Forever Learning

Facebook has recently discovered that beyond the uncanny valley of personalized marketing lies the bottomless pit of invasive identity misappropriation.

But there is a deeper problem here. I’ve said it before and I will say it again. Facebook has the data, but they do not have users with shopping intent. Nobody goes to Facebook to buy stuff. Facebook is for meeting friends, like a bar or a club.

Even with the best products in the world and the most detailed private information it is not easy to sell stuff to strangers in bars; unless you’re selling beer.

Dear [prospect.first_name],

Following our last discussion on [prospect.last_contact_date] concerning [prospect.subject_area] I think the following article would be of particular interest to you.

Seth Godin writes.

Sure, it’s easy to grab a first name from a database or glean some info from a profile.

But when you pretend to know me, you’ve already started our relationship with a lie. You’ve cheapened the tools we use to recognize each other and you’ve tricked me, at least a little.

Increased familiarity begets heightened expectations. Personalization has its own uncanny valley.

The uncanny valley is a hypothesis in the field of robotics and 3D computer animation, which holds that when human replicas look and act almost, but not perfectly, like actual human beings, it causes a response of revulsion among human observers.

When you treat your customers as though you know them personally they will be personally offended if you do not. Beware of the eerie hollow of broken promise.

Daring Fireball quotes some interesting research findings related to what Barry Schwartz dubbed The Paradox Of Choice.

About 60% of the people stopped when we had 24 jams on display and then at the times when we had 6 different flavors of jam out on display only 40% of the people actually stopped, so more people were clearly attracted to the larger varieties of options, but then when it came down to buying, so the second thing we looked at is in what case were people more likely to buy a jar of jam.

What we found was that of the people who stopped when there were 24 different flavors of jam out on display only 3% of them actually bought a jar of jam whereas of the people who stopped when there were 6 different flavors of jam 30% of them actually bought a jar of jam.  So, if you do the math, people were actually 6 times more likely to buy a jar of jam if they had encountered 6 than if they encountered 24, so what we learned from this study was that while people were more attracted to having more options, that’s what sort of got them in the door or got them to think about jam, when it came to choosing time they were actually less likely to make a choice if they had more to choose from than if they had fewer to choose from.

A fascinating psychological effect with clear implications for display advertising, but there is a lesson here for online marketeers and analysts as well.

In this study, fewer people stopped when there was less choice, but more people actually bought something. If we were only measuring the former (i.e. attention), and not the latter (i.e. sales), we would be led to think more choice would be about 50% more effective at bringing in customers. And boy, would we be wrong!

Metrics matter; especially when you are using a system which can automatically optimize your process in order to maximize those metrics.

Don’t get yourself in a jam; remember this next time you decide to measure click acceptance instead of actual sales to drive your online marketing effort. Clickthrough rates are useful as a measure by proxy, but they can be misleading.

Seth Godin on the topic of perception, memory and marketing concludes.

Your accountant might care about the facts. You, the marketer, need to care about the conversations and the memories.

I recognize the sentiment, but think that’s only partially true.

Individual consumer perception might be the result of conversations and memories, but marketing to consumers  as a group is also about numbers. Results should be measurable, lest a company risk investing a lot of money not just in stories, but in fairytales.

You, the marketer, need to care about the conversations, memories and the facts. You need to be an accountant as well as a storyteller.

It seems that my little rant against the apparent lack of scientific rigor and the use of data to analyse performance in the world of advertising is nothing new. Scientific Advertising, written in 1923 by advertising icon Claude C. Hopkins, lays out a convincing argument in favor of the use of an empirical and results-oriented approach in all marketing.

The bottom line of this argument is the same as the true bottom line for every company. It’s all about the money.

Scientific advertising is impossible without [knowing your results]. So is safe advertising. So is maximum profit.

Groping in the dark in this field has probably cost enough money to pay the national debt. That is what has filled the advertising graveyards. That is what has discouraged thousands who could profit in this field. And the dawn of knowledge is what is bringing a new day in the advertising world.

