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So I’m Clay Cowan, I’m a partner at KcKinsey and Company. in our marketing practice, just as a brief intro, I was previously the Chief Marketing Office for Gilt and for Betterment and then I was at digital for Starwood, Starwood Hotels, which does a lot of personalization. Really excited to be here today.
Hello I’m Robert Tas and I work in our marketing and sales practice, I help lead our digital marketing practice. And I spend a lot of my time at the intersection of data and technology and help a lot of our clients with personalization efforts. Previous to joining McKinsey I was a practitioner, and a B to B tech company, and I also helped run JP Morgan Chase’s digital marketing globally and helped them implement personalization there at scale. So I’m excited to be here and chat with you all.
So first, a few things. Really exciting to be talking to people who are truly pioneers and on the edge of this. As you might imagine we tend to work with bigger companies, and people who are learning about this. I feel like we are talking to the group that is leading the way, and we talk about examples of companies of how this works really well. So it’s really exciting to be here with you today. We traditionally talk a lot about the “why” to do this, and the “how” to do this. For this audience, I think you guys are the choir on why to do this. You understand the why. I hear a lot of questions about playbooks and operating model, and what we see out there working well in terms of actually making it go. So how do you structure, how do you actually operationalize that? So we’ll send most of our time today. This isn’t gonna work. TBD if it’s gonna work at all. But if it’s going to work, it’s going to be because it’s informal. So if you guys have questions fire them up, and we’ll be happy to take them. Where are we? Uh oh, gave my answers so you guys are gonna kill that one. Alright. First an exercise. Everybody stand up. Please just do me this one favor. It’ll be quick.
[Robert] They had their coffees.
I know it, I know it. Alright.
[Robert]They didn’t pay attention.
So I’m gonna ask a set of questions. Robert’s gonna help. What percent of consumers begin their product searches, this’ll be showing you how it works, begin their product searches on Amazon? Maybe you saw the answer, but instead of starting at Google, we see 55% of product searches start on Amazon. Right? So very high. So that has changed in the last 18 months. Now, I want you to think about the answer to the next question.
[Robert] I feel like Vana White right now.
Yeah go for it.
[Robert] What percentage of online and offline sales are influenced by Facebook, power of social?
Everybody got the answer in their head?
[Robert] Who thinks it’s A?
30, 40, 50, 60. OK. If you got an answer other than the right one, which is 50, please sit down. Ah, really would’ve weeded you out on the first one.
[Robert] They’re just tired.
Second one. By 2020, which I realized in the car on the way over here is 20 months from now, right like we’re supposed to have hover boards soon. That’s not very far off. So what percentage of all customer interactions will be handled without a customer agent? You call into a call center or you type into a chat or you send an email to a customer interaction. What percentage are going to be handled without a human?
[Robert] Is it what we wish will be handled without a human?
55, 65, 75, 85. Right so 85, stay up.
Right. So only 15% of interactions are going to be handled with a human. If that doesn’t tell you what the job market, you know. So how many emails does an average American receive a day? A working American? 100, 130, 160, 190? Anybody? You guys in the back are all standing but it’s because I don’t watch. 130. Anybody left? Alright well if you had gotten the last one right you would’ve gotten a prize, so apologies. No one got it. Alright so then what percentage of open emails do people click on? 10%, 15%, 20%, 25%? We see on average open rates, open and then clicked, 10%. So this is a little bit of a problem statement. Right, which is I’m gonna be searching on platforms that aren’t a search platform traditionally. And how do I market to a person that has 130 emails a day? And even if they open it, how do I get them to click on it? And so this is data that we see right now and where we’re headed. OK we’ll go quickly on why it matters as I told you. So this quick version is 83% of consumers want personalization, 95% of retailers say it is so paramount to their strategy. The cognitive disconnect is, that’s a big word, that 23% of people think retailers are actually doing this well. A lot of people that are doing this well are in the room. So thank you. 15% of retailers say that their personalization strategy is fully implemented. So that means 83% of consumers want it, and 85% of retails do not really do it yet. Right so that’s the disconnect. That’s why it matters. We talk about personalization a lot and it’s really important for us to talk about what we really mean is personalization at scale. We talk to people and they say “Oh, I do personalization”. But what they really mean is they do some version of segmentation, they have a little bit of a slice of the marketing, send this people that, or send this people that, or they have a welcome drip. What we mean is, you use customer and prospect triggers. Signals in the marketplace, what do I see that I can observe in data. In real time, right, not I acted on it in the past. I acted on it as it happened, so that means there’s probably technology to happen. Because you cannot manually do that. Across all channels, not just your email channel, not just your eCommerce channel. And then with an operating model, they can actively sustainably do it. Because what we see is when people try to do the first three things, they break their marketing organization. They just can’t keep it up. Right so you have to find a way to operate. So I think we’ll spend more time than usual today talking about that.
