Kevin Hillstrom: MineThatData

Exploring How Customers Interact With Advertising, Products, Brands, and Channels, using Multichannel Forensics.

August 11, 2009

OMS: The Online Marketing Simulation

This is the fourth part of our series on Advanced Web Analytics and Online Marketing Simulations (OMS).

The goal of an Online Marketing Simulation (OMS) is to help us see how decisions that are made today influence the long-term health of our business. We're going to use an analysis process that is not commonly, if ever, used in Web Analytics.

We manage the Online Marketing Simulation (OMS) by linking conditional probabilities, simulating how a group of customers are likely to evolve over the next five years (or if you're analyzing social media, maybe the next five days!).

Let's look at a very simple example. You have three micro-channels in your online business.

  1. Online Orders via E-Mail Marketing
  2. Online Orders via Paid Search
  3. All Other Online Orders

In this simple example, 10,000 customers purchased in 2007 via paid search, not purchasing via e-mail marketing or via any other method of generating an online order. We follow the 10,000 customers to see how they evolve during 2008. Let's assume that the 10,000 customers migrated as follows in 2008:

  • 6,000 did not purchase during 2008.
  • 1,500 purchased via all other online orders.
  • 1,200 purchased via paid search.
  • 200 purchased via paid search and all other online orders.
  • 700 purchased via e-mail marketing.
  • 100 purchased via e-mail marketing and all other online orders.
  • 200 purchased via e-mail marketing and paid search.
  • 100 purchased via e-mail marketing, paid search, and all other online orders.

Since we are analyzing three micro-channels in this example, all via yes/no indicators, we have 2*2*2=8 possible future outcomes.

The majority of customers (6,000 of the 10,000, 60%) did not purchase during 2008.

Notice that 1,700 customers purchased via paid search during 2008. This is one of the interesting things that we don't take into account when using the web analytics tools from the leading paid and free vendors to measure conversion rates --- we don't factor in how today's actions influence tomorrow's business. In this example, 10,000 paid search customers in 2007 yield 1,700 paid search customers in 2008.

Are you budgeting for future paid search activity that you are causing because of today's paid search optimization activities?

This is what the Online Marketing Simulation (OMS) environment does. We look at the future trajectory of all customers. Instead of looking at three dimensions (paid search, e-mail, all other), we look at a dozen or two dozen or more dimensions. We look at many combinations of prior activity, measuring the percentage of customers who migrate to a future state of activity. And we don't have to look only at advertising micro-channels, we can fold in the merchandise categories the customer purchases from (or views online if you wish). Once each customer is placed in his/her future state, we replicate the process, showing where the customer will migrate in year two, then year three, then year four, then year five.

In the example above, we can estimate how much paid search expense we will incur over the next five years because of today's paid search and conversion rate optimization practices. We can estimate how many customers will purchase via e-mail marketing over the next five years because of today's paid search and conversion rate optimization practices. We can see how one merchandise category will grow or shrink if we change our e-mail marketing strategies. We can sum demand, expense, and profit, short-term and long-term.

In the next OMS post, we'll begin to work through an actual dataset with numerous dimensions, so that you can see how the Online Marketing Simulation (OMS) environment really works. The example will be representative of the type of consulting I do for clients, helping them understand how the online channel will evolve based on today's decisions.

As we work through examples over the next month, ask yourself four questions after each post:

  1. Can my Web Analytics software tool do this analysis?
  2. Can my Web Analytics analyst do this analysis for me?
  3. Can my Web Analytics software vendor do this analysis for me?
  4. Can the leading Web Analytics consultants / bloggers do this analysis for me?

If the answer to each question is "no", then the Online Marketing Simulation (OMS) is something you'll want to investigate.

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2 Comments:

At 5:48 AM , Anonymous Jay Allen said...

This is excellent, Kevin. I'm enjoying the Glieber's stuff, but the practical stuff is invaluable. Now to crunch some numbers . . .

 
At 10:27 AM , Blogger Kevin said...

Thanks for the message. Hopefully, it is different from what we usually read, and useful, too!

 

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