The Trust Profit

John Robb is a prophet who has proven his wisdom, but the BigCos don’t get it, and I wonder if they’re suffering from a structural problem. Today he describes a project he helped create at Gomez where they were able to tie their fees from business clients to their clients’ customers’ satisfaction levels, yielding unprecedented profits.

Here’s John’s formula describing what works:

Focused content –> Trusted decision support —> Performance-based advertising = huge profits

Let’s break it down. Trusted decision support is the heart of this success story. Clients and customers who defer decisions due to, well, indecisiveness, leap into a transaction when they understand the quantified benefit of a prospective purchase. Amazingly, companies are united in their rejection of the simple technique of tracking the measured quality of their transactions. As John reports,

Of course, this isn’t going to happen anytime soon.  Why?  Trust needs to be inserted into the equation.  Trust by customers in the decision making tools.  Trust by media companies that advertisers will accurately report their customer conversions.  Trust by the advertisers that the decision making tools will be objective and not treat them unfairly.  As always, trust is in short supply, but I think that can change.

John