Michael Mothner is the founder and CEO of Wpromote, a global online marketing, SEO, PPC and social media firm. We spoke with him about what makes his company tick, automation systems, and the challenges that come with working with data for a living.
1. Wpromote uses content, creative and digital channels to help clients acquire customers and grow lifetime value.
2. Mobile traffic is up exponentially. When it comes to understanding the impacts of different marketing initiatives and media buyers and so forth, understanding what’s happening in the mobile space is really important.
3. The key to making or extracting value from data is knowing what to ask it.
4. Technology can do the heavy lifting for us, but if we want to get more valuable insights, we need to practice more critical thinking.
5. Michael invests time and funds into three areas of his business: the core business budgets where there tend to be certain expected outcomes and consistent ROI; branding budgets that don’t necessarily yield immediate ROI, but are necessary for long term exposure; and the testing bucket, where the goal is to test new innovations. These initiatives don’t always win, but it’s necessary to designate time and money for ongoing innovation.
6. You can differentiate yourself from companies that have a large breadth (i.e. Amazon) by positioning yourself as a company with great depth of content that has emotional appeal.
7. Create “content for humans.” If you start creating all your content with the lens of what Google wants, it dilutes the strength of your brand.
8. To a certain extent, you can get in trouble by trying to stay up on trends (aka “the new shiny things.”) A lot of times, they can be a distraction just getting in the way of what’s actually occurring. Stay up on what’s happening, but don’t read too far into it.
ML: Thanks for joining us today, Michael! First question: If you had to describe to a stranger on a plane what your company does, what would you say?
MM: We’re a digital customer acquisition agency, so we use content, creative and digital channels to help our clients acquire customers and grow lifetime value. We’re very performance-based, and the channels that we touch are paid search media, social advertising, organic search and content marketing and emails. Analytics help determine how to drive sales, increase future lifetime value, optimize mobile purchases and increase cart value. We work with any interaction that’s measurable and optimizable, like online transactions, in-store customers, email leads or phone calls.
ML: You’ve been on the Inc. 500 list a total of seven times now, which means that your company is considered to be one of the best top places to work in the United States. What makes you so unique?
MM: We have a pretty unrelenting motto that started out as an internal joke, but now it’s kind of actually a thing. As a company, we don’t want Mondays to suck. I want to come to a place where I love what I do and the people that I work with. But that mindset doesn’t just apply internally. If we do a really great job for clients, they look like heroes; their business grows; they sell more products; they impact more people; their Mondays don’t suck. It might sound like kind of a trivial concept, but I think it speaks to both our passion of what we do and also that we don’t take ourselves too seriously, either.
ML: So, you started Wpromote in 2001 in your dorm room. After 14 years running the company, what do you know now that you wish you knew back then?
MM: Ha. Everything! I guess I wish I had known the importance of mutual trust and transparency with employees and clients. I think I’m just now realizing how valuable those things are in terms of giving and getting the most from the people we promote and the clients we work with. I also wish I had paid more attention to technology and progression, which I tended to prioritize less in favor of more granular business stuff. Things are always adapting and changing in this industry; if you take a hiatus for six months and come back, you’d better go re-learn everything, because the space has almost certainly become a different world.
ML: Since it’s still the beginning of 2016, there are tons of different articles about digital marketing resolutions for this year. Do you have any digital resolutions?
MM: I want to continue to figure out what certain trends mean and to see where our clients, technology and strategies fit into those trends. I’m specifically interested in mobile, since we’re seeing it across every vertical that we work with, and mobile traffic is up exponentially. When it comes to understanding the impacts of different marketing initiatives and media buyers and so forth, understanding what’s happening in the mobile space is really important. With people simultaneously using devices, platforms, social media, search engines and content, it’s a really complex journey.
ML: I recently read your article about marketing automation systems technology. Clearly, there’s a common trend of investing in modern tools to get predictable numbers that feed into marketing automation, which then feed into a bidding platform. Obviously, the promise is good and enticing. Are there any challenges that you see with this process?