Hopkins pioneered the use of keyed coupons to track the success of different campaigns and ads. He believed that the only purpose of advertising was to sell more products and that the effects of such efforts should be measurable and those responsible be held accountable. New ideas and concepts should be tried in a small, controlled and safe setting so that their (monetary) results could be measured and analyzed.

Only when a new approach proved to be successful in a number of trails could it be trusted to be applied at larger scale. Take this passage from his autobiography My Life in Advertising.

How have I been able to win from this situation so many great successes? Simply because I made so many mistakes in a small way, and learned something from each. I made no mistake twice. Every once in a while I developed some great advertising principle. That endured.

The technology of the time allowed Hopkins et al. to try new things and make mistakes only on a per town basis. Results had to be analyzed manually and each iteration required significant effort and some investment. Still, what knowledge could be gleaned from these relatively small scale ventures proved key to Hopkins’ success in advertising.

Judging by his own accounts it never occurred to Hopkins that different ads would have different results for different towns or different people. He was simply empirically searching for the perfect ad; one town at a time. Once found, this super ad would be unleashed upon the entire nation.

In that light, Oracle Real-Time Decisions (RTD) is like the traditional scientific advertising method on steroids. Not only does it apply the concepts of empirically testing success and failing in small doses and learns from those mistakes automatically; it is also able to segment the respondents into an seemingly infinite number of sub-groups and find a super ad for each.

Computing Science has taken Scientific Advertising to the next level; and you cannot afford not to follow.

[As a side note, I think it important to realize that Scientific Advertising was written before Edward Bernays took his uncle's ideas and used them to revolutionize the field of advertising. Thanks to Hopkins's scientific and empirical approach most of the facts and results cited still hold water, but some of the explanations and conclusions he puts forward are terribly outdated. If you want to know more, I can highly recommend Adam Curtis's award-winning 2002 documentary for the BBC, The Century of Self.]

3. Gratuitous use of Flash.

It is not Adobe’s fault, it is your fault for using Flash for the most pathetic things mankind has known. Why? Because your agency can win an award? Because you believe that the Web is essentially TV? Slow sites make your management happy?

Remember every time you use flash on your website, a cute puppy dies. Think of the puppy!

Most of the items on this extended list compiled by Avinash Kaushik seem pretty obvious to me. Most likely you, my internet-savvy friends, would question even the need for writing these down like Avinash has.

Oh, how ignorance is bliss, my friends!

My work with Real-time Decisions (RTD) has introduced me into the wonderful world of marketing and advertising. A world where many companies still consider basic concepts like scientific control to be the latest craze (they call it ‘A/B testing’, but the idea remains the same). A world where gut feeling and HiPPO (highest paid person’s opinion) continue to rule, while real data and hard evidence are readily available.

The fact that Avinash felt the need to publish his list of truisms might explain some of the difficulty in conveying the concepts behind RTD to customers. Number ten on the list in particular sounds sounds awfully familiar to me.

Measuring success, a hot topic?

10. Making lame metrics the measures of success: Impressions, Click-throughs, Page Views.

They, and their brethren like video views and emails sent and # of followers on Twitter and Likes on Facebook and. . . all stink worse than Amorphophallus Titanum.

Use metrics that matter: Loyalty, Recency, Net Profit, Conversation Rate, Message Amplification, Brand Evangelist Index, Customer Lifetime Value and so on and so forth. Each a glorious magnificent metric that truly tells you that value was delivered, or delivers the swift kick in the pants that we all need when we don’t. How can you not love that?

If these people are not at ease with the idea of using cold data to measure success, or if they simply do not know how to define ‘success’ in the first place, how do you think they are going to feel about letting an artificially intelligent computer program improve the rate of that success by learning about customer behavior and preference? Not so good, I guess.

David Lightman: [to Joshua] Come on. Learn, goddammit.