Interviewer: Today I’m very pleased to welcome Daniel Kehrer, VP of Marketing of MarketShare. Daniel is in charge of marketing, communications, content, thought leadership and demand generation at MarketShare. Some of the things that Daniel does, which is why I’ve invited him here, is that he likes to inform, educate and create actionable insights about big data, advanced analytics and marketing through a clear and engaging multimedia content. Hey, that’s a podcast right?
Interviewer: And he has a unique ability to translate PhD and data scientists speak into plain English. That’s something I would love to hear. He’s a nationally recognized business thought leader, a blogger, a social media and big data influencer, a Forbes contributor and a columnist widely cited by major media such as the New York Times, MSNBC and many others. So, what does MarketShare do? MarketShare offers cross-media analytic solutions for global marketers. The company has been called out as a leader in the industry by Forrester Research; and a cool vendor by Gartner; and has enabled more than half of the Fortune 50 companies to dramatically improve their marketing effectiveness. MarketShare focuses on helping marketers figure out how much to spend, where and how to spend it and the results those dollars will deliver, specifically, and this is the key, how those dollars will contribute to revenue. So, welcome Daniel really pleased to have you here.
Kehrer: Thanks Glenn I’m glad to be on the show thanks for inviting me.
Interviewer: You are welcome. So, we talked a little bit earlier about several topics and one that really rose to the top is the topic of attribution. I’d love to hear some of your thoughts about it, attribution in marketing.
Kehrer: Yeah absolutely, attribution a very hot topic right now in the analytics field and big data field, and it kind of comes out of the digital space. But, it’s important to frame up attribution. If advertisers or marketers could land customers or get clients with a single perfectly crafted ad, or one message you wouldn’t really need attribution right, because you wouldn’t have to attribute what’s happening, but that’s not the real world. We live in a very complex and kind of fragmented ecosystem and it’s getting more fragmented, more complex all the time, so the influences on consumers or in the B2B realm occur in multiple ways. And so, this is a huge, huge challenge for marketers, not just digital marketers but marketers in general, so that the so called consumer path to purchase becomes increasingly complex and it has multiple steps.
Kehrer: Attribution is all about assigning value to those steps along the way so that you know what’s happening, and you can then shift and allocate your resources in proper places, but this is not easy.
Kehrer: But, you’ve got to have accurate attribution and planning and allocation in order to execute well on where to allocate your marketing dollars in the future, but the field is full of futility. One of the things that we’re looking at now and has become commonplace is this last click attribution. That’s kind of the old way of doing it.
Kehrer: So, you give all the credit to the last click and that’s obviously wrong.
Interviewer: And that’s because you don’t know what else to do right?
Kehrer: Yeah, you don’t necessarily know what else to do, or you assign equal value to all of the different touch points, and that doesn’t really work either; or you’re simply measuring – and this is something that we talk about all the time, you’re only measuring digital. So, you’re only measuring essentially in a digital silo, so if you’re doing digital attribution and you’re deciding where to allocate your marketing dollars across the entire spectrum based on your digital attribution you’re missing something.
Kehrer: You’re missing the offline component, and you’re missing the non-media driver component. So, this is where big data comes in, because now with big data you can get information across not just all of your digital drivers, but your offline drivers as well, and other macroeconomic factors, maybe the weather for example, or the economy, job growth or non-growth. Those things all impact how people decide to do something, to buy or not to buy.
Interviewer: Right, right, more snow shovels at a certain point depending on the weather.
Kehrer: That’s right.
Interviewer: Has nothing to do with my marketing.
Kehrer: That’s exactly right. So, what’s kind of happened in the attribution field it’s still kind of coming into its own, so I refer to it as attribution anarchy almost, because everybody looks at attribution through their own particular lens; an agency for example, or somebody who is just an online store, or digital marketer, or a big company. That’s that single lens view or that siloed kind of view is what leads to an incomplete view and therefore, inaccurate attribution. So, you’re shooting yourself in the foot.
Interviewer: So, give us a sense for – given we now understand this problem how does one go about addressing it?
Kehrer: Well, first recognize what the flawed approaches are, kind of a lot of the traditional approaches, measuring digital in a silo, and then applying inadequate tools for the job. So, what does that mean? Maybe you’re trying to just do this with spreadsheets or by looking at small amounts of data or sampling data. And/or you’re failing to properly account for the non-media influences around the journey, or you’re simply looking backward at what’s happened in the past. That’s another error that our traditional attribution is making, because if you’re deciding what to do in the future based purely on looking at what happened in the past that’s not the right way to do it either, because the future may be different. In fact, it’s not a might, it will be different.