I think I’m gonna just that, and I’m a little probably harsh, but we need to stop following people around on the internet like prey, and actually personalize experiences. With messaging, offers, experiences, end to end. And we have amazing technology now. We’ve got to stop doing the peanut butter crap that we all see.
– think that might’ve been the first time McKinsey said crap in a presentation.
I hope we’re filming.
[Robert] They don’t let me in front of media much.
[Robert] Alright. So we think about the components of personalization, we like things in buckets. Our four buckets are these. Let’s start at the top with data foundation. There’s a lot of ways to do it, but I have a single view of the customer and then I understand things about them. This is where our value is. This is our most valuable overall segment, our micro-segment, these are the types of behaviors that we see that drive that value. So starting at the data. The second is, I gotta make a decision about what to do about that. My data’s telling me this one thing, I gotta make a decision on what to do about it. Right, and then how to handle those sets of decisions that maybe cause collisions with any individual customer. Oh you’re new, you’re new to file, so we have a program that does that. But then you showed us a signal that said we should do something else with you, what happens at that collision point? Because, well, we might want to send you 20 emails a week, right, but how do I make a decision about what to do about that? OK so we have a hypothesis on what we want to do. How we want to handle that scenario or how we want to act on that signal. So we see this person puts something in their cart, how do we want to act on that signal based on what we know of who we are? So then we need to design something to happen. Right so I want to send a notification in the app when someone adds jeans to their cart, to let them know X about sizing. We think that’s a hypothesis that’s going to drive “Oh wow these guys seem to really know jeans, “let me add something in it”. So I need to then design something to actually do that. SO I need to write the copy, what’s gonna happen in the app, how am I gonna send the email out, but literally I gotta make the thing. Right? And then we gotta distribute it. So the previous was just chasing everybody around the internet. How do we use platforms of like OK this is gonna happen in display, this is gonna happen in email, how are we actually gonna make that happen and then listen to the results to throw back into the data. And so we thought a thing based on what we saw. We designed a decision about like OK we’re gonna go do this test, we think there’s some value in doing this thing. Then we designed a set of tests or designed a set of marketing trails to go out, and then we delivered them, and then we tracked the result back into the data. So that’s how we see companies operate at scale. Lots of technology but also an operating model to make that happen. When we see companies switch to a cycle of a truly agile operating model, what really matters is that the throughput goes through the roof. So you see companies, or we see companies often start at 3 to 4 tests a month, that’s being generous. They say they run tests but they really don’t. And so this traditional, we ran this campaign last year, we’re gonna run this campaign next year, we’re gonna spend this much money on it. We hear that a lot. But when you go through this more agile operating model, of like we’re gonna talk about who’s in the room for that, we see the result of, not even the result of the tests, the metabolism of the tests go from 3 a month to 30 a month. I would say lighter, faster tests are better than fewer, bigger, it’s better outcome than fewer bigger tests. So we see a lot of like OK what is the best version that we can get out in two week sprints. So take what the tech organization does in terms of building digital product, and applying it to marketing. How can you work in two week sprints to get four tests out every two weeks? Then you’ll get up to eight tests out every two weeks, and then you’re gonna have at the end of the month, three or four winners, and then how do you scale that.
[Robert] Changing the cultural mindset of what testing is today versus what it was 10 years ago or before that, is really the trigger switch that has to happen. To be able to increase the metabolic rate that Clay’s talking about is where the amazing value capture is. And as companies start to think about that culturally as a performance mindset, you see the light bulbs go off. It’s an amazing transformation. But it’s really reorganizing yourself and your organizations to be in a position to be able to move fast, and we’ll talk more about that in a minute.
Yep. So I hope that everyone in the room feels comfortable with the right hand side of this page. Right cuz you were the bleeding edge. Right so we see companies like yours in the room, that are at 30 tests a month. That’s a great bar for a marketing organization. If you’re above that, great. We also see the execution of the numbers of days an email, from an idea of an email to the out the door of an email, is less than a week. We see big companies where it’s many months. Right, but it should be fast. So I hope that feels comfortable to you all, but if it doesn’t, it’s a great benchmark to aspire to. If you’re ahead of it, let us know how you do it. Can you take this?
