How Data-Driven Marketing Contributes to the Class Divide

Once on a calibration call, I heard a customer service rep actually tell a customer who was doggedly asking for a better rate something like “You’re one of our low-segment customers. No matter how many times you ask, none of you guys can get that rate.”

Clearly, that rep was seriously off-script. But the segmentation score on her CRM screen told her that the company didn’t value this customer very much, so she didn’t either. I built the segmentation model that told her that. For me, it brought into stark relief how marketing segmentation can affect dynamics far down the road.

In many years in the field, I’ve seen the good that data-driven marketing can do. It makes online life more relevant. It helps businesses stock products their customers want to buy. But the intrinsic power of data analytics to segment a population can also be wielded to divide it.

The last twenty years in which database marketing has hit the big-time coincides with a period of increasing polarization between rich and poor. I’m not suggesting that segmentation causes this polarization. Rather, it’s that it helps drive the wedge, already in place due to a complex mix of social, economic and political factors, deeper.

The objective of segmentation is to enable businesses to target their marketing capital toward the acquisition and retention of those customers yielding the greatest profit. There isn’t anything wrong with this, per se. Making money is what businesses are supposed to do, and it is the responsibility of their marketing organizations to help make that happen.

Customers and prospects are identified by their potential to enhance the bottom line, and strategies are crafted to reward the more desirable segments for doing business with them and not reward less desirable groups for it (or even subtly discourage them from it). The most profitable customers are not always the wealthiest – but let’s face it, it’s often the way predictive models will tell you to bet.

Predictive and yield models tell builders how to market and build most profitably. A prospect who can only afford a $195K house is courted by no one and can’t find a new house to buy. A prospect who can afford a $950K house is courted by everyone and has plenty of choices.

Profiling will tell businesses which customers are likely to have the wherewithal to pay on time and upgrade to more profitable products. This insight will be incorporated into the firms’ CRM systems. Those segments will receive the best offers, the special concierge customer service phone lines, the waived fees. There might also be “aspirational” or “elite-in-training” groups that get slightly better treatment in hopes that they will start behaving like the elite groups. And the other segments?

It costs them more to do business. They pay more for products. They have to wait in a longer phone queue for customer service. As for the service they do get when the phone is answered, there is no scripting in the CRM system that explicitly says “you don’t have to go the extra mile to treat this customer well”. But it’s pretty much guaranteed that some harried customer service reps will (perhaps in a rush to minimize the Average-Handle-Time metrics they’re bonused on) interpret it that way.

Before analytics, businesses often had policies that every customer should be treated like they’re the best customer – because absent the data, the assumption was that every customer had that potential. But in the data age, there is no more benefit of the doubt. When people complain that customer service doesn’t exist anymore, they’re wrong. It’s still alive and well – it’s just heavily up-market.

To reiterate, marketing segmentation and analytics did not cause the class divide. That has existed for millennia. Let’s at least be aware about how marketing analytics contributes to it in present day.

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New Agile Jobs

Code-Alones – Programmers who lack the people skills to be developers.

None-Of-Your-Business Analysts – Requirements gatherers for skunkworks projects.

Projectile Managers – Representatives of death march projects who must appear before angry stakeholders in the Marketing Conference Room.

Time Bandits – Scheduler/Physicists who bend the time-space continuum at the end of a sprint.

Pester Control – Analysts who intercept and gently steer away stakeholders who try to bother the development team with scope creep requests.

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Data-driven Decisions vs. Decisions With Data in the Room

Billions of dollars are spent on data. Analytics. Business intelligence. Modeling and profiling. Surveys and focus groups.

This data is presented to decision makers. But that’s not the same thing as saying that data is driving the decisions.

Has this ever happened to you? You’re in a meeting with executives. The Marketing Department presents data supporting the necessity of a change in the way your company is currently doing business. The execs politely listen to the data read-out, then announce their plan to continue pursuing the current course of action. Why?

Lots of reasons. The data went against their intuition. The data was presented by a department other than their own. The data threatened someone’s fiefdom. The data pointed to a course of action that was difficult or complex. The data was too math-intensive to hold their interest.

If you ask these execs whether they are making data-driven decisions, they will usually say yes and actually believe it. They are, in the sense that they are making decisions in the same room where data was presented. But that’s not the same thing, is it?

It’s not enough that the data is solid. It has to be sold.

Sometimes the people who are the best at crunching the data aren’t the best at presenting it or pursuading others that it’s important. That’s why the presentation of data is best when it’s collaborative. Gather data, make it bullet-proof, weave it into a story non-geeks can understand. Then, let the best communicator on your team (or someone else’s team) tell the story and sell the story to the people who need to make decisions from it. Good analysis only gets you halfway there – pay attention to making it come alive.

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Agile Humor – Multiple Choice

Choose the most correct answer:

1. User Experience:
(a) is a distinct professional discipline focusing on how a product’s use is perceived and experienced by the people using it.
(b) finishes a sentence that begins “If I were a user I would want…”
(c) is that nice department of people on the third floor that we let decide whether the “Submit” button should be red or blue.
(d) means my experience. I’m a user too. You know, a really experienced one.

2. Code Complete:
(a) means all feature code for a sprint is written and documented, and ready for testing.
(b) is a cruel tease – it’s never, ever, EVER effin’ done.
(c) a prerequisite to all of us getting wasted at Dave and Busters.
(d) is the time when you discover what the words “welcome changing requirements, even late in development” mean to you.

3. Sprints:
(a) are a short time period, usually 2 to 4 weeks, during which portions of code deliverables are written, tested, and possibly pushed to production.
(b) run like mini marathons.
(c) are ten pounds of coding stuffed into a five pound bag.
(d) are given clever names to distract you from the fact you haven’t had a day off in two and a half weeks.