MM: One of the reasons that I think we’ve been successful is that, really early on, about 6- 7 years ago when we started building our technology to manage bids and keywords, there was a big push toward this kind of algorithmic solution. That is, for example, if I plug in the inputs and my goal outputs, there would be some magical algorithm that would give me the optimal results. And what I think we realized correctly early on (which I believe to be one of the major hurdles that good marketers have overcome) is that messaging and content have to be more human. When you’re speaking to humans, you’re telling a story with the content; you’re talking about a product; you’re working to create emotional resonance, and those things aren’t going to be solved with bid automation. It might be a great tool, but it doesn’t provide an understanding of what makes people click on one ad versus another, or what inspires someone enough about a product to make them purchase.
ML: So, there’s a ton of data out there, and we seem to be drowning in it. Do you think that’s because there is so much of it, or is it because we’re really not sure what the right data is?
MM: The key to making or extracting value from data is knowing what to ask it. If I don’t know what to ask, then I can’t possibly get the answer that I want. Understanding what problems you’re trying to solve and then using the data to help solve those problems is probably more challenging than the collection of the data in the first place. Data for the sake of data that looks back and tells what happened is nice, and it can help wrap up what I already know. But that’s only so valuable. What I want to be able to do is change my strategy based on what I learned so that I’m impacting what’s going to happen next. I think a lot of the time, data can be your own worst enemy because there’s so much of it that it’s hard to make sense of it all, and so it’s easy to fall back on your safe place of, “Oh, look at real time visitors; I feel good about this; I know what it means.” And at that point, you’re really not getting any value. That’s the type of data that won’t make you change what you do, and it’s a waste of time.
ML: So, I was interviewing a TED speaker who was talking about big data, and we were trying to figure out why people get stuck on getting the right data. And she pointed out that technology can do the heavy lifting for us, and that’s why we’re comfortable. However, we want to get more valuable insights, and we need to practice more critical thinking instead of relying so much on a computer. But critical thinking is not something that we tend to continuously do as much as we need to.
MM: Yeah, the secret sauce really isn’t in the computing power or the data collection; it’s the analyst’s experience, intuition and insight that ultimately determines what to ask the data or what hypothesis to make.
ML: There are so many different tools and marketing channels out there right now. A lot of marketing executives are innovators, but they’re also pragmatists. So, how do you innovate something new when it hasn’t been proven to work yet?
MM: We have to make that argument pretty frequently. We usually turn innovation challenges into business cases that we can test. We try to dedicate a portion of our budget and mental resources in advance to test in new innovative spaces. We always invest heavily in our core business budgets where we tend to have certain expected outcomes; that’s what drives the train. And then we have a budget for branding that doesn’t necessarily yield immediate ROI, but it’s necessary for the long term exposure. And then there’s the testing bucket, where the goal is to test one of every X things, and either we get a winner to move onto further testing and innovation. You might not always win, but you need to at least designate time for ongoing innovation. If I don’t make the time, I’ll never do it.
ML: When I was reading your blogs and articles on Inc., I noticed a major recurring concept you’ve pioneered that I particularly liked called “intuitive search intelligence.” Can you tell us a little bit more about the concept?
MM: Sure; so, the idea is an extension of this very simply paradigm in which you need both technology and human intuition. For example, machines exist that can tell whether, say, ad A will outperform ad B. The algorithm for this machine is very good, and it’s much better than the human eye at determining which ad will perform better. There is nothing wrong with a machine performing this task, as it’s much more efficient and reliable than a human result. On the other hand, as humans, we ask a lot of questions that can help us take things further. Why did ad A perform better than ad B? What would ad C look like, and how would we make it better than both ad A and ad B? Those kinds of questions can really only be answered by human intuition and experience. Asking why and hypothesizing an answer relies on that intuition and then uses it to drive the follow-up questions that can get real, thorough answers.
