The Marketing Tea Party

Quantipulation

By Ron Shevlin

Quantipulation: The Art of Using Numbers to Create Marketing Myths and Misconceptions.

A guy named John Wanamaker is famous for something he said 100 years ago. He said:

“Half the money I spend on advertising is wasted; the trouble is I don’t know which half.”

Unfortunately, he’s wrong. I mean, if he didn’t know which half was wasted, how did he know it was half and not three-quarters or one-quarter of it?

He’s also wrong because it’s conceivable that 100% of his advertising dollars were wasted.

A century ago there were no ad ratings or measurement services. So how he could possibly know if ANY of his advertising spend was effective? It’s quite possible that any increase he saw in sales was due to exogenous factors like the weather, the economy, the competition raising prices or going out of business, or word of mouth among customers.

Ah, but hold on here a second. I guess it’s possible that 100% of his advertising spend was effective – or at least, not wasted – depending on what measure of success you use. If you don’t believe me, ask DeBeers.

Is it likely that the advertising he did had absolutely NO effect at all? Probably not. Just because someone didn’t make a bee line for the department store after seeing an ad, doesn’t mean the ad had no effect and should be considered wasted dollars. Some might have seen the ad and learned about the store, or the ad might have left others with a positive impression of the store.

Wanamaker thought half his advertising spend was wasted because he had no way to measure its effectiveness and didn’t even know what to measure.

Today’s advertisers have some measurement tools and services available to them, but none can claim to be totally accurate. And marketers are dreaming up new metrics every day, so you can be sure that no one measure is perfect, nor can we safely assume that even a group of commonly used metrics can truly give us a reliable picture of the effectiveness of advertising.

Bottom line: Any claim on what percentage of your advertising is wasted and what isn’t is just a random guess. We simply don’t know – and can’t know.

Here’s another claim to consider: Have you heard that its costs five times more to acquire a customer than to keep or retain one? How did they figure that? You could double the number of insurance, credit card, or mortgage customers you have by simply tweaking your underwriting guidelines, risk guidelines, or interest rates. No big cost associated with that.

But to retain those customers, you have to incur some big costs to keep branches open, provide call center support, and deliver service in an ever-growing number of channels. Many of the costs you incur to keep the business running are costs that help keep your customers satisfied – and, hence, keeping them as customers. There’s simply no way the cost of acquisition is five times greater than the cost of retention.

But, wait, that’s not right either. Because all those costs you incur to retain your customers help to make your company the great company that it is. It’s what you’ve built your reputation upon. And without that reputation you couldn’t retain OR attract customers.

Bottom line: There’s simply no way to accurately calculate the cost of acquisition or retention. It involves making too many judgments and decisions on which activities contribute to acquisition and retention. It can’t be done.

These claims – that half of advertising is wasted, or that acquisition costs are five times greater than retention costs – are examples of what I call Quantipulation:

The art and act of using unverifiable math and statistics to convince people of what you believe to be true.

The examples I just gave are just two examples of this widespread practice. In fact, the incidence of quantipulation has grown by 1273% compounded annually since 2003. And I have the math to prove it:

What’s driving this growth in quantipulative activity?

The false legitimacy that quantipulation provides gives quantipulators confirmation that the things they WANT to believe are really true.

In addition, there are many people who want to lay claim to having the secret sauce for marketing success, and sadly, many people who want that special sauce. Quantipulation provides the “scientific” proof that their sauce tastes best.

There are at a lot different flavours of this special sauce that people quantipulate about, especially about customer loyalty, influence, performance metrics and ROI.

Source: http://marketingteaparty.com/2011/07/25/quantipulation/

Why Mark Twain Was an Analytics Guru

While I have no doubt Albert Einstein was talking about digital marketing when he said, "Not everything that can be counted counts, and not everything that counts can be counted," I have also come to the view that Mark Twain was an analytics guru. While possibly most famous for his "There are lies, damned lies and statistics" quote, I have discovered a number of other quotes that demonstrate his understanding of the world of analytics. Here is a selection of some of them:

"All generalizations are false, including this one."

Here he was talking about segmentation. Generalized metrics such as overall conversion ratios, average time on site, and so on are largely useless. They only make sense when the data is segmented and the underlying patterns and differences can be understood. The same is for survey data as well. Metrics such as NPS can vary wildly among different customer segments and so these segments need to be identified and looked at separately.

"Few things are harder to put up with than the annoyance of a good example."

A great insight into the power of evidence-based decision making. Solid facts, presented well, are hard to ignore. Twain was probably also thinking about the need to have an approach to testing and experimentation when he said this. There's no better way to silence the HIPPO (highest paid person's opinion) than to have concrete evidence from testing about why one approach is better than the other.

"It's no wonder that truth is stranger than fiction. Fiction has to make sense."

Sometimes the data doesn't make sense and the skilled analyst needs to understand why. Is the data telling her something new? Is this real insight or is there a problem with the data? Often, if it doesn't seem right, then it probably isn't right, but occasionally there may be something that the business has missed, the competition has missed, and there is real opportunity to be exploited. Just make sure you've checked the data thoroughly before you tell the CEO!

Twain also had some great advice for budding analysts:

"The more you explain it, the more I don't understand it."

This is a great piece of advice. Basically, keep it simple, but don't be simplistic. A good analyst will be able to present quite complex notions in ways that are easy for people to understand. This is the art of storytelling. Developing compelling narratives that engage the audience is quite a skill. There's an important role for data visualization here as well. It's harder to create simple charts and graphics than to scatter lines and bars all over a PowerPoint slide. That's why an analyst also has to be an artist.

"I was gratified to be able to answer promptly, and I did. I said I didn't know."

I think it's OK to say that you don't know; it's better than bluffing…

"It is better to keep your mouth closed and let people think you are a fool than to open it and remove all doubt."

…and being found out later, as long as you say that you'll find out the answer and come back to them. And then make sure you do.

And finally:

"The most interesting information comes from children, for they tell all they know and then stop."

Don't be afraid of silence, particularly if you're presenting to your audience. Deliver your insight and wait for a response. Maybe ask them a question, and then wait for a response. "Is that something you recognize?" and "Does that fit in with what you know?" are all ways of seeing whether what you're saying is hitting the mark or missing the mark. It's better to find out in the course of a conversation that what you're saying is not falling on fertile ground rather than just to be ignored later. Maybe you need to get more evidence or maybe you need to explain the point in a different way.

So that's why Mark Twain was an analytics guru!

Source: http://www.clickz.com/clickz/column/2083511/mark-twain-analytics-guru