MarketingExperiments Blog: Research-driven optimization, testing, and marketing ideas

You’ve finally set up tracking on your site and have gathered weeks of information. You are now staring at your data saying, “Now what?”

Objectively interpreting your data can be extremely overwhelming and very difficult to do correctly … but it is essential.

The only thing worse than having no insights is having incorrect insights. The latter can be extremely costly to your business.

Use these six simple steps to help you effectively and correctly interpret your data.

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So you want to optimize the amount of success you have converting your customers?  Well, one approach could be to optimize the customers with which you choose to do business. In other words, only market to customers who can really get value from your product.

Not only can you gain more business, but you can also find customers who are more compatible with your organization. This allows for smoother transactions with a higher success rate, which in turn raises the profit with fewer headaches.

How do you do that? It comes down to some math, namely statistics. If you have a data analyst on your team or in your company, I’m going to show you one tactic they can use to help you choose customers to market to who are much more likely to choose your product.

This analysis can even help you set pricing. After all, customers who can get more value from your product will likely pay more for it as well, or, at the very least, need less incentive to encourage them to buy.

Partition analysis helps you predict who will buy

Partition (or decision) trees are a multivariable statistical approach to identifying and classifying members of a population into groups based on a set of dichotomous attributes that are unique to them. The first step, just copy and paste that sentence into an email to your data analyst to show them that you know what you’re talking about.

All the above sentence really means is that you can use these advance statistical approaches to separate the wheat from the chaff of potential customers.

One of the benefits of this type of multivariate analysis is that on top of classifying groups, they can be used to predict which group a particular individual member of the population will be in. If your current and potential customers make up the population, this method will tell you if the potential client you seek to do business with will be a great fit for your company, or if they will be more hassle then they are worth.

In other words, you’re looking for potential customers who have attributes similar to those who have already bought from you. It’s the marketing equivalent of your buddy asking you if your football-loving girlfriend has any sisters.

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I recently attended the MarketingSherpa Email Marketing LEAPS Advanced Practices Workshop in Boston and, though these events are always good for new information, I found myself surprised – and even outright alarmed – by one particular statistic cited at the beginning of the event: 61% of companies do not routinely test their email campaigns.

Sixty-one percent. See for yourself:
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You step into the store, the little bell rings above the door letting the shopkeeper know he has a new customer. Of course, he instantly recognizes you. “Hey Bob, welcome back. I remember how much you enjoyed the brioche I made last week, so I set aside some Danish braid I baked fresh this morning. It’s quite similar. I think you’ll love it.”

And then I wake up from my dream. Because, of course, that’s not the experience most of us have anymore. For the majority of the country, we step into a big box retailer. The doors open with a cruel, efficient “whoosh.” Sure, we get a “welcome to…” greeting, but then a cold metal shopping cart or the latest circular is thrust upon us. One-to-one marketing is dead…well, in the bricks and mortar world.

Online, it is actually alive and well, thanks to… Read more…