ML: So, how do you think organizations should structure some of their analytical reports on dashboards? Right now, dashboards just show a bunch of data points, and there’s nothing intuitive about the experience. Do you rely on certain dashboards? And, if so, what makes them special to you?
MM: We try to keep the fundamental dashboards or scorecards down to the bare bones; these are the 3, 4 or 5 metrics that drive the business. These have to be chosen carefully. Site visitors is usually an obvious one that people tend to watch, but it’s also not very telling. I don’t know the visitor quality; I don’t know if they’re buying; I don’t know where they came from; I don’t know how to use that information to change strategy. It’s important to have a meaningful discussion of what you’re actually looking for. How did we do last week? What are the couple of metrics that are going to help actually answer that question? And what are the metrics that will help us guide how we’re going to change the strategy for next time? It might be a really simple dashboard, but it definitely takes some thought to get it right. This strategy forces you to not just pat yourself on the back for one metric; you know what I mean? I’ve seen plenty of dashboards that have a ton of metrics going on that are easy to cherry pick. You can use those to tell whatever story you want. And when you give yourself that freedom, it allows you to be kind of lazy as a marketer, and it doesn’t force you to be hard on yourself in answering the tougher questions.
ML: So, let’s talk more about metrics. One of the metrics that I’m a huge fan of is lifetime value. Most organizations want to measure lifetime value of their customers, but they tend to struggle with how to define it. Do you have an approach or methodology that could be useful for those companies?
MM: It’s interesting; I‘d say that 90% of companies don’t know their lifetime value, and the ones that come to us with this issue tend to be very smart. Even just coming up with a consensus on what lifetime value is and how to measure it is a starting point that most companies have not gotten to. It’s a more sophisticated view that budgets have historically not been able to support, and we haven’t had the data to figure it out until recently. When organizations go about measuring lifetime value, it starts with a pretty open discussion on what metrics need to be monitored and at what frequency. What is the product or service, and how often will customers engage with you as a company? Then, you have to find data to build a model around the answers to those questions. And to take it further, you can use those questions to then guide our marketing decisions. After looking into all those metrics, you might discover that your lifetime value is huge, but you don’t necessarily have the ability to spend all that money today since that value is spread over many years. And then sometimes, your lifetime value turns out to be lower than what you thought, and your business will be less sustainable over time based on what you’re selling now.
As a company, we’re spending considerably more time, effort, money, budget and marketing initiatives for our clients now than we did several years ago. And we’re spending considerably more than before on initiatives to increase the lifetime value of current customers vs. getting new customers through the door the first time. You can spend a lot of time and money on marketing to existing customers through email marketing, social engagement or content marketing, etc. But it may be far cheaper than actually going and acquiring a new customer if we can increase the frequency of a purchase from once every 12 months to once every six months.
ML: So, it’s clear that companies who figure out how to do this well will win. Yesterday, I was interviewing the editor-in-chief of Internet Retail, and he touched a little bit on this. He was saying that companies really have to step it up, especially in the e-commerce space, because otherwise, Amazon is going to take them out of business. So in your opinion, if an organization is small and is competing with major competitors, what does it really mean not to out-market someone, but maybe outsmart someone?
MM: We found that a significant portion of our clients compete with companies like Amazon. And a huge factor of your success comes down to the story that you’re telling. For example, we work with a company called PetFlow that sells dog food. Walmart and Amazon also sell dog food; it is a commodity. But PetFlow has an advantage because their brand tells a story about how much they love your pets. Story-telling is the key to a winning strategy. It doesn’t have to be a story with a beginning and an end, but it could just be an emotional connection that the brand fosters through the messaging on its website or packaging or other materials. And if you’re good enough at the story-telling aspect, you can build loyalty that trumps the convenience factor of “everything stores” like Amazon. You’re never going to match Amazon in the convenient distribution centers, free shipping and easy access to credit cards on file, but you can potentially beat them out with an emotional connection through compelling content. We have clients that out-rank Amazon for particular products because they really do have better content. Amazon is incredible in many, many ways, but it’s great in breadth, not depth. So, I think that’s where the opportunity is. If you try to beat them at their own game, you will not win.
