The first was the introduction of the browser in the mid 90’s.  Suddenly you could research product details, examine similar products across different sellers, and read professional reviews published by magazines online.  Consumer immediately eliminated the information imbalance that had existed for all of civilization, where the seller always knew more than the buyer.

The second came quickly after the first, with the widespread usage of search, which allowed consumer to learn a huge amount about a specific category or product in a short period of time, including prices and sellers, in just a few minutes.  This meant that it was likely a consumer knew more about a specific product or category than an associate standing in a retail store who had received 8 hours of training before getting thrown on the floor.

The third was the advent of ratings and reviews, thanks primarily to BazaarVoice and Amazon.  Now consumers had a pool of primary research to draw from to evaluate the qualitative differences between products. It also exposed flaws and other non-obvious positives and negatives, putting consumers even farther ahead of sellers.

The fourth and fifth waves started nearly simultaneously – the social wave and the smartphone wave.  Social tools allow near real-time feedback from trusted sources and the crowd when a decision needs to be made, and mobile access allows the use of all tools anywhere, any time.  Both are rapidly transforming the nature of commerce, with Amazon’s recent overt effort to divert shoppers while actually in a competitor’s store representing the beginning of a brutal competition for customers.

The sixth wave, which is just now getting started, is the model wave.  There’s now enough information available on an individual to build a meaningful predictive model around ability to spend, share of wallet, propensity around certain products and categories, and many other potentials.  When the vast trove of behavioral and attribute data is run through parallelized processors, really interesting models can be developed.  And when event and transactional data is run through grid-based, in-memory rules processing, very fast decisions, offers, suggestions, and other behavioral “nudges” can be made.  Its the ultimate in information arbitrage: in order to get ahead of consumers, companies need to figure out what consumers want before they know it.

So marketers need to start finding great options for the technology to enable the sixth wave (I know a good one that happens to sign my paychecks) and great talent that can develop and administer the models themselves.

Marketers can take great advantage of Inertial loyalty, through a steady stream of marketing messaging and impluse drivers.  These customers will continue to respond and interact, without much prodding.  At the same time, these customers have no explicit tie to your company, so they can be persuaded to leave at any time.  Witness the 8% increase in churn at Verizon since the iPhone was introduced, which is a lot in mobile.

How do you identify this?  Not easily.  Customers who do not engage with the brand are far more likely to have Inertial or Involuntary Loyalty, although many customers with real loyalty also fall into this category.  The best way to address these customers is to migrate them to Rational or Emotional Loyalty.  At least then you have tools to improve loyalty.  Most likely your Rational Loyalty efforts will also resonate with these customers.