How to achieve FAME in analysis

focused handsIn retail, and in web retail in particular, we are drowning in data. We can and do track just about everything, and we’re constantly pouring over the numbers. But I sometimes worry that the abundance of data is so overwhelming that it often leads to a shortage of insight. All that data is worthless (or worse) if we don’t produce thoughtful analysis and then carefully craft communication of our findings in ways that enable decision makers to react to the data rather than try to analyze it themselves.

The most effective analyses I’ve seen have remarkably similar attributes, and they happen to work into a nice, easy-to-remember acronym — F.A.M.E.

Here, in my experience, are the keys to achieving FAME in analysis:

Focused

Any finding should be fact based and clear enough that it can be stated in a succinct format similar to a newspaper headline. It’s OK to augment the main headline with a sub-headline that adds further clarification, but anything more complicated is not nearly focused enough to be an effective finding.

For example, an effective finding might be, “Visitors arriving from Google search terms are converting 23% lower than visitors arriving from email.” An accompanying sub-heading might further clarify the statement with something like, “Unclear value proposition, irrelevant landing pages and high first time visitor counts are contributing factors.”

All subsequent data presented should support these headlines. Any data that is interesting but irrelevant to the finding should be excluded from the analysis. In other words, remove the clutter so the main points are as clear as possible.

Actionable

Effective findings and their accompanying recommendations are specific enough in focus and narrow enough in scope that decision makers can reasonably develop a plan of action to address them. The finding mentioned above regarding Google search visitors fits the bill, and a recommendation that focuses on modifying landing pages to match search terms would be appropriate. Less appropriate would be a vague finding like “customers coming from Google search terms are viewing more pages than customers coming from email campaigns” accompanied by an equally vague recommendation to “consider ways to reduce pages clicked by Google search campaign visitors.” Is viewing more pages good or bad? Why? The recommendation in this case insinuates that it’s bad, but it’s not clear why. What’s the benefit of taking action in quantifiable terms?

Truly actionable analysis doesn’t burden decision makers with connecting the data to executable conclusions. In other words, the thought put into the analysis should make the diagnosis of problems clear so that decision makers can get to work on determining necessary solutions.

Manageable

The number of findings in any set of analyses should be contained enough that the analyst and anyone in the audience can recite the findings and recommendations (but not all the supporting details) in 30 seconds. Sometimes, less is more. This constraint helps ease the subsequent communication that will be necessary to reasonably react to the findings and plan and execute a response. Conversely, information overload obscures key messages and makes it difficult for teams to coalesce around key issues.

Enlightening

Last, but most certainly not least, effective findings are enlightening. Effective analyses should present — and support with clear, credible data — a view of the business that is not widely held. They should, at the very least, elicit a “hmmm…” from the audience and ideally a “whoa!” They should excite decision makers and spur them to action.

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The FAME attributes are not always easy to achieve. They require a lot of hard thought, but the value of clear, data-supported insight to an organization is immense.

The most effective analysts I’ve seen achieve FAME on a regular basis. They have a thorough understanding of the business’ objectives, and they develop their insights to help decision makers truly understand what’s working and what’s not working. And then they lay out clear opportunities for improvement. That’s data-driven business management at its best.

What do you think? What attributes do you find key in effective analyses?

“We tried that before and it didn’t work”

Light bulb“We tried that before and it didn’t work.”

Man, I’ve heard that phrase a lot in my life. And truth be told, I’ve spoken it more than I care to admit.

But when something fails once in the past (or even more than once) should it be doomed forever?

I was lucky enough to hear futurist Bob Johansen speak last week at Resource Interactive’s excellent iCitizen conference, and he said something that really stuck with me:

“Almost nothing that happens in the future is new; it’s almost always something that has been tried and failed in the past.”

It’s so true. Think about Apple’s recent successes. MP3 players floundered before the iPod came along. Smartphones existed in limited fashion before the iPhone changed the landscape. And tablet computers had been an unrealized dream for quite some time. In discussing the tablet computer in 2001, Bill Gates famously said that “within five years I predict it will be the most popular form of PC sold in America.” When that didn’t happen, it wasn’t hard to find people predicting the tablet’s failure: “The Tablet? It isn’t RIP. But it’s certainly never going to be the noise Bill Gates thought.” But then along came the iPad and its million units sold in the first month alone. And don’t get me started on e-books, which many loudly proclaimed were bound to fail. Jeff Bezos begs to differ.

We humans have this tendency to throw the baby out with the bathwater when something fails.

But the reality is that the success of any new idea — be it a product, a promotional idea, a merchandising technique, a sales tactic or website functionality —  is dependent on many different variables. Execution matters a lot. But we’re also dependent on many other situational contexts in the idea’s ecosystem, like timing, audience/customers, design, the economy, and the general randomness of life. Even slight tweaks to any of those variables can be the difference between success and failure.

