Now that we know how to Measure Desirability, we need to act on what we learn.
Many web Analysts and Marketers are pretty hip to Optimizing for Actions. What they have a hard time thinking about is Optimizing Against in-Action. It’s the mirror image of what people usually pay attention to. If you’re having a hard time wrapping your head around this idea, try this analogy:
In the early days of web site funnel analysis, most people focused on the Active traffic, that is, the traffic making it to the next step, “step conversion”. The focus was always on optimizing “for Action”, on getting people who made it to Step 2 to Step 3, etc.
One problem with this mindset, of course, is that the percentage of traffic making it through the funnel steps is often quite small. So by optimizing “for Action” you are dealing with a small, probably biased group and the potential impact versus total traffic is going to be relatively small.
At some point, people began to realize the tremendous value of the mirror-image question – this traffic that is falling out of the funnel, where did it go? Because if you could optimize against in-Action you would hit a much larger cross-section of the population and have a larger total impact.
In other words, the most important question to ask is not “Why is this small group of visitors converting”, it’s “Why is this huge group of visitors not converting?” Further, if you knew what non-converting traffic did just before the in-Action, you could infer from this “Previous Action” why they were not converting.
This thought process is what convinced the web analytics vendors to start creating the “leak diagram” version of the Funnel, where you can see exit paths by funnel step. This functionality allows you to target efforts not based on what people were doing, but what they were not doing, and infer why they were not doing it by looking at the Previous Action (funnel Exit path).
I challenge anyone to argue it’s easier or more effective to optimize a funnel by Action rather than by in-Action with Previous Action. Previous Action shouts “why”. Knowing that 80% of the Funnel Abandonment at Step 2 goes to the “Shipping Policies” page is like all those visitors screaming at you “I need more info on Shipping!”
It just makes too much sense.
Likewise, when we see dis-Engagement we should read un-Desirability. And we should look to the Previous Action for clues on what is un-Desirable. Previous Action Clues such as:
a. They bought the same product or products
b. Products bought were from the same vendor or category
c. Responded to same campaign / traffic from same source
d. They talked to the same salesperson or service agent
e. They were formally Engaged with the same kind of content
and on and on. Find the dis-Engaging visitors or customers, then cross-tab by Previous Action. Just like a Funnel Analysis with Exit Paths. Attack the high volume ones first. If you need help starting, perhaps you should ask Customer Service for a whole list of un-Desirability opportunities.
Here’s what needs to be understood. Interactivity demands that these issues are somebody’s problem. For as great as Interactivity is as attracting customers, it tends to be quite weak at holding them. There is a tremendous ramp in Engagement early on in the cycle, which drops off just as fast on the other side for most participants except the very hard core. Why? Interactivity drives very high expectations on the visitor / customer side, and it doesn’t take much to screw up that relationship.
Interactivity is relentless like that.
So somebody has to do this job: finding the root cause of dis-Engagement and fixing it. Why? Because even more than with the typical web site optimization, very small changes can produce enormous increases in Profits. Why? Because you are dealing with much larger populations – those who did not Act, as opposed to those that tool Action of some kind.
What does this all mean on the ground level?
For Web Analysts: There is an exciting and challenging world waiting for you in this dis-Engagement data. You may or may not be able to access this data through your web analytics tool. If you can’t, find out where it is – in the customer service systems, help desk systems, commerce systems – and start exploring. If you have a BI unit, find somebody in BI who wants to work on these ideas with you.
For any given free cycle, you should resist the natural tendency to “Go Deep” in your own world, spending your precious time probing the inaccurate. Instead, “Go Broad”, and try to start connecting some of these un-Desirability ideas. This can be hard work, but I know you’ll enjoy it, and the payoffs in terms of profitability are huge.
For Strategic Marketers: Somebody has to do this job. Will it be you or the “Chief Customer Officer? Given Marketing causes a lot of these un-Desirability problems in the first place, it seems to me the Root Cause folks should be in charge of this effort, rather than those catching the flack.
Now I know what you’re thinking – this Desirability thing ain’t my job. I Push. I generate Sales, Awareness, etc. “Desirability” is not on the List. Poor service? Not on the list. Faulty products?
Please, not my area.
OK. Let me ask you something. When you lose a customer, what needs to happen on your side? You have to replace that customer just to stay even, right? So, to grow sales – which I think you are in charge of – you have to not only replace the lost customer but also add another customer. That means, for a fixed budget, that you’re not going to be able to grow sales as fast as you could if you were better at keeping customers, if you were attacking un-Desirability.
Do you think your sales goals for this year are “cake”? That you have “easy” targets? That you are absolutely confident you’re going to hit the numbers? If you answered Yes, then fine, you don’t need to care about Desirability. Just churn ’em and burn ’em, my friend. I guess you’re not the kind of person who would like to absolutely smash your sales targets to bits.
For Both Analysts and Strategic Marketers: If you are going to talk the customer experience talk, please start walking the walk.
A couple of suggestions:
1. Yes, this un-Desirability work often requires (demands?) cross-functional teams, because un-Desirability problems often start in one silo (Sales, Marketing, Product) and end in another (Service). Is that an impossible barrier to overcome? Start looking for partners. Better yet, start formalizing the idea of a Business SWAT team. More real world examples here, here, and here.
2. Wikipedia defines Experience as “observation of some thing or some event gained through involvement in or exposure to that thing or event”. Event. Behavior. Stop with the demographic segmentation already, it’s just obscuring everything that’s important to customer experience. Save the demographics for the Push end of the funnel where they mean something. Once you get to Action and move over into Pull mode, you’re now into Behavior.
Desirability is about Behavior, not Age and Income.
So that’s the whole model, front-end to back-end. This model incorporates many of the ideas floating around out there right now – Customer Centricity and Experience, Engagement, Reputation Management – into a single Data-Driven, Optimization-friendly, Customer-Aware, Accountable Marketing process.
In short, Measure Customers, not Campaigns. That’s the secret to unlocking the power of Interactivity and making it work for you. Otherwise, Interactivity can work against you.
Your Comments and Questions are appreciated. Your challenges as well – why can’t you do this? What will it take to change that?
Example: At HSN, I started by forming the Business Swat Team at the Director Level – IT, TeleCom, Customer Service, Marketing (me), Merchandising / Presentation, Fulfillment, Finance, and (of course) BI
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