Kehrer: So, that’s where the science comes in here Glenn. And MarketShare has probably one of the highest ratio of PhDs per capita of employees of any company around figuring out these things. So, these are advanced, predictive models that are built to handle this big data. And those predictive models account for all of these different things and then are able to look forward and with far greater accuracy than ever before predict what you should do in the future and what’s going to happen in the future.
Interviewer: There’s a phrase that marketers use, marketing mixed modeling, and I’d love to hear, if you have one, an example of a company that has used that to improve their marketing results.
Kehrer: Right, okay, so yeah Glenn, marketing mix modeling is kind of a traditional component of advanced analytics. It’s been used by companies for a long time, but again, what’s happening now is marketing mix modeling is entering a completely new era, and it’s essentially going away as just a standalone type of thing. So, this is an area where MarketShare has done a lot of work in for a lot of major companies with optimizing their marketing spend and being able to model what they do predictively going forward. But, what’s happening now is this is being combined with attribution. So, in our world it’s kind of the best of marketing mixed modeling combined with digital attribution to create this new hybrid, kind of holistic view of what’s going on, and that’s what really hasn’t existed before in the space.
Interviewer: Okay, so yeah, tell us an example.
Kehrer: Well, I think one of the best examples is a company, USAA, which was the winner of last year’s marketing analytics leadership award, which is an award for companies that are doing pioneering work in the analytics space. And Forrester did a great case study on USAA. So, in USAA’s case, they’re a big insurance company, the old cool tools couldn’t keep up with what was happening with customer behaviors that they were seeing. So, now they had a long, successful history as kind of a traditional direct marketer, but as that strategy changed and their target audiences moved across into more diverse media landscape they needed a more powerful approach to measuring what was going on, and how consumers were making those purchase decisions that we were talking about before. So, they went out and looked for a vendor, and in this case it was MarketShare, it was us, and they assembled a cross functional team inside, so combining marketing and finance and analytics to deliver the requirements that they needed. So, this was a kind of internal partnership that they developed that was really pioneering. And that’s starting to happen at a lot of other companies to deliver better business insights that are connected to revenue based on analytic results. So, this is informed the marketing strategy now of everything that happens at USAA, and they’ve been able to quantify in very precise terms through the modeling and through running war games scenarios on what to do or what not to do, and to see the kind of return that they’re getting on their marketing investment.
Interviewer: So, talk a little bit more about the war gaming and the predictive analytics.
Kehrer: Oh, it’s very, very important. So, this is one of the things that MarketShare’s own revenue Cloud technology can do. It offers the ability to for somebody to go in and run these different scenarios. We have some clients that are really power users and they’ll come in and run just multiple scenarios, and you can do them on a real time basis. You can see the impact of, well if we spend here we don’t spend there; we shift up here; we do more digital; we do more social; we do more offline; more television; you go more on Twitter; you can adjust all these things and see what’s going to happen predictively before you spend the money. So, that’s become a huge, huge component and one of the great values of this type of technology to these big brand marketers.
Interviewer: Wow, that’s really, really powerful. So, you have a predictive model on what the results are going to be for your marketing spend?
Kehrer: Exactly, and this can be as sophisticated or simplified as you want inside of these technology platforms. You can add variables or put in your constraints into the system, because a lot of marketers have constraints they have to spend certain amounts of money in certain areas, or they can’t spend more than x amount in another area, so you can factor in and program in those constraints in the models and run scenarios against specific campaigns. You can do it on a regional basis; you can do it for certain products and then add others products and see what the impact is of one product on another product. You’re doing all this in the technology before you’re spending the money, so the net impact is very, very powerful when you then go out and spend the money in the real world and connect that to business outcome and then see what it does in terms of boosting your revenue.
Interviewer: Wow, wow! So, let’s talk about why all companies don’t do that. When we talked to clients we talk about change management being one of the biggest obstacles to enabling people to take advantage of things like what you just described as predictive modeling. Can you talk a little bit about how that fits in from a thought leadership perspective, what companies they should be thinking about adoption of these capabilities?