Yeah so as we were starting to talk about in the setup in the beginning around, what’s the playbook look like. We have kind of four things that we talk a lot about to our clients. We talk about data, everybody talks about data activation. I think it’s really about not just getting a lot of data and getting insights about the customer, but actually being able to connect them to multiple channels. So my first thing is about omnichannel data activation. You saw in one of the slides earlier about multi-platform. I think it’s really important to understand how your customer buys, they don’t buy in one channel. They buy across multiple. The way they do research, the way they engage, the way they leverage their time. If you can remove friction from that, you’ll be a winner in that category. The second point is around taking those signals and not treating everybody the same. We have got to stop that peanut butter of one campaign goes to everybody and we hope it works. We all have to understand that we have this amazing treasure trove of data now, that allows us to learn and understand the segmentation of how to monetize each one and not judge each campaign by one conversion rate. The third is really around the agile marketing concept that we’ve been talking about. The way we operate at the speed our organization can move, and developing that muscle memory, is really foundational to scaling this fast. And then finally, this is a new thing in marketing. You need new capabilities, you need new people, you need new organizational structure. We’ll talk more about what that looks like in terms of activating that at scale. So the first one let’s dig into a little bit is data activation. This is where we’re pulling together all our different data sources. Our first party data sources and our third party data sources. Stitching them together so that we can get real insights. You know people talk a lot about big data and the volume of information, this is where one of the things we see is being able to connect to legacy systems into that ecosystem, normalizing the taxonomies, being able to link them at a customer ID, is new. Most systems weren’t designed that way. They were designed in a silo, they were designed in a legacy environment. Now we’ve gotta rethink how these data infrastructures all work together. But once you enable that, the power of data is amazing and it allows you to really hit the accelerator on the next level of optimization.
I want to highlight where people mess up here. They start with trying to get the ocean of data and then personalize off of that. Just start with a puddle. Whatever puddle you got. And act on that. And then add more data to the puddle and then you got a pond, and then you got a lake, but yeah you see where I’m headed.
And as we think about this as a battleground area, I think that companies that do it well, like Clay said, start with a plan. And it’s a strategy, it’s not accidental. It’s not something that happens episodically from a campaign or things like that. I think it’s something that’s thought through to figure out how do I enhance my data over time. I think the crawl not run metaphor is a good one. Like Clay was saying, but I think you have to have a real plan to figure out how to connect the right data sources to enhance your value proposition. I mean the great news is there’s so much out there, you just have to weed through it in a thoughtful and methodical way to be able to drive value that way.
The other piece we see is companies ask a lot about third party data. I’ll tell you the winning companies are acting off of first party data primarily. And augmenting a little bit with second and third party.
And then the second thing is translating those insights once you get them into meaningful action. So as we think about tackling those signals and being able to learn how customers buy, being able to move from mass personalization, to targeted, to trigger-based. To understand that journey of how a typical customer buys is really the secret sauce of being able to leverage. Understanding the trigger points and being able to optimize each one those engagements can yield significant value of impact as you see in our typical open rate there of email. We go from that 5-15% of mass as we get better and more targeted we go from 15-25%, typically, and then we’re really triggered based on an action, where I raise my hand, we see 25-40% lift in open rates. And the brand’s messages start to resonate and drive commerce.
So what’s important on this concept is yep, more personalized more opens more click-throughs, more purchase per email sent, absolutely. But you’re always going to have a balance. You’re never, if you are great, no one’s 100%. No one’s identifying every customer, you don’t have the triggers yet. So what’s the spectrum of my batch and blast raging river of business as usual emails that are just going out, and then how am I bringing an increasing amount of those to be more personalized. But it’s always a blend. And then the decisioning is alright who gets the batch and blast and who gets the personalized. That’s where the collision management has to happen.
And then I think as we think about the funnel, this is one of the biggest opportunities that I see. I feel like most companies can kind of get the brand stuff and the bottom of the funnel humming, but it’s the everything in between I think we’re not yet doing a great job of. We really haven’t figured out and cracked the code on nurturing and being able to manage a decision process for a customer in the way they buy. We’re so excited that you’re at the bottom of the funnel and we’re pounding that with thousands of offers and things like that, but we haven’t done a good job sometimes at the middle and upper funnels to really understand the customer’s contact. And being able to track them through multiple purchases. Understanding their patterns and being able to leverage it. I really think this is the 201 301 of personalization that we’re heading into now, and I think there’s huge value at stake here that we can go after.