In the others words, we shouldn’t automatically assume a past failure of an idea means the idea was bad. To be clear, I’m not suggesting there aren’t bad ideas that deserve to remain in the trash heap. However, we should at least break down the failure of an idea that we must have considered worthy at one point. (Why else would we have tried it in the first place?) What went wrong and what went right? Was it the execution? The positioning? The audience? Did we even have enough data points in our measurement that our findings of failure are statistically significant? Did it really fail?

Once we’ve broken the failure of the idea down into its component parts, we’ll have a better sense of whether or not the idea itself was at fault. We’ll have a much better understanding of the problems we would face if we tried it again, and that better understanding will give us a better platform from which to base our next attempt if we so desire.  We’ve all heard the stories of Thomas Edison’s thousands of failures before he finally got the incandescent light bulb right. Would we all be in the dark today if he gave up?

What do you think? Have you good ideas junked because of past failures? Was it the idea or something else?

Bought Loyalty vs. Earned Loyalty

Earned loyalty vs Bought loyaltyAcquiring new customers is hard work, but turning them into loyal customers is even harder. The acquisition efforts can usually come almost solely from the Marketing department, but customer retention takes a village. And all those villagers have to march to the beat of a strategy that effectively balances the concepts of bought loyalty and earned loyalty.

I first heard the concepts of bought and earned loyalty many years ago in a speech given by ForeSee Results CEO Larry Freed, and those concepts stuck with me.  They’re not mutually exclusive. In the most effective retention strategies I’ve seen, bought loyalty is a subset of a larger earned loyalty strategy.

So let’s break each down a bit and discuss how they work together.

Bought loyalty basically comes in the form of promotional discounts. We temporarily reduce prices in the form of sales or coupons in order to induce customers to shop with us right away.

Bought loyalty has lots of positives. It’s generally very effective at increasing top line sales immediately (especially in down economies), and customers love a good deal. It’s also pretty easy to measure the improvement in sales during a short promotional period, and sales growth feels good. Really good.

And those good feelings are mighty addictive.

But as with most addictions, the negative effects tend to sneak up on us and punch us in the face. The 10% quarterly offers become 15% monthly offers and then 20% weekly offers as customers wait for better and better deals before they shop. Top line sales continue to grow only at the cost of steadily reduced margins. Breaking the habit comes with a lot of pain as customers trained to wait for discounts simply stop shopping. Bought loyalty, by itself,  is fickle.

But it doesn’t have to go down that way.

We can avoid a bought loyalty slippery slope when we incorporate bought loyalty tactics as part of a larger earned loyalty strategy.

We earn our customers’ loyalty when we meet not only their wants but their needs. After all, retail is a service business. We have to learn a lot about our customers to know what those wants and needs are so that we align our offerings to meet those wants and needs. Which, of course, is easy to say and much more difficult to do. But do it we must.

To earn loyalty, we have to provide great service and convenience for our customers. But we have to know how our customers define “great service” and “convenience” and ensure we’re delivering to those definitions. Earning loyalty means offering relevant assortments and personalized messaging, but it’s only by truly understanding our customers that we can know what “relevant” and “personalized” mean to them. And a little bit of bought loyalty through truly valuable promotions can provide an occasional kick start, but we have to know what “valuable promotion” means to our customers.

We earn loyalty when the experience we provide our customers meets or even exceeds their expectations. As such, our earned loyalty retention strategies have to start before we’ve even acquired the customer. If we over-promise and under-deliver, we significantly reduce our ability to retain customers, much less move them through the Customer Engagement Cycle we’ve discussed here previously.

But earned loyalty can’t just be the outcome of a marketing campaign. It’s much bigger than that, and it doesn’t happen without the participation of the entire organization. Clearly, front line staff in stores, call center agents and those who create the online customer experience have to be on board. But so too do corporate staff, including merchants for assortment and marketers for messaging. And financial models for earned loyalty strategies inevitably look different than those built solely for bought loyalty.

Since customer expectations are in constant flux, we have to constantly measure how well we’re doing in their eyes. Those measures must be Key Performance Indicators held in as high a regard as revenue, margins, average order size and conversion rates. (Shameless plug: the best way I know to measure customer experience and satisfaction is the ACSI methodology provided by ForeSee Results). Our customers’ perceptions of our business are reality, and measuring and monitoring those perceptions to determine what’s working and what’s not is the best way to determining a path towards earning loyalty.

Earning loyalty requires clear vision, careful planning, a little bought loyalty, lots and lots of communication (both internally and externally), and some degree of patience to wait for its value to take hold. But when the full power of an earned loyalty Customer Engagement Cycle kicks in, its effects can be mighty. The costs of acquiring and retaining customers drop while sales and margins rise. That’s a nice equation.

What do you think? Have you seen effective retention strategies that build on both bought and earned loyalty? Or do you think is all just a crock?

Retail: Shaken Not Stirred by Kevin Ertell


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