Convergence of Finance and Marketing is a two-way avenue

For over a decade now, if not longer, marketers have had a desire to be line financiers -- create sophisticated mathematical models to predict marketing campaign success, make marketing decisions instantaneously with little human intervention, and to continue dehumanizing their market. The latest iteration in this effort has been the move to programmatic buying. (the "go to" word of 2013) What has been happening at the same time, however, especially with the market decline in 2007/2008 has been finance moves to be more like marketers. Late last year, while going on vacation, I decided to read the book by Alan Greenspan, the former chairman of Federal Reserve, probably the person most responsible for the irresponsible ways of the 2000's market bubble and bust. He wrote the book, "The Map and the Territory" to, pretty much, justify his tenure at Federal Reserve and to analyze why all his grandiose plans failed the economy. In the book, Mr. Greenspan concluded that the reason why he and his friends could not predict the markets, was simple -- human behavior. He delves into behavioral economics, relatively recently popularized by Chicago economics professor Steven Levitt and New York Times journalist Steven Dubner in their 'Freakanomics' blogs and books. The premise is extremely simple, everything is math, but with some human behavior. If this sounds familiar, but different to marketers, you are right. Marketing has been the polar opposite -- all human behavior, with some math. Over the past few decades, however, marketing has been moving in the realm of big data, programmatic -- attempts to 'scientize' the field and algorithmize human behavior. This, many marketers feel, would bring them into finance territory -- efficiently generate monetary valu, and more selfishly, make their services more expensive. At the same time, recent financial crises, first in the late 80's, then in the late 90's and then in 2007-2008, has taught financiers and economists that there is something to finance than just efficient markets. It is the human element that "Mad Men" have been in charge of for the past three quarters of a century. The answer lies somewhere in the middle, in understanding the linear, yet chaotic, prejudiced human behavior and logical, measured and scientific econometric approach. What we need is a Spock, a combination of human, emotional, unpredictable mother and logical, process-oriented, historically knowledgeable father. For marketing and finance fields to continue to succeed, it is not enough to refocus marketing on science, to push everything to machine learning and cold, automatic decisions; and it is not enough for economists to add some human modeling into their equations. A mind meld needs to happen between a scientific selections of facts and a human understanding of elements and decision making to humanize stock symbols and brands so that they can have a dinner table (or, rather texting/FaceTime/Skype) conversation with their human partners and contributors.

Marketing to people vs. marketing dialogue.

When marketers speak of marketing, we usually speak about marketing to our consumers, prospects or customers. We talk about which marketing channels drive particular actions that we are interested in, how we can configure our marketing processes to drive higher adoption, sales or loyalty. While this has been a great tool in an environment where media has been pushed – TV, Direct Mail, circulars, Out of Home, in the current consumer environment, this approach is wrought with issues. While a lot of marketers speak about a dialogue using social media, and other online tools, we rarely think about marketing (and marketing measurement) from consumers’ point of view. Let’s start with example. We speak about attribution. Which digital channel should get credit for a particular action and, what is the best way to optimize channels to drive a particular result. Let me flip this statement a bit on its head. Why won’t we talk about which channels consumers prefer to use to get to the particular result, and what interactions consumers do in the process. This may sound as a small change but it is a significant one. We are not looking at how to optimize channels to achieve best results, we are looking at how to optimize channels to achieve desired consumption behaviors by consumers. For instance, we are not saying we should be investing a particular amount into branded paid search, we are now evaluating whether the consumers that are consuming that paid search click, are consuming it in the flow that is particularly beneficial to us. Thus, we are not optimizing particular channel event s because they prove that they are not profitable to us, we are optimizing consumer events within their interactive journey with us to produce best possible outcome. What this means is that, while the bottom line is always important, it is our job as marketers to 1. Identify best possible consumers for a particular product 2. Identify best possible journeys (in paid, earned and owned media) for each consumer 3. Optimize consumer journeys to steer (not drive) consumers into the journeys that would generate the highest impact at the lowest cost The way that I see to do it, is to go beyond segmentation. Almost every company that I have dealt with in my marketing career, with exception of AB Inbev, and Axe, has focused on marketing to 25-45 year old women . Women in households, by and large, ARE the decision makers, so every company that wants a share of household’s share of wallet needs to speak to these women. Most companies also identified life triggers, such as marriage, birth of a baby, etc as the time that is best to market to these women, as that is when they are most likely to think about this decision. As a marketer, this sounds perfect, however, if one thinks for a moment as a consumer, do we truly have time to think about buying a computer, insurance product, make-up, when they are waking up every 3 hours to feed their baby, or are planning their wedding or enjoying the honeymoon? For us to get to this point, we need to first change our thinking, and second, change the way we are measuring and analyzing our interactions with consumers. We are currently measuring our interactions as direct connections -- our action X resulted in customer action 1. Our measurement systems need to be reconfigured to track and evaluate multiple customer interactions with us and make immediate adjustments in experience based on a change in customer behavior. We need to score our prospects and consumers on propensity to perform a particular action (conversion) that we are interested in and make tweaks to the score with every incremental interaction that the customer performs during the interactive session. We need to begin designing our measurement systems where each interaction between us and our customer immediately changes our perception of our customer and adjusts our conversation with them. Think about it as a sales process when you purchase a new car. Each consecutive action by an experienced and good salesperson is based on everything that they know about you, and while the beginning of the conversation may start with the preconceptions that the salesperson may have about you (the wife is the decision maker, you drove to the parking lot in a Lexus and are looking at a Mercedes so you are pretty well off, you are dressed all in black so you consider yourself stylish (if you live in New York City), etc.) and then they adjust as they learn more from your responses, interactions, even gestures. Our marketing measurement systems are not as advanced as a human eyes, ears and nose, but, can be, at the same time designed to pick up new actions and evaluate them against what we know, and optimize behaviors. What this process also does, is that it changes people’s work focus from focusing on developing particular products and managing particular media, to refocusing on customer behaviors. Not segments, as we usually think about it. We are not going after “young moms” or “up and coming millenials”, but at “researchers”, “deal seekers”, “cheap but gooders”, “procrastinators”, “just do it’s”. Those are behavioral segments that focus on the behaviors that we can observe, influence and guide through our controlled environment.