So an advanced player is pretty good at this. So we share a client example which is you come and do your first purchase, you make a small basket at a small discount. We always like to make it harder but you bought denim, your second purchase, so we think you’re a jeans buyer. Right so then we send you a larger discount, get you back in six months later buying more jeans, and then we want to introduce you into a new category. Right so we know you’re a jeans buyer, how can I tell you a little bit about cardigans? I don’t get to say cardigans much. So I get to tell you about athletic wear, and introduce you to new categories, starting with an introduction about what we do. Then I want to expand you basket, bigger basket on that, keep denim there, and then layer in that third category over the top, cardigans or whatever the thing is. So we see retailers that do this really well, whatever the category is, understand where they came in, deepening the relationship of what they came in for, introducing them to something new, deepening the relationship there, and the real unlock is the more categories you shop, the more occasions you shop, the more opportunities you have to personalize.
So then we talked about the acceleration rate of how you operate, and this concept of agile marketing. We talk about what we see a lot from our clients is they’re so silent right, they have all these functional roots. This waterfall approach to getting campaigns out the door. They have a lot of people that do a thing, but are disconnected from the objective and goal of the thing. And I think it’s really, as you think about moving forward of how to operate, we’ve got to radically reimagine how we go tackle this, so moving into a more cross-functional agile team, where you sit in a room, you have a common goal, and you can get stuff done. We’re seeing amazing success with this model. I think it’s the way we have to operate. I mean the development guys have been operating like this for a little while, we’ve now applying this to marketing, and are seeing radical change in the ability to capture value and change that metabolic rate within organizations.
So I’m gonna hang here for a second because I think this is the room that inspired this approach at bigger companies, I want to make sure it resonates with you all because, you know I was a better man at Gilt, we had small marketing departments, we all sat in the same room because there was a room. But we see is we see a scrum master, so a squad that can act on discrete tests to get things out the door without referencing anybody outside of that squad. It is the agile digital model applied to marketing. So the scrum master business lead type person, someone to help with the data and analytics real time in the room. By not sending it over to a data group, not sending it over to a BI group, the real times when hey, if we target people who bought jeans, in Detroit, how big is that group? Oh that’s great, leaning over the shoulder to look at it. That is where the unlock on the timing and the metabolic rate is. It’s side by side. And you actually learn a little bit. I didn’t know sequel, well I still don’t, side by side you understand the data, and you also understand some of the things you can do with it. And the data person is sitting right next to the business person who understands why they’re asking the question, it’s not just some sort of academic exercise. So then you have channel owners. What I’m gonna do with that. Search, email, whatever it is, display. Get the channels you need for the thing you’re going after. Copy, UX designer, and a front end developer. Sometimes we see those all combined. Smaller, you got a really talented front end developer who’s also a combo designer and also a UX. Awesome, right? But the idea is, everybody’s in the same room doing the same thing against a measurable outcome and a task. Right so our goal is to, one of my client’s goal, they have a one and done problem. Clients come in, people customers come in, they buy, and they never see them again. One and done. That’s the objective is to improve the one and done rate, drive down the one and done rate, get that second purchase. So that’s agile squad, very tight purpose, fix one and done. Then that team makes decisions about OK, how might I fix that one and done problem? It’s not a CMO saying “I want to fix “one and done by doing X”, right? It’s an eyes on hands off approach, that is “Hey team, we have a one and done problem, “what do you guys think are the best ways to go fix it?” And that team comes up with a set of tests and a set of ideas, and then get them out the door. Sometimes they need to go outside of the team. To do that, maybe I need to talk to the business line, like hey what are the best jeans to market? What is the best baking product to put in front of a customer like this? You guys know the product better than we do, what do you think we should put out there? I need to talk sometimes to IT, can our system do this? Legal, and risk, can I say things like that? So just this idea of agile squads running, with a central group that they can reach out to. We had a video, let’s skip it.
We’re gonna get the yank here.
It’s a good one though.
We can tease it.
It’s basically just the logo.
Click here if you really want to see it.
They don’t let us work with clients, we just do stuff like this.
