Kevin Hillstrom: MineThatData

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

March 06, 2009

Non-Linear Direct Marketing

Last week, I made a comment about online marketers ... "they're the folks who stare at you when you mention anything that cannot be immediately quantified with a conversion rate metric". Ted asked for clarification, suggesting that conversions, from a direct marketing standpoint, were a good thing.

It is my belief that direct marketing has always been non-linear. If direct marketing were linear, cannibalization would not exist.

It is my belief that direct marketing has always been treated as a linear process.

For instance, we've always talked about the purchase funnel, with linear concepts like "aware-consider-shop-buy-own". Given this linear process, we set up our KPIs, our "metrics", around this purchase funnel. Does the customer visit more than just the homepage? Does the customer put an item in the shopping cart? Does the customer buy something (conversion)?

These metrics allow us to measure success. The online marketer is uniquely qualified to measure each step in this process.

But ask the online marketer to answer any question that is non-linear, and the process falls apart. For instance, ask your web analytics expert the following set of questions:
  • Of all the customers who abandoned a shopping cart last week, what percentage visited the site again this week? And of those who visited the site again this week, what percentage purchased something?
You can answer this question with many web analytics software packages. That being said, few web analytics experts can answer this question for you. Even fewer online marketing experts can answer this question for you. If you ask this set of questions, you are very likely to get a blank stare. Go ahead and try it sometime!

This is important, because a customer originally labeled as a "failure" by a linear set of metrics (the customer abandoned a shopping cart) becomes a "success" because of a purchase the following week.
  • Our Metrics (Linear): Shopping Cart Abandonment = 50%, Conversion Rate = 50%.
  • Actual Outcome: Conversion Rate = 100%.
Now granted, this process is technically "linear" according to the definition of a purchase funnel. But the behavior of this individual customer does not fit our linear set of KPIs --- a successful outcome is actually recorded as a series of unsuccessful steps.

This is one reason that I typically review annual timeframes with a Multichannel Forensics analysis. We can see interactions better, we can see if a series of negatives result in a positive, we can see if combinations of advertising fundamentally change customer behavior.

7 Comments:

At 4:48 AM , Anonymous Ecommerce Recruiter.com said...

Great post. The very ideas of "response rate" and "conversion rate" presume a linear nature -- but the worldly reality of any response rate less than 100% demonstrates their non-linear behavior.

Kind of like a spray of shotgun pellets.

Harry Joiner
EcommerceRecruiter.com

 
At 4:14 PM , Anonymous Ted Grigg said...

You say, "It is my belief that direct marketing has always been treated as a linear process."

There is probably some truth to that. But experienced and talented direct marketers are anything but linear thinkers.

They understand that the buying process has never been linear.

The challenge is to figure out what parts of the buying decision advertisers can control and use to make money.

Witness the struggle marketers are having with social media. How much control do they have with this strategy? Probably more than they think, but less than they would like.

So in a world of growing complexity, the task requires that online and direct marketing analysts (these are overlapping disciplines) distill the mountains of data into a form that direct marketers can use to project sales and evaluate the success or failure of key strategic initiatives.

In my opinion, the marketer needs to work with simple formulas to evaluate and plan future marketing efforts. Could that be why some of us come across to you as linear thinkers?

Hence the cost per lead, cost per sale, cost per customer and their derivatives. These are still the basic formulas for evaluating the success of direct response campaigns.

In my mind, the analyst must help expose inefficient or under performing activities to refine the selling machine.

Not to be too judgmental, but I find that some analysts tend to revel in the data without providing actionable recommendations.

In my experience, the best direct marketers and analysts know how to look at the data and quickly discover the weak spots and expansion opportunities.

So success comes as a result of simplifying the complexity of it all.

 
At 4:29 PM , Blogger Kevin said...

Thanks for your comments, Ted. We can probably agree to disagree on certain issues, and agree on the vast majority of direct marketing topics. Regardless, many clients benefit from either point of view.

 
At 6:22 PM , Blogger Kevin said...

I will say, Ted, that this is the kind of conversation that is just plain missing in direct marketing. Neither side is right or wrong, both sides are essentially right in many instances.

Outside of a few blogs, however, this discussion isn't happening publicly, and it hurts our industry.

 
At 6:23 AM , Blogger Chris Greco said...

I'm curious to know why you believe this conversation is missing. Path analysis and optimization is part of the conversation. What is proposed in this article appears to be a natural extension and evolution of this.

 
At 6:26 AM , Blogger Chris Greco said...

FYI...my question 'fuses' your points from 'Non-linear DM' and 'Channel Migration Visualization'

 
At 7:56 AM , Blogger Kevin said...

Hi Chris, I think there are a couple of different topics being considered.

The analytics community is very comfortable with conversion paths. And many linear direct marketers are comfortable with conversion paths.

However, the conversion paths lead to dead ends --- at Nordstrom, we knew that our best customers visited the website three times a month, visited the store twice a month, and purchased once a month --- 85% of the time in-store. Well, traditional web analytics simply fall apart when trying to measure this relationship. Under the scenario I just described, we have a measured conversion rate of (0.15) / 3 = 5% ... and yet, the customer converted at a 100% rate.

This process is non-linear ... and our system of metrics is poorly calibrated to observe this phenomenon.

Worse, our business leaders struggle with this --- they're given tools that tell us that conversion was 5%, with abandoned carts and the like, while the customer is essentially satisfied. So we work hard to improve the website, only to find that we don't ever move annual retention rate or purchase frequency.

This latter discussion is not well understood in our industry. It is complicated. Ted is right to suggest that analysts fail to make things easy for business leaders to understand. And few people ever talk about this level of complexity / simplification.

 

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