More on Attribution

Few days ago, I had a conversation with an acquaintance of mine about marketing attribution. He kept quizzing me about my stance that attribution is a useless and unnecessary excercise. Of course, in the current marketing analytics climate, this is blasphemy and, coming from one of the attribution meccas -- Digitas, I should have known that I would get significant push-back.

The crux of the argument for attribution was, that it is the only way to measure how much an individual (digital) channel drives conversions and to optimize it. My argument was that,
1. You can't measure it
2. You don't need to optimize to it.

Of course, as usual, I did not make my argument as eloquent as I could or should have, and spent the next few days going over it in my head. Here's what I think.

I still believe there is no right way to measure attribution, especially in digital space. Most common approaches, first click, last click, even factorial attribution will miss the true attribution. We cannot, and should not look at attribution on macro-levels, attribution is purely individual, and we cannot use averages to simplify it. As Jim Lenskold rightly spoke in his book "Marketing ROI", customer value is not a constant, we should not be using a constant, or average customer value in calculating ROI. Similarly, why are we falling into the same pit by calculating average/constant attribution factor for a given digital channel? By assuming that attribution is constant for a given combination of a digital channel and client, we are saying that a given channel cannot drive more conversions.

As I've argued before, one measure cannot be both performance and optimization measure. For instance, if you are trying to optimize 'quality' visits to your website, 'quality visits' is not a performance measure, it is a mean to an end. Similarly with attribution, if you want to optimize how effective is each channel in contributing to the conversion, you should not be using the same measure to talk about the performance of the channel, and, more importantly, assign budgetary values to each channel based on that performance.

One may ask, and rightfully so, 'if you are not using attribution models to find out how well each channel is doing, how do you know it's doing it's job?'

My answer is -- determine what job that channel has and manage accordingly. It is naive to think that the job of each channel is to drive conversions. At the same time, however, it is naive to think that channels have a job of 'awareness' or consideration. Here's a simple objective for an online media channel "Drive 1,000,000 qualified visitors to xyz.com within 3 months using $200k budget." Determine what 'qualified' visitor is. Same with paid search and social. Same with website. Only website now, has a bigger objective, in taking these visitors and converting them into paid customers. Yes, we are building a story, but each chapter has it's own job to do.

We should stop thinking how much each channel is contributing to conversion, and start thinking and concentrating on making each channel as effective as possible in what it is designed to do. Engineers and assembly workers designing and building doors for the car are not thinking on how well the engine is going to be running, they are concentrating on designing and building the best door possible that serves it's function well. So should we.

