Marketing Over Coffee: Mobile website traffic averages, Facebook retargeting, and more

In this week’s Marketing Over Coffee, hear about mobile website traffic averages, Facebook retargeting features, useless Kickstarters, and much more:

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Cherry picking your marketing data

Over the holiday weekend, I had a chance to bring a statistics aphorism to life, as I went cherry picking at a local farm. If you’re unfamiliar with the expression, cherry-picking one’s data means selecting only those case studies or data points that reinforce your point, while ignoring the rest. This expression never made a ton of sense to me until I actually went cherry picking.

IMG_9194Believe it or not, half of these cherries aren’t ready to eat.

Here’s why it now makes sense. Cherry trees have a wide, wide spectrum of fruit ripeness. At any given time, on any given tree that is in season, about 5% or so of the cherries will be picture-perfect, ready to pick and eat. About 20% are reasonably close to ripe, but might need a few more days to mature. 5% or so will be past ripeness and on the way to rotten. 10% will inevitably be partially eaten by pests. The remainder will be in various stages of ripening but nowhere near ready to eat.

From a statistical perspective, if you wanted a true understanding of a tree’s ripeness, you’d randomly pick cherries from it and get a wide selection of cherries at various stages of ripeness. If, however, you wanted a more practical, more useful harvest, you’d only pick the ones that were ripe or near ripe, even though your harvest would be statistically non-representative of the tree as a whole.

Cherry picking one’s data isn’t universally bad, however. It’s bad if what you’re after is statistically representative data. It’s good if you only want to look at certain pieces of data. For example, while understanding where your entire marketing database is in terms of readiness to purchase is important, cherry-picking only those prospects who are close to buying or ready to buy makes logical sense from a resource management perspective. You want your sales and marketing efforts to focus first on those opportunities that are most ripe before they cross into overripe (and likely buy from someone else).

Understanding what your end goal is – statistically valid representation or the best of the best – will help you to understand whether cherry-picking your data is a bad or good choice.


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Making change difficult

Vocus Demand Success 2014

The corollary to easing the pain of change is to make change difficult. Here are three examples:

Social networks try to make change difficult by sheer mass. It’s where the people are, like it or not. It’s where your friends mostly are (or that’s what their hope is, anyway).

Operating systems make change difficult by making it expensive. You invest in apps and then to switch means re-buying all of them, because what works on one platform doesn’t work on another.

Contracts make change difficult or impossible by making departure financially onerous. Lengthy legal proceedings, court costs, and penalties keep you locked in.

All of these kinds of change resistance mechanisms have one thing in common: they are the resort of companies that are not the best in class. When you are the best experience, the best product or service, you will lose some customers to churn. However, a good portion of them come back when they realize that an overly clever salesperson promised what couldn’t be delivered. Being the absolute best at what you do and delivering on the promises you make is the only guaranteed change prevention mechanism. The pain of changing and losing what you have to offer keeps people around. The catch is that the price of being the best is very high.

Using these lock-in mechanisms makes sense if you are not the best in class. It’s not necessarily a bad thing – if you are self-aware enough to realize that you aren’t the best in class, then they make logical sense to use. They are generally accepted as solid business practices. Be aware that making them overbearing risks your reputation as unhappy customers complain until they can escape – and the longer you hold onto them, the less likely they are to come back or refer colleagues.


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