eCommerce Analytics

(Read the entire Customer Analytics: A Guide to Getting Started series)

In our last installement we tested offers to likely and unlikely buyers to gauge reaction. Let’s now use the results of this test to determine if we are being too timid or aggressive with our probability to buy cutoff percentage.

Read Customer Analytics: A Guide to Getting Started (part 7) »

(Read the entire Customer Analytics: A Guide to Getting Started series)

The situation so far: We have a glut of women’s sweater inventory that we need to unload. We decided to identify the customers who are most likely interested in purchasing women’s sweaters so that we can send full priced offers to them while offering deep discounts to the rest of the customer base.

In part 4 we produced the relevant data and had our data modeler (or software solution) produce a list of customers and their relative probabilities of responding to a sweater offer.

Read Customer Analytics: A Guide to Getting Started (part 6) »

(Read the entire Customer Analytics: A Guide to Getting Started series)

Now that we’ve explored a couple of possible customer analytics goals and developed plans to achieve them, we can now start thinking about execution.  Before we do that, however, I want to touch on what is probably the biggest challenge in executing a customer analytics initiative: organizational behavior.

Read Customer Analytics: A Guide to Getting Started (Part 5) »

(Read the entire Customer Analytics: A Guide to Getting Started series)

Last time we left off, we put together a plan to help us to use customer analytics to understand which marketing campaigns were worth pursuing and which to kill. This is a valuable analysis that can yield real profit growth without requiring any advanced predictive modeling. But what if we want to do something with a little more sizzle that really boosts the bottom line?

Read Customer Analytics: A Guide to Getting Started (Part 4) »

(Read the entire Customer Analytics: A Guide to Getting Started series)

Yesterday we talked about one of the reasons it’s important to go into your customer analytics intitiative with a well defined goal and a solid plan.  So how do you put a plan together to achieve our customer analytics goal?

Read Customer Analytics: A Guide to Getting Started (Part 3) »

(Read the entire Customer Analytics: A Guide to Getting Started series)

In part 1 of Customer Analytics: A Guide to Getting Started, we talked about defining the goal of your customer analytics initiative.  We’re now going to spend some time over the next few days talking about planning.  But first, I want to briefly give an example of why it’s critical to have a well defined goal and plan before deciding which type of tools you need.

Read Customer Analytics: A Guide to Getting Started (Part 2) »

(Read the entire Customer Analytics: A Guide to Getting Started series)

More and more companies are looking to implement customer analytics as a way to better understand purchasing behavior and squeeze more revenue out of their customers. And why not? Over the past few years, companies have been investing in collecting tons of data about their customers through their CRM, web analytics, and transactional systems. But how do you get started in customer analytics?

Read Customer Analytics: A Guide to Getting Started »