I think as you walk through the process of getting the model right, I think it’s really important to align to those KPI’s and getting the team and everybody focused, it’s amazing when you start removing those hurdles and people start to work together, you can start to scale where you do these very formalized, you know, much like in development where you have planning and stand-ups and daily activities where you look your colleague in the eye and you say today I removed this hurdle to get this campaign out the door. It’s really liberating to see, and we’re seeing the cadence of these things from one to two three weeks, maybe four at max, where you’re running sprints at a specific goal, and the results are really starting to come back, and the learnings of those really allow you to scale fast.
So what happens is you get a layer cake type approach, so you get, so call it two week sprints, and those sprints got those tests out the door. Sometimes those test can be measured in a few days, sometimes they take more time to get the sample you need. So let’s say it takes three or four weeks for the results to come in, but you got those out the door. Well then you start getting the next wave of sprints out. So you kind of have a layered, so as those tests go out, and as those go out, these other tests start to come back in. And so in the market, you can have anywhere 8, 10, 20 as you get going, tests that are in the market, depending on and then, you’re starting to see results that are feeding back in. So you can imagine three or four tests that are live, and then you’re acting on the results as they come in. And you can imagine, probably hence the venue and the conversation, it gets pretty complicated. Once you go beyond a couple of agile squads working, the scaling gets really tricky and the collision management gets pretty tricky.
So we talked about the last bucket which is new capabilities. And people think that you get the technology and it just automatically does it for you. I think there’s a couple things to consider there. So the idea is that I think there’s a combination of technology that you definitely need as a key enabler in the system. But you have to enable a process and people around it. And I think it’s really important to think through the organizational structure of that, understanding how to do that collision management, understanding how to do the segmentation, how to do the inputs, how to enhance that environment and operationalize at that scale requires a different setup than you probably have in most organizations today. And a lot of this is new. So it used to be sitting in IT typically, where oh we run the systems for you, press a button. That world’s changed where marketers really have to have a seat at the table where they control turning those levers and dials, and being able to scale and operationalize them to be able to drive the impact that’s needed.
Yep I think tactically, what has changed? In the room, you can pull the data, and in the room you can manage the routing and decision. In the room. You’re not sending it to somebody, like I’m making the campaigns and I’m understanding what I’m gonna do and I’m actually, people who manage the hands on the keys are in the room. So I think we’re both old.
You may be older than me.
So marketing used to be an art. This is a group of people who are very creative, making art, switched to a craft about 20 years ago. Then we have content, different people. I used to work at an agency, so you have planners, suits, and creatives basically. And so then you go to mobile, you see these channel-focused people, right, and I think in some other room, you’re gonna have people who are channel-focused. Right so it’s I do mobile, I do social, I do UX, I do product. What we’re seeing shift is the collision, right of functions, like Robert said, we’re never involved with marketing really before. Which is I’ve got an analytics team, a digital IT team, and then the business owners, but they always just talk about marketing is over there. Right, those guys. And then marketing used to point at them as those guys being a problem too. Getting them into the room, and then as you get your data scientists, your solution architects, and your analysts, marketing is really a functional translation layer to say I have this customer problem, and I’ve got these different capabilities that I can pull from, and then I know what I can do in social, I know what I can do in my creative, I know what I can do with my email. This marketing’s job is to actually hmm, how might I take this data, plus this sense of capabilities, and do something with it functionally and translate it. All this gets pretty complicated. And when it hums, it’s a really beautiful thing. It’s a combination of tech, gorgeous and glossy for the consumer, and it’s automated and scaled. It doesn’t usually start that way. For the consumer, it’s important that it looks polished, right? It’s important you get their name right. If you’re going to try to personalize it, get it right. Hi, nice to see you Robert. Thank you for coming in last week. Two bits of data, just make sure they’re right. The consumer’s gonna go yep, great. The back end may be a total mess. Right, it’s gonna be OK I have to manually pull that from the system, it’s gonna be a real pain in the butt to get that test out. But what you want to get is get the metabolism used to running that test, get used to trying those things. And then see the lift. And then you’ll make the decision of whether it’s actually worth automating it. You’ll see big companies try to build perfection first, first just like see if it’s worth doing. If this concept is worth doing, do it on a small scale, do it with sticks and bubble gum, and then go from there. And then as we see the spectrum of marketers move along that journey, it’s starting at this concept of broadcast. I’m sure no one in this room is at that spot. We see other companies like no I do personalization, what they really mean is they have some macro-segmentation of the marketing, that they’re smashing up with you know Nielsen data or whatever. It’s great, it’s better than the former. We start to see micro-segmentation clusters, 70 segments not 7, and then at scale, I have a one to one, we used to do this a lot a Gilt, Gilt they send out millions of variants of emails on a one to one basis. And then what we see from a dynamic personalization is, it’s not just the channel that’s like that, it’s across all your channels that are like that. And it’s happening in real time with tech. So that’s kinda what we see. It’s a journey. The key I think for this room is the operating model. Like you guys have got the tech, or you got the data, I hope it feels like its a little bit.
