Category Archives: DataBase Marketing

Measuring the $$ Value of Customer Experience

Marketing IS (Can Be?) an Experience

Early on I discovered something from the work of leaders in data-based marketing business models: they were always very concerned with post-campaign execution – not only from  marketing, but also through product, distribution, and service. I thought this strange, until I realized they knew something I did not: when you have customer data, you can actually identify and fix negative customer value impacts caused by poor experience.

This means you can directly quantify the value of customer experience, budget for fixing it, and create a financial model that proves out the bottom line hard money profits (or losses) from paying attention to the business value as a result of customer experience.

And critically, this idea becomes much more important as you move from surface success metrics like conversion and sales down into deep success metrics like company profits. Frequently you see the profit / loss from “marketing” often has less to do with campaigns and more to do with the positive or negative experiences caused by campaigns.

Examples

You might think taking the time to provide special treatment to brand new customers would always encourage engagement and repeat purchase. You’d be wrong. Sometimes this works, sometimes this does not work, depending on the context of the customer. Does it surprise you to find out customers often do not want to be “delighted”?

Continue reading Measuring the $$ Value of Customer Experience

Omni-Channel Cost Shifting

One of the great benefits customer lifecycle programs bring to the party is unearthing cross-divisional or functional profitability opportunities that otherwise would fall into the cracks between units and not be addressed.  What I think most managers in the omni-channel space may not realize (yet) is how significant many of these issues can be.

To provide some context for those purely interested in the marketing side, this idea joins quite closely to the optimizing for worst customers and sales cannibalization discussions, but is more concerned with downstream operational issues and finance.  Cost shifting scenarios will become a lot more common as omnichannel concepts pick up speed.

Shifty Sales OK, Costs Not?

Why is cost shifting important to understand?  Many corporate cultures can easily tolerate sales shifting between channels because of the view that “any sale is good”.  On the ground, this means sourcing sales accurately in an omni-channel environment requires too much effort relative to the perceived benefits to be gained.  Fair enough; some corporate cultures simply believe any sale is a good sale even if they lose money on it!

Cost shifting  tends to be a different story though, because the outcomes show up as budget variances and have to be explained.  In many ways, cost shifting is also easier to measure, because the source is typically simple to capture once the issue surfaces.  And as a cultural issue, people are used to the concept of dealing with budget variances.

Here’s a common case:

Continue reading Omni-Channel Cost Shifting

Marketing Funnel Not Dead, Using Funnel Model for Attribution Is

It’s become fashionable to declare the “Marketing Funnel Model” dead.

For example, here is a post worth reading on this topic by Rok Hrastnik. There are some very good points in this post on why using a funnel to attribute media value is really a troubled idea. I was flagged on this post because it has a quote from me that seems to support Rok’s  thesis about the death of the funnel model and the related idea, “Direct Response Measurement is a Wet Dream”. The quote is from a comment I made on a post by Avinash where we were discussing the value of sequential attribution models:

There are simply limits on what can be “proven” given various constraints, and that’s where experience and a certain amount of gut feel based on knowledge of customer kick in. If you can’t measure it properly, just say so. So much damage has been done in this area by creating false confidence, especially around the value of sequential attribution models where people sit around and assign gut values to the steps. Acting on faulty models is worse than having no information at all.

But none of this means the Funnel Model is dead, or that Direct Response Measurement overall is a Wet Dream. What’s (hopefully) dead is people using the funnel model inappropriately for tasks it was never designed for, in this case multi-step attribution of media value to goal achievement. On the other hand, if this specific funnel use case is what Rok was coming after, I agree, because it didn’t make any sense to use a funnel model for this idea in the first place.

Let’s unpack these ideas

Funnel thinking is based on a relatively reliable model of human behavior, AIDA.  This model from human psychology does not specify tools, channels, or media.  It simply says that there is a path to purchase most humans follow. That is:

A – Attention: (Awareness): attract the attention of the customer
I – Interest:  (Intent) promote advantages and benefits
D – Desire: convince customers the product will satisfy their needs
A – Action: lead customers towards taking action / purchace

Example: I’m Aware of tons of products I would never buy. There are lots of products I think are Interesting but I have no Desire for. There’s a short list of products I Desire but have not Acted on. The list of products in my head worthy of purchase consideration gets smaller and smaller at each stage of the AIDA model. This is the funnel.

The AIDA funnel has not changed and it’s not dead.

It’s a model of human behavior, not media consumption.

Continue reading Marketing Funnel Not Dead, Using Funnel Model for Attribution Is