But collecting is only half of it. Finding ways to strategically use the data is the real goal.
One such way is coming up with a customer profile.
Here are two types:
1) Demographic - This is a set of characteristics like gender, age, marital status, geographic location, socio-economic status, etc. It provides enough information to create a mental picture of the typical member of the hypothetical group. For example, a marketer might speak of the "single, female, middle-class, age 18 to 24, college educated demographic."
2) Behavioral - This type of profiling is more concerned with what the customer is actually doing. It cares only about customer activity. This is infinitely more important than demographical information.
Infusionsoft makes it pretty easy to collect both pieces of data. The first is pretty typical and any crm can store information like age, address, and even supply custom fields for information like socio-economic status (perhaps in the form of a "score" or comparative rating). When it comes to behavioral data, Infusionsoft's tagging system makes this feat very achievable.
What are my customers doing? When's the last time they've engaged with my website? How long have they gone without purchasing? How long have they gone without clicking on a link? Will they visit again? Will they buy again? These are the questions answered by collecting and analyzing behavioral data.
Simply put - customer behavior is a much stronger predictor of your future relationship with a customer than demographic information will ever be.
Granted, demographic profiling is useful if your business relies on selling advertising. But even then, the behavioral profile trumps it because if the customer stops visiting your site or interacting with you, you're not going to have eyeballs to serve ads to, no matter how personalized or customized to the visitor's demographic profile the ads may be.
Customer modeling is probably a better word for the latter profile because it is action-oriented. Models aren't about "set-in-stone" characteristics like "my customer is a female between the age of 18 and 24." Models are about actions over time like, "If a customer does not make a purchase in the next 30 days, they are unlikely to come back and make any further purchases." That's a model.
Modeling seeks to look at customers who are engaging in a certain behavior and tries to find a commonality in them. For example, in Infusionsoft, I can pull my top 20% of customers by monetary (how much they've spent) or frequency (number of transactions) values and attempt to find a commonality. Combined with other data, I can determine on average, how long it took this group to make their first purchase. In doing this for one client, we determined the difference in a customer who goes on to purchase more than 30 times and one who purchases half that amount (both great customers by the way) is a 10 day disparity in the time it takes to make their first purchase.
Not surprisingly, as the time it takes to make first purchase increases, the customer is less likely to spend as much or as frequently. Simply put - his best customers engage faster than everyone else. This is data the marketing team can respond to!
Or perhaps, you may find that if a customer buys 3 times in first 90 days, they will go on to spend an average $2000.00 compared to those who only buy once in a 90 day period ($500.00). This is another example of a model.
The real power comes in combining both demographic and behavioral data to produce an even crystal clearer picture of the customer. Just remember that if you must choose, always go with behavior. If you've got finite dollars and one company offers to analyze and compile the demographics of your customer base versus another analyzing behavioral trends and actions, go with the latter.
If you aren't tracking behavior on an individual-client level, you owe it to yourself to schedule a tour with Infusionsoft. Behavorial tracking is commonplace with this solution and will allow you to do "Fortune 500" marketing activities to increase customer value, extend their lifecycle, and lower wasteful spending on the wrong prospects and customers.
Until next time.
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