ML: You mentioned the word “story,” which is an interesting word these days because everyone is saying that you need to tell a story to win big with your customers. What does that really mean to you? How should organizations start thinking about what their stories are?
MM: So, I use the term story loosely. It’s all about what the brand stands for. You could be engaging with the brand and its material on any device in any number of formats, but the feeling you get from the content should always be consistent. For example, we all know that Apple tells a story, right? There’s a look and feel and vibe to their products, and there’s a story that’s very defined, even if you can’t put your finger on it. The story of your brand is more important than ever before because so many things have become commoditized. So to break out of that, you need to tell a story that resonates with your user or potential user.
ML: And to follow up on that, stories are often part of content, right? In your opinion, what makes good content, and what types of organizations are great at doing content these days?
MM: We really believe in “content for humans.” If you start creating all your content with the lens of what Google wants, it dilutes the strength of your brand. Google might reward you for creating the type of content that it favors, but you end up with a no cohesiveness; you’re not telling a story about your brand anymore, and that Google-optimized content suddenly becomes a different initiative on its own. You want to create great content that is relevant and shareable. Content for content’s sake is where you get a lot of mess, noise and lost value. Quality over quantity is huge.
ML: So is there a certain content calendar schedule that you recommend your clients stick to?
MM: It really depends on the client and the brand. Do you want your brand to be a thought-leader? Do you want to be a resource? Do you want to be funny? Who you are should be a huge determiner of what content you put out. You should ideally create a calendar of the type of content you’ll have, where it will live, and what purpose it serves for your brand. This strategy will help you think strategically without generating content for content’s sake.
ML: Things change every day in my niche of analytics; there are new companies that are starting up every day in my field. I think I heard that 100 new analytical startups were started in 2015. How do you keep track of this? What do you do to really stay on top of all the changes that are taking place in a digital space?
MM: You know, to a certain extent, you can get in trouble by thinking that staying ahead is looking at the new shiny things. A lot of times, that can be a distraction just getting in the way of what’s actually occurring. For example, a lot of times someone will ask what the next big thing is, and I might reply that I don’t know. But, I want to figure out what the next 10 small things are, because those are much more likely to be incrementally actionable.
ML: So how do you factor in context? There are so many simultaneous things going on in the digital realm that you can basically find a way to correlate completely unrelated things (like seeing a correlation between the weather and the number of downloads for a certain app, for example). How do you solve this problem of faulty correlations?
MM: Yes, there is an infinite amount of content. Scientists also face these types of challenges with experiments; if they wanted to, they could easily shelve results that are uninteresting and publish results that are interesting (and some do). It’s the same thing with the type of data that you and I deal with. For us, in a world that’s not simple, we try to keep it as simple as possible. I try to be aware of both micro trends and macro trends and find the most logical conclusions in the data. But there really is so much of it. A lot of times, context can be used to explain away anything.
ML: Last question: do you have any go-to resources for doing digital research and seeing what’s taking place? I know you’ve mentioned you’re very careful about how you direct your strategy and try not to follow too many shiny objects. But are there any resources that you personally pay attention to, like publications or apps?
MM: You know, we certainly listen to what Google says, and then we try to read between the lines. We’re not exactly getting news per se, but you kind of have to in the world of search. And then you have to then overlay what we’re seeing in reality and compare the two. I do absorb all the standard tech media and I stay up on those “hot and not hot” things and the trends and apps and etc. But I’m also very careful to not necessarily read too much into those things. We have to be careful of how the data is being used in the media, like we were talking about with false correlations. We follow Internet retail; we follow trends in analytics and the migration of usage to mobile apps and things like that from typical news sources. We just take it all with a grain of salt.
2. More Articles by Michael Mothner on Inc.