All companies out there are eager to get to how their customers are doing business with them. And for most of them, they have lots and lots of information on how this behavior paints a picture.
With this post I want to get a simple, but powerful idea out there. Aggregated behavioral patterns. That might sound somewhat complex, but let me explain.
Think about your customers and how they purchase, interact or show interest in the offerings and services your company provides. All these things they’ll experience and follow-up with actions. Like visiting your website, searching for something they might need and hopefully decide on doing business with you and your company. Or they’ll decide otherwise.
In all these actions you will find behavior. Behavior based upon what a customer finds, needs and compares to what is being offered.
Lets assume we are lucky enough to get real interest from a customer and he or she decides to buy a product from you. This results in a purchase order. But, how did they start? What did they buy? Do they come back for more? All these transactions and decisions sit on a timeline. The timeline that conforms to that one customer’s decisions and actions.
Now, 5 different customers get or are interested, they will all research, interact and decide to buy products from your company. Customer ‘one’ buys his first product in January 2018, customer ‘three’ buys his second product in December 2019 and customer ‘two’ buys his fifth product in February 2019. Customer ‘four’ buys his first, second and third product during October and November 2017, while customer ‘five’ buys his first product in February 2019.
February 2019: Two customers buy a product. Customer ‘two’ buys his fifth product and customer ‘five’ buys his first product. For this month we can say we have a returning customer. He or she already bought 4 products prior to this last purchase. In February 2019 we can say we have different customers, with different profiles showing different behavior. Now, most companies don’t have 5 customers. So getting to insights based on customer purchases is a bit more difficult.
What we should understand is that customers decide and follow-up in their own pace and time. But no matter what the differences are for making a decision, every customer has a first, second, third, and so on, decision somewhere in time. It becomes a sequence of events.
To get insight we need to map this sequence of events onto our data. The idea and example provided here with this post is a sequence of purchase orders any customer did with our company. For this we have taken a purchase orders table, ordered it by CustomerID and OrderDate (asc) and applied a sequence for each and every customer found in that purchase orders table.
After doing this, we end up with a unified timeline for each and every customer in our database. Every customers 1st, 2nd, 3rd, 4th, … purchase. In the app you will find with this post we called it the ‘Sequence of Orders’.
In the image above you see a simple line chart. Two expressions called LEFT and RIGHT, both containing a calculation to determine the average amount per Customer for purchase orders they have been doing with us. The horizontal (X) axis in this example contains every customer’s 1st, 2nd, 3rd, 4th, etc purchase order that was ever done with our company. Drawing the unified timeline for customers and their purchasing behavior.
In this example, we made selections for two different groups of customers, to draw a comparison. The ‘BLUE’ line associates with the selections we have made on the left side of the screen. The ‘RED’ line associates with the selections we made on the right side of the screen.
For this comparison we can say: Our customers who have a bachelors degree that own a car and have children buy less on their initial investments in the product. This compared to our customers with the same bachelors degree that don’t own a car and don’t have children. The latter group spends more on their initial investments and don’t really come back for more after the 4th purchase order. This is different for our customers in the ‘LEFT’ group, they’ll buy more products after the 4th purchase order.
The app containing the example in the screenshot can be downloaded here.
Also the data used in this app can be downloaded.
If you have any questions or additions, let me know in the comments.