is you are giving someone a business case, so that they can make a decision.

You’re trying to speak their language and understand their pain points so that you can really demonstrate the value of the problem that your thing solves.

Christopher Penn 25:08

Exactly.

So on that note, if you’ve got some things you’re trying to sell to your executives and and are struggling with it, why not bring it over to our free slack group go to trust insights.ai/analytics for marketers, where you and almost 2800 other marketers are asking and answering each other’s questions every single day.

And wherever it is you watch or listen to this show.

Now if there’s a platform you’d rather have it on instead, go to trust insights.ai/t AI podcast.

We are on pretty much every place that hey, if you liked today’s show or any of our shows, please consider leaving us a rating and a review.

It really helps out.

Thanks for tuning in, and we’ll talk to you soon


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