Smart business decisions come from simplifying problems. Bars can help!

Solving complex business problems “ain’t always rocket surgery,” to cite a colloquialism I just discovered. It often boils down to a little bar and a big bar.

As an outsider, I have the luxury of both working with data scientists and in gentle opposition. The first part is easy. Data scientists work with my clients’ data daily, and have produced elaborate models to help make things more understandable.

But I also work in gentle opposition. To quote best-selling author and distinguished professor of economics (and fellow “outsider”) Steve Levitt, it’s all in the incentives. He’s excerpted immediately below from one of his People I (Mostly) Admire podcast episodes. You can listen to this one-minute audio clip by clicking the player, or read on … the transcript immediately follows it.

Little Bar / Big Bar

When I work with firms that have data scientists, what I find almost uniformly is that they operate in an incredibly complex space. They’re very concerned with technicalities, with techniques, with things being hard. And I think the answers are often very simple. So I try to always do simple things, and try to relate them in very basic ways. Like, my favorite kind of graphs are Big Bar / Little Bars graphs.

They’re graphs that have one really little bar … and one really big bar, and those are the kind of graphs that I show to CEOs if I’m trying to convince them of something. And the CEOs say to me, ‘Wow, that makes sense to me. I don’t understand how you take the same data that my data science team has and I never understand anything they’re saying.’

So, you might say ‘The answer is to do things really simply,’ but I think it’s more complicated when you think of incentives. Because much of the power that comes to data scientists in firms and organizations is because they are completely and totally inscrutable. And the other people have no idea what they’re doing. And by having a set of skills that no one else has, you can wield power because no one understands why you’re doing it. You have a very special talent. And so, I have the luxury of being an outsider.

Steve Levitt, “I’m Not as Childlike as I’d Like to Be” | People I Mostly Admire Bonus Episode

Wow! Can I relate. I hear this frustration when I talk to the leadership within my clients. Which is why I have espoused simplicity in everything I report, and have for years.

Of Oracles and Job Security

At the end of a talk I gave in 2018 about experience optimization, I urged the audience to think of themselves as modern day oracles. But instead of the literal magic tricks that the Greek vestal virgins employed to keep their jobs, we only have our science to keep us regarded as useful and legitimate.

Scrupulous science.

Many data scientists stop there. They generate reports using the latest and greatest methods, but when the output is shared, business leaders too often have no clue what the data is telling them.

That quote I shared with you from Steve Levitt was in response to a question about the future of data science as a profession. If you are a data scientist, consider this advice: Spend more time listening to your employer about the problems dogging them. And if you’re one of those employers, you cannot go wrong by hiring, when appropriate, someone outside of the data scientist industrial complex to whip up the bars!

Why isn’t the Disaffection Index (DI) more popular with campaign marketers?

Many years ago, when self-proclaimed Email Diva and my own personal career doppelganger Melinda Krueger conceived of the Disaffection Index, my only qualms were with its name and acronym. She wrote about this campaign KPI in one of her MediaPost pieces. If I remember correctly, she even sent me a pre-read. I told her I loved the metric but predicted it would become more commonplace with campaign marketers if she gave it a TLA (three letter acronym). I was only half joking.

You be the judge. First, what is it?

Rather than unsubscribe / delivered, the DI is calculated by dividing unsubscribes by the response rate …

Calculated this way, the DI tells you how many people either a.) clicked on your e-mail for the sole purpose of getting off your list or b.) were so dissatisfied … they chose to unsubscribe.

Excerpt from “The New Unsubscribe Rate”

Today every subscriber and brand loyalist is worth too much to squander. So why isn’t this KPI on every campaign manager’s dashboard?

Last Click Index (LCI) to the rescue!

I humbly suggested at the time that LCI was a better term for two reasons. First, it adds drama. When someone unsubscribes, you’d believe you weren’t getting any more clicks from them. B*tch, bye!

And secondly, I had then and still have zero affection for the word disaffection. But it’s her baby, and a rose is a rose by any name. (Clever guy, that Shakespeare).

So if you’re a campaign marketer, start using it, regardless of its inferior name. You’ll thank me. And Melinda.

Melinda is currently an Associate Principal for the Salesforce Marketing Cloud, and I predict she will laugh heartily when she reads this. I do hope so. I miss talking shop with her!