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.