I’m inspired by what’s coming next, man. There’s so much opportunity in taking personalization to the next level and you guys are leading the way. It’s a really exciting time.
Any questions, or?
Do we have time? I don’t think we have time.
[Staff Member] Take some questions while I bring in the next guests. Group A can always ask them.
That’s agile, man.
One of them could be, why did we wear the same outfit, that’s a fair question. We found that out this morning.
Can we get a selfie? Got to get a selfie.
[Audience Member 1] I’ll repeat it, yeah.
[Audience Member 1] So the question is, and I’ll make sure I heard it correctly, which is the organizational model we propose seems offsite oriented as opposed to onsite oriented to the close the deal. Right how is the translation between those? I’m not quite sure I fully understand that.
Think I do.
[Audience Member 1] Yeah.
So is merchandising and landing pages included in that? So the short answer is yes. So what we see is companies pick a problem that they want to solve, so one and done, how might we best solve that problem? Might be with merchandising and landing pages, making sure that they know about this thing. It might be better with email. So companies tend to focus on what do I need to do to solve the problem, give them an objective measurable outcome, and then let the team decide what they want to pull in. I can’t think of anything short of broadcast media that we haven’t seen pulled in. Right sometimes landing pages but it’s hard to pull in radio, what are you gonna do with that?
I think the way I think about the question is that organizations are making a decision point of how to organize, to Clay’s point of picking a problem. Am I picking a pod and aligning against a specific funnel stage, a specific buying situation, is it buy flow, is it website, is it upper funnel, middle funnel, bottom funnel, one of the pivots that we’re also seeing though is organizations are suddenly aligning those pods at a segment level. SO I have a financial services client that’s very thoughtful about a specific financial segment where they have an end to end team responsible for the entire journey. I think these are the type of playbook decisions that organizations have to figure out where they’re going to win. I think the trap is not to get enamored with one specific area. Because oh my god I want to optimize my website and make sure my converts get that, but make sure you look at the full spectrum of how the customer interacts and then align your organizational resources to manage the full picture.
[Audience Member 2]
Who has a lean team?
[Audience Member 2]
That’s a great question. So the question is, let’s say you’re just starting out. And you’re just leaning into digital for the first time. How as the head of the business or the head of the marketing group, would you advise structuring, right, to go get after it? Should it be build a team of generalists who are just smart and can figure it out, or build a team of specialists against a problem that you have? I’ll give my stab at it, which is I’ve never seen a team go wrong by staffing with people who have solved the problem that you have before. Right they may have solved it in a different vertical, they may have done it in retail and you happen to be in banking, they’re gone after a new segment, or you may have a problem with customer acquisition costs in a retail business are way too high, and you’ve got to get them down. And whether it’s fashion apparel going to discount apparel, what’s the problem you’ve got to solve? I would say find people, who have solved that problem before. And then channel owners are generally pretty specialized. Right so if you’re going to have an email person, or a loyalty person, that stuff changes so much that it’s important have specialists. Generalists tend to be more in them middle, but those important to have that know deeply what they do. So I would just say athletes are great, but you need people who are porcupines or hedgehogs they’re good at one thing you know, but they’re pretty good at it.
I have no idea what he’s talking about.
No that’s a good one, think about it.
The one answer that I would give is a little bit of a cop out, but you’ll like it I think I hope.
You’re a consultant.
It’s true. The first hire that I would make is the person that’s gonna advocate and know my customer better than anybody. And that might be an analytics person, it might be a channel person, it might be a strategist, but you’ll know who that person is. I want them to understand the customer better than anybody and be able to connect the dots on what we need to do. And I’ve seen it in a number of different people manifest itself, and I think that’s the most important place to start, cuz that’s gonna drive the work and that’s gonna drive success.
That’s a better answer. Thanks guys, appreciate it.
McKinsey partners, Clay Cowan and Robert Tas, share insights on how to use real-time data to deliver superior experiences and introduce a concept to help companies 10X their personalization velocity.