The 2011 Marketing Tea Party Awards

Last year we issued the first of our eponymous awards to some very worthy winners.

The word Like took honors for Most Annoying Word in the Marketing Lexicon, while Twitter walked away with the Most Overhyped Yet Ineffective Marketing Tool award. And, to nobody’s surprise, Groupon won Bonehead Decision of the Year (for passing on a $6 billion offer from Google).

Although 2011 is only 10/12ths of the way done, we’ve pretty much seen enough (in fact, we’ve seen all we can take), and can confidently call this year’s winners in some newly ordained categories.

The New Coke Award

This year’s winner of the New Coke Award, for the company that commits the worst strategic blunder, is — hands down — Netflix. The firm’s pricing decision and  flip flop on the Qwikster thing resulted in the loss of nearly a million customers and somewhere in the order of $12 billion in market valuation. If you’re Google, that’s no big deal. But to the rest of us in the 99%, that’s a lot of money.

In the age of social media, where gathering feedback from the market and testing marketing (read: pricing) decisions can be done relatively fast and cheap, there’s simply no reason for major strategic blunders like this one.

Now, I know what you’re thinking: Based on the criteria, wouldn’t Bank of America be a close contender? No. They captured a different award:

Credit Union Marketer of the Year

Bank of America, with a single move — that they didn’t even implement — has done more for the credit union industry in one month than credit unions have done for themselves in 100 years. The Great Debit Fee Fiasco of 2011 will be a case study in business schools for years to come.

The circus surrounding an announcement — wait, did they ever really announce it? — is perhaps unprecedented. The number of parties taking credit for the reversal has only just begun. Claiming that they “listened to their customers” as the reason for the reversal only begs the question: Why didn’t they ask their customers BEFORE they made the decision?

Congrats, credit unions. This is your Rocky moment.

Most Overused Word in the Marketing Lexicon

I’m going to go out on a limb and make a prediction: 2011’s most overused word might just repeat the honor in 2012. Whether I’m right or wrong about that, there’s no doubt in my mind that Analytics takes the crown for most overused word in the marketing vocabulary for 2011.

Did you know that when you create a spreadsheet, and populate some cells with formulas that do addition and subtraction, that that’s called Analytics? If you use an Excel function, you might get away with calling it Predictive Analytics. 

Have you ever taken a list of customers and identified those that meet a certain criteria, like under a certain age, or over a certain income level? Congratulations, you’re an Analyst performing Analytics!

Do you create reports for the management team showing them traffic on your firm’s web site? That’s called web analytics.

And there’s certainly no shortage of experts telling us that analytics is the key to competitive success. If you’re not performing predictive analytics on the social media data you’re monitoring and capturing, then you might not still be in business in 5 years.

If analytics was overhyped and overused in 2011, just wait until next year. 2012 will be the year of Big Data. We here at The Marketing Tea Party will be doing our best to make it the year of Right Data. Because what’s one more bruise on the side of our heads from beating it against a brick wall?


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Blinding Me With Science

Conventional wisdom holds that “if you can’t measure it, you can’t manage it,” so we have metrics to help us manage our businesses.

And then there are Twitter-related metrics.

Meeyoung Cha from the Max Planck Institute for Software Systems looked at data from all 52 million Twitter accounts and determined that:

“The number of followers a Tweeter has is largely meaningless. Popular users who have a high number of followers are not necessarily influential in terms of spawning retweets or mentions,” she said. The more interesting question is how should one measure influence, she continues. Unfortunately there is no one easy answer to that, she says. “One would have to take a combination of many metrics, including follower count, mentions, and re-tweets. However the hard part is figuring out the relative importance of the component metrics.”

Cha is spot on that follower count isn’t important. But she’s wrong when she says that the hard part of measuring influence is “figuring out the relative importance of the component metrics.”

The hard part is figuring out what influence is. When you figure that out, then you can start arguing about how to measure it.

Social media analytics firm Sysomos conveniently avoids defining what influence is, and has developed a metric it calls the authority ranking: A score between 0 to 10 – with 10 signifying someone with very high reach and influence.

Social media “heavyweights” Chris Brogan and Jeremiah Owyang have an average follower authority (an “AFA” if you want to sound cool) of 4.0 while Jason Falls’ AFA is 4.8, and Scott Stratten’s is 4.6.

I guess we’re to conclude that Jason and Scott are more influential than Chris and Jeremiah.

If they want to raise their AFA, Chris and Jeremiah can cull through their list of followers (139k for Chris, 65k for Jeremiah) and block those with a low AFA. And then, going forward, only allow people with a high AFA to follow them.  I can’t think of a bigger waste of time, or stupider thing to do.

I could be off-base here, but to me, influence is about shaping how people think and/or act, wouldn’t you agree?

If you do, then how in the world can you measure influence simply by looking at follower count or follower’s follower count, retweeting activity, or mentions? What does any of that have to with influence?

Answer: NOTHING. Those “metrics” have nothing to do with influence.

I can’t tell you how many times I’ve DMed someone who has tweeted a link and asked “You believe that load of crap?” only to receive the reply “oh, I don’t believe it — I was just passing on the link.” If they don’t believe it, then they really weren’t influenced, were they? Nor are they being influential, because, apparently, they’re not trying to shape anyone’s thoughts or behaviors.

Most of these Twitter metrics are just pseudo-scientific stabs at establishing a system for score-keeping.

Don’t get me wrong: I’m not suggesting that you stop bragging about your follower count, influence ranking, or AFA score. Anything that helps you deal with your personal insecurities is OK in my book. But don’t try to blind me with your science. It’s not working.