Kehrer: Absolutely, so it doesn’t happen in a lot of companies simply because of inertia in a lot of cases. Some companies have become much more data driven. They have recognized analytics and big data as absolutely vital to their success and competitive success going forward in the future. And some companies are simply further along that curve than other companies are.
Kehrer: We find that there’s a wide disparity of sophistication levels, even among major global brands in terms of applying big data analytics to every day decision making within the company. And especially in marketing organizations, some marketing organizations have changed dramatically you know. They’re partnering with the CIO and the CFO and they’re becoming much more data driven, and the CMO knows all about analytics and they’ve got digital people on staff, and they’ve got a lot more analytics people on staff. And other marketing organizations are still kind of stuck in the past and running things in traditional ways. So, those are the ones who are trying to play catch up, and still running analytics on spreadsheets or something like that which just isn’t going to cut it in this kind of world going forward.
Interviewer: Right, right.
Kehrer: So, the ones that have been successful at it have realized a few things, probably four or five things. So, one is that you have to have this kind of forward looking bias, so you can’t just be looking in the rearview mirror all the time.
Kehrer: And another thing is they realize that their own data isn’t enough, just the data you have within your own company, so you need broader industry knowledge. So, one of the things MarketShare does for example, is benchmarking. So, because we work with a lot of clients we can aggregate observations of other company’s successes and failures and put those into the data stream.
Kehrer: So, that kind of thing so that these kind of data partnerships with these other places and vendors and data outlets to supplement your own data is really crucial. And again, that’s what big data can do for you. And then the ones that are kind of doing best practices are realizing you have to track the entire purchase journey, and you need to have sophisticated models that really can get very, very granular, the bottom up kind of thing; and then marry that with what we call the top down which is more the macroeconomic view.
Interviewer: Right, right. Well, tell us one last thing here. Where do you think the future is going to be for marketers? Let’s talk about some of those advanced marketers and what they’re doing and how they’re pushing the envelope?
Kehrer: You know, the future looks very, very bright and it’s happening very, very quickly, so this entire field of advanced marketing analytics is changing dramatically. So, it’s like we were talking about before, marketing mixed modeling is moving on to something else. Digital attribution is moving on to something else. What’s happening is these things are combining. They’re combining in the Cloud into what we call the 360° view of your entire marketing ecosystem.
Kehrer: And so, that’s taking place through this technology. And the brand marketers, the big global brands that we work with are recognizing this, and they’re bringing these things together themselves and working through these kind of institutional adoption roadblocks that almost everyone does have to some extent, some much more dramatically, so that they can take what’s coming out of this technology, these analytical insights, and really put them to work. Because, if they don’t – big data doesn’t mean anything and analytical insights don’t mean anything unless you’re using them to influence business outcomes, and that requires institutional adoption component that sometimes requires changing your organizational structure; changing the way you think; changing how different departments work with one another, how they communicate with one another; and how they put these things to use. And the ones that are able to do that most effectively are the ones that are leading.
Interviewer: Well, it sounds like a virtuous cycle where if I am a CMO and I can become more adept at using analytics now I am more adept at proving the correlation between my investment and revenue, therefore, I get more attention and value at the C-Level with my colleagues, therefore, I get more funding to do an even better job going forward because I can prove the impact to the organization. So, it sounds like a very virtuous cycle.
Kehrer: Well, there you go. You just nailed it right there Glenn. That’s exactly what’s happening. The CMOs are now, for the first time in a lot of cases, able to prove the value of what they’re doing. And that’s an extremely powerful message in the C-Suite and frankly in the boardroom, because the CMO now has – the marketing organization now has a page in the boardroom book. Where it was more smoke and mirrors before, or maybe it was considered to be creative or seat of the pants, now it’s all documented. It’s quantifiable. Here is what we’re spending on marketing. Here is the precise impact that it’s having on the bottom line, and this is making the influence that CMOs have in their organization and with the rest of the C-Suite. And so, this is one of the other things that we do on our own marketing side, when an organization gets a new CMO we talk to them about hey this is a perfect time to prove what’s going on with your marketing quantitatively so that you can show these numbers to the board and to the CEO.
Interviewer: A very compelling argument for getting good at using analytics, especially on the predictive side. So Daniel, thank you very much. This has been very enlightening.
Kehrer: Thanks for having me Glenn it’s been a pleasure.
Interviewer: Alright talk to you soon.
Kehrer: Alright bye.