Answers: Aw, come on now…

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A Marketer’s Guide to Agile Development – Who Owns Analysis?

I got certified in Marketing Data Governance a couple of weeks ago – and on the first day of certification class, I heard something that made me choke on my coffee.

Our instructor told us that the question we should be asking is NOT who owns the data – it’s who owns the means of analysis. Because they who own the means of analysis ultimately get to control the story.

That makes sense, and explains why I’ve been fought over. As a data professional, I mean. I’ve spent most of my analytical career in Marketing – but Finance, Information Technology, and Operations have all at one time or another discussed bringing my Analytics practice under their managerial control at various stages of my career.

Sometimes Marketing analysis points up shortcomings in other departments – maybe even running counter to a department’s carefully crafted party line. Maybe Sales isn’t converting leads so well. Maybe IT’s app isn’t thrilling customers. Maybe Finance’s allocation of budget dollars to acquisition at the expense of retention isn’t such a great strategy.

That inevitably makes some political waves. Politics shouldn’t enter into Analytics – except it almost always does. If we can’t steer clear of it, we can at least be aware of it and craft our data presentation and messaging to acknowledge it. This will help minimize the “shoot the messenger” dynamic – or the spawning of competing analytical operations controlled by (and not coincidentally, producing analysis flattering to) the departments they measure.

Analysis has power. Which means control of it is a big deal, a big responsibility, and a big political advantage.

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A Marketer’s Guide to Agile Development – Big Data Envy

Marketers are becoming as insecure about big data as they already are about mobile. It’s like the middle school dating scene – you think everybody else is doing it but you.

Don’t buy into the hysteria. Relax. Big data is real, alright. And, its potential really is quite vast. But its buzzword-du-jour status right now causes marketers unnecessary angst. Nobody wants to be perceived as anything less than cutting edge, and it’s a status thing to say you’re “doing big data.”

Before you hire the Hadoop gurus, ask yourself if your operation is ready to use big data. Are you already wringing enough insight out of your existing customer databases and retention data to move the attrition needle down a few ticks? Are you mining data out of your existing digital analytics tool sufficiently to inform decisions about content?

If the answer is no, then queuing up big data could be like buying your kid a new Escalade when he’s still learning to drive the 2003 Honda Civic.

As I said, big data has great potential – yet data won’t become insight until you ask questions and use it to get the answers. Let’s make sure that paradigm is working on the regular data before rushing to harness big data.

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Agile Humor – Agile Billboard Top 10 – 11/28/12

1. Rihanna – Diamonds (the Vizio Flow Remix)

2. Maroon 5 – One More Night (Until Freakin’ Code Complete Is Done)

3. Ke$ha – Die Young (Yes, Scope Creep Kills)

4. Bruno Mars – Locked Out of Heaven (Server Credentialing Blues)

5. fun. – Some Nights (Red Bull, Get Me Through)

6. Ne-Yo – Let Me Love You (Until You Learn To Love Yourself or Until I Find a Girlfriend Who Plays Minecraft)

7. PSY – Gangnam Style (There’s Something Hotter Than Agile?)

8. The Lumineers – Ho Hey (Don’t You Come At Me With More Changing Requirements, Bro…)

9. Taylor Swift – We Are Never Getting Back Together (Pair Programming Fail)

10. Flo Rida – I Cry (Abandoned Code Remix)

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Agile Humor – Halloween Costumes

Put on a rumpled plaid hoodie and old jeans. Smear some pizza down the front of the hoodie. Dab your face with ivory-toned makeup to reproduce the pallor of a four-day-coding-marathon and go as a developer.

Put on a hemp shirt and a pair of Seven For All Mankind jeans. Pick up a pair of Oakley sunglasses. Get a spray tan, grab a Vitamin Water and go as a marketer.

Put on an oxford shirt and a pair of Dockers. No food smears on the shirt, you don’t have time to eat. Knit your brow and go as a project manager.

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Agile Humor – Agile Drinking Game

Great for attending business meetings remotely – access your GoToMeeting, grab a bottle of Stoli, then down a shot every time you hear:

FAIL FAST

WUDDAYA MEAN, FAIL?

EMPOWERMENT

NIMBLE

COLLABORATIVE

REQUIREMENTS

DONE

WUDDAYA MEAN, DONE?

MARKET-READY

RAPID PROTOTYPE

DEFINE RAPID.

FEATURES

BACKLOG

Just remember to cover any points YOU need to address in the meeting BEFORE your second shot of Stoli.

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Agile Humor – Why Did the Chicken Cross the Road? (2)

MARKETING

We’ll recruit a representative chicken panel and probe their attitudes toward crossing the road.

SALES

Not my problem. I just have to convince the chicken to come to our side of the road, it’s up to customer service to keep her there.

CUSTOMER SERVICE

If we had a CRM system that truly met our needs, I would have known the chicken was disssatisfied, and presented her with a save offer.

CREDIT AND COLLECTIONS

The chicken didn’t give us 30 days written notice that she was going to cross the road, so she will still have to pay for the month of October.

PRODUCT DEVELOPMENT

Too many chickens are migrating to the other side of the road. We need to create a new side of the road.

MERGERS AND ACQUISITIONS

Our recommendation is to buy the other side of the road.

FINANCE

We can buy the other side of the road as long as we can close it and merge it with our existing side of the road operations.

EXECUTIVE COMMITTEE

Let’s get a consultant in here who’s knowledgeable about migratory chickens.

LEGAL

We can’t afford the liability. Effective immediately, all chickens are prohibited from crossing the road for any reason.

More Agile Humor – Why Did the Chicken Cross the Road (1)

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