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Analytics, Segmentation, Right-Channeling

There’s a really good article on the Harvard Business Review Online site called Changing Health and Wealth Behaviors with Analytics by Tom Davenport and John Sviokla. I won’t summarize the article here, you can read it yourself. But there are three things I took away from it that I think are spot on:

  1. Analytics will increasingly be an important element to marketing competency.
  2. Customer segmentation should be driven by behaviors.
  3. Marketers need to actively shape customer behavior, not just understand it, or react to it.

I did, however, have some reactions to each of these points:

1. Analytics is rapidly becoming a meaningless buzzword. I can’t count how many technology vendors have told me about their “analytics” capabilities. When I say to them “it sounds to me like what you’re calling analytics is really reporting” some will admit that that reporting is what they’re really talking about. Call me a purest, but I’ve always thought of analytics as applying statistical techniques to predict or explain something. Slicing and dicing data isn’t analytics in my book.

The problem with this is that firms will invest in new technologies and processes because somebody in the organization called it an “analytics” initiative, when in reality it has nothing (or little) to do with analytics.  This is an age-old problem: Firms invested hundreds of millions of dollars in initiative because the project sponsor called it a knowledge management or reengineering effort.

2. There are forces working against behavioral segmentation. For starters, many firms (especially financial services firms) purchase data from various sources that enable them to do attitudinal segmentation. While behavioral data may come from internal sources, and therefore be cheaper (theoretically), the firms that supply attitudinal data segmentation will  make the case for why their data is still valuable. In addition, just because there’s “better” data out there doesn’t mean marketing is agile enough to change the way they plan and execute campaigns.

Then there’s the question of whether or not that internal behavioral data really is less expensive. For a decentralized, multi-line of business, channel-stovepiped business, pulling together reliable, consistent behavioral data across LOBs and channels is a pipe dream.

And where would you start? As Davenport and Sviokla wrote in their article, the first step in the process towards behavioral segmentation is “getting some data about behavior.” While space might not have allowed for them to more specific, that wasn’t very specific. And the financial services example they gave — using retirement savings calculators — wasn’t really a very good example.

Marketers will need to develop a theory — and then test and refine this theory — regarding which behaviors are the most important to collect data on. You can find some of my thoughts on this here and here.

3. Marketers don’t get right-channeling. The HBR article starts off by commenting that “changing consumer behaviors is increasingly critical to the success of several major industries.” This statement can be interpreted in more than one way. On one hand, it might be an observation consumer behaviors are changing and that that’s important. On the other hand, it might be a prescription to managers that they need to do things to change consumers’ behaviors, and that the ability to do so is increasingly important.

There are a lot of people who will interpret the statement the first way, and that’s too bad, because the authors intend the statement the second way. And it’s a really important thing for marketers to understand, and a competency for marketers to have.

A few years ago I was at a conference where the then-CEOs of Bank of America and Fleet Bank were speaking. In separate presentations, they both said the same exact thing: “We’ll do business in the channels our customers want to do business in.” That sounds very customer-centric, but it’s a helluva expensive way to do business, especially as customer channels and touchpoints proliferate.

I recently gave a presentation at Open Solutions’ customer conference on Right-Channeling Customer Interactions, where I argued that financial institutions needed to develop a competency for right‐channeling consumers’ interactions and transactions. Specifically, that through education, peer analysis, segmentation, channel integration, and process redesign, firms needed to test and learn their way to understanding what works and what doesn’t when it comes to actively shaping customer behavior.

I think that’s what Davenport and Sviokla are advocating for in their article.  The problem is that this isn’t nearly as sexy as social media and launching your new Facebook page or some Foursquare campaign. I guess it comes down to what your priorities are: Generating profits or generating buzz?

It’s Not This Verus That, But How Much Of This And How Much Of That

All the talk about how direct mail has run its course, the superiority of email ROI, and how influential print inserts are (relative to TV ads) is simply not very helpful. What do those who put out these research findings expect us to do? Move our entire marketing investment to the new or better investment vehicle?

If you want to put 100% of your marketing budget in print inserts because it’s better than TV, or shift 100% of your direct mail investment into email because of its higher ROI, that’s fine with me. Especially if you’re one of my competitors. Cuz’ you’re going to fail faster than Asafa Powell runs the 100 meter dash.

The issue isn’t direct mail vs. email or print inserts vs. TV, but how much of each should we do. The firms that succeed will be those that figure out the right mix. If you’re a marketer, there are three questions you need answers to:

1. What’s our current mix?
2. How did we arrive at that mix?
3. What should the mix be?

I know of firms that are deploying statistical models to attempt to answer the last question. I’m not saying that they should stop what they’re doing, but I guarantee you that if they don’t answer #2 (and #1, for that matter), their models won’t be successful.

Here’s why: Because today’s investment mix is often the result of politics, historical spending levels, budget negotiations, outdated market assumptions, ineffective or non-existent testing approaches, and, in general, an absence of strategic thinking.

When they try to implement the model’s results, because they have no handle on how much is actually being spent on what and by whom, the spending mix won’t change the way the model says it should.

In other words: Garbage in, garbage out.

In a white paper titled Competing On Analytics (which ultimately became a book of the same title) Tom Davenport wrote:

Virtually every major company uses some form of statistical or mathematical analysis, but some take analytics much further than others. [One attribute] of firms that compete on analytics: Widespread use of not just descriptive statistics, but predictive modeling and complex optimization techniques.”

Davenport is spot on. But getting there isn’t going to be easy, and I don’t think that a lot of firms really understand the cultural changes needed to get there.

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