I break analytical marketing into two families: performance optimization and performance improvement. Both families are equally popular these days. However, I'm still seeing significant frustration landing "analytical marketing", particularly in large companies. Smaller "born on the web companies" have no problem at all with this. Generally, the founders of these companies built the core strategy around analytics, hired people comfortable with these concepts, and have woven analytics into the core IT systems of the company as it has grown.

However, for larger "digital immigrant" companies, weaving analytics into marketing can be a daunting task. It's no accident that large global consultancies like IBM are investing heavily in analytics consultants. They've realized a simple truth: that no matter how many fancy new airplanes an airline has, they won't get off the ground without skilled pilots and mechanics. So, why not just book a ticket on United?

I can't take credit for the pilot / mechanic / airplane /airline analogy, but it's a good one so I'll use it shamelessly. To be clear:

• Pilot = analytics marketing professional. A dork like me. There are different kinds of pilots. There are the ones that can only fly the plane, and then there are the ones that can also probably start their own airline.
• Mechanic = data warehouse, SAS server, web analytics etc. software guru. These are the people that actually understand how the plane is put together and fix it when it breaks.
• Airplane = the data warehouse, SAS, etc. software itself, or "cloud", doesn't matter. These are the $100,000 + CAPEX investments that make analytics possible.
• Airline = IBM Global Services etc.--the firms that will just do this stuff for you. You just get on the airplane and it flies you where you want to go.

Looking at it from the company's perspective that just wants to get better at customer insight, targeting, ROMI, web ad optimization, etc., it's a very difficult strategic question: Where should I start? One could make an argument for starting at any of the four bullet points above, and I can think of case examples of companies who have gone down each path. But, I'll give you what I think the answer is now.

• Don't even bother hiring mechanics if you are less than $500 M in revenue, unless you were born on the web. It's extremely expensive; the people that can truly build great systems are few and far between, and the pain will be enormous.
• Everyone who wants to do analytics needs at least one good "senior pilot". All the other stuff might be outsourced, or you might fly United, but you need one person who really understands the stuff and can direct vendors, etc.
• Whether to buy airplanes or not depends on business context. I'm a huge fan of the cloud and renting airplanes, and this is getting more and more feasible. Companies that provide managed ROMI environment that still house your data like MSights are a powerful option. However, for large companies, buying other components selectively can make sense. And it certainly makes sense if you were born on the web.
• Full-service airlines can also make a lot of sense. Totally outsourcing all analytics to IBM might be the way to go if your culture is simply not built around digital and it's not a core focus. Over time, the company may get enough digital natives on board to make analytics a core competency.

"Barrier Removal" is a tactic I've used to great effect many times in strategic situations where customers don't seem to be behaving the way companies want them to. In many cases, to a customer, there are hurdles galore when getting information or making a purchase. To companies, these barriers may not be at all apparent.

Barriers can be physical, rational or emotional. Physical barriers might include:

• Long load times on a web page
• Credit disapprovals at a car dealership
• Small type size in an ad
• Long distances to a dealership

Rational barriers might include:

• Higher prices than competitors
• Feature sets mismatched to needs
• Confusing steps to buy

Emotonal barriers might include:

• Fear of the unknown
• The brand doesn't match my identity
• Distrust of the product / brand

When a marketer adds up all the barriers, you get something similar to a Markov chain. Each barrier can be thought of as "erected" or "non-erected." A non-erect barrier means the probability of a customer passing through that barrier is 1--because the barrier doesn't exist. But an erect barrier will cause some fall-out, and will effect all downstream barriers, too.

Doing a buying analysis based on barriers can be a powerful tool. One gets the sense that a company like Apple has done them in their retail stores, but maybe not for their B2B business. Looking at an Apple store, there are very few barriers.

Physical:

• Everything is in stock
• The stores are close to target populations
• There are products available for demo all the time

Rational:

• Prices are clear and intuitive
• Features meet consumers' needs
• Buying is simple--just talk to an associate and you walk out with your mac / ipod.

Emotional:

• The store is appealing and comforting
• The brand is trusted

However, when you look at B2B, there are barriers galore.

Physical:

• Where does one go to get Mac for business? The store? A distributor?
• What if my battery runs out? Why are the batteries internal? (some insulting me emotion here.)

Rational:

• Apple doesn't work seemlessly with Office. Or does it (some confusion mixed in here.)
• Apple doesn't make servers.
• There isn't enough business software available for Apple.

Emotional:

• I've never thought of the Apple brand as being built for businesses.
• Apple spends all its time marketing iPods.

Anyway, it's a simple example for illustrative purposes. But I love doing these barrier / hurdle projects. Maybe I'll do another post on the simple math... which gets to the upside business case of barrier removal.