More on attribution (from OMMA metrics & measurement)

'Attribution is a dead end. It is a relic of siloed organizations'. Jeff Eisenberg, FutureNow Inc. Keynote speaker.

Attribution Analysis

Lately, there has been a lot of talk among marketing community about attribution analysis. Put simply, attribution analysis, is a method of allocating business goals to specific marketing tactics, i.e. TV campaign, website design, SEM, etc. In theory, this is a very useful tool, as it would allow marketers and advertisers to finally pound their chest and say "I told you so! What we are doing is relevant to your bottom line!" In practice, however, it is not that simple. Designers don't design for things to be easily measured, or, evenmore, customers are not easily forthcoming in their cross-channel behaviors.

I considered doing attribution analysis once, when I began my journey into Marketing ROI measurement. I decided to start with the (in)famous purchase cycle funnel (or hourglass depending on whom you ask) and use conversion rates between each step to calculate the attribution rates to each step. Then, as theory went, I would break out each channel within the step based on individual conversion rates, and voila -- I have my attribution model. Sounds good. In practice it was a bit more complicated as one can imagine. While I was working on perfecting my thoughts, I met Riccardo Zane, who gave me a new view on the purchase funnel and asked me to do what I've always been preaching -- look at it from consumer's point of view.

When we illustrate 'customer journey' through the funnel, we never illustrate it linear, it always jumps from one place to another. Yet, we never ask, why is that? If that is the case, maybe the funnel (hourglass) is not the right model? Maybe, customers don't make their decisions the way that we always have modeled? And if that's the case, what about attribution? Does it make sense at all?

Of course, people assign different channels different values when they make their purchase decisions. It is obvious, even by looking at such unscientific methods as ourselvles. From the marketing intelligence standpoint, do we care? Yes, one can argue, that if I know which channel is most important for my customer to make a decisions, I can invest more of my budget into that channel so that more customers can make a positive decision and make a purchase. I would think, on the other hand, that what we care more about, is knowing what actually makes a person decide to purchase, what kind of intelligence they are looking for.

Let's remember, that as marketers we posess a lot of channels of information, and very few channels of actual purchase. Before late 90's we had 3: in-store, mail-order, and phone. Then we've added web, and to the lesser part (at least in US) mobile. Web added an enormous weight to marketing efforts, as it required both the need to provide real-time information and real-time purchasing ability. It allowed customers make spur of the moment purchases (probably contributing somewhat to the current economic environment), but also, added to the information overload. How do we account for all this?

I say we don't. Let's take the simple approach. What do we care about? Customers buying our product repeatedly, our brand to increase in value, and more customers joining our fold. And we want to do it as efficiently as possible. The key to this is -- Customer Intelligence, which is to say understanding what our existing and future customers need to make a decision, and what our non-customers need to change their stance. It's not about attributing 10 purchases to facebook page, or 100 sales to a TV campaign, it's about understanding what customers need from across channels and providing them a unified, cohesive message that would allow them to make a positive decision towards our product again and again.

I would argue, that from optimization standpoint, we should stop attributing KPI's to each channel and start measuring and optimizing channel cohesiveness, campaign impact and across channel immersion. How do we do it? Stay tuned...

Coming up...

• Thoughts on attribution analysis
• Roles of Marketing Intelligence professionals
• Why doesn't Marketing Intelligence work
• What are the parts of Marketing Intelligence
• Strategies vs. campaigns
• Marketing Intelligence Education

Why Marketing Fermat

It's elementary Watson. Fermat's Last Theorem is a simple equation, yet, no complete solution was found in over 400 years. What I'm going to cover in this blog, sounds as simple as Fermat's last theorem, yet, has spawned a whole group of people who do it every day, and, approach it from an amateurish way.

Marketing Intelligence. a.k.a. Marketing Analytics a.k.a. Marketing Measurement a.k.a. Marketing ROI (add another 100 or so acronyms here at your own leisure). It is a combination of skillsets that allow more technical among the marketers to understand what the hell they are doing, and, whether, what they are doing makes sense.

What is Marketing Intelligence. Simply put, it is understanding how marketing improves business results. It has many parts to it, which I'm going to get into more details in future postings here, however, it really is simple. It is not about measurement, it is not about tracking, it is not about data collection, it is not about complex modeling and simulation. All of that are means to an end. This blog is about how companies should go about acquiring Marketing Intelligence and about tools and approaches that may help them achieve that.

We have IQ, EQ, how about MIQ? :-) (but more about that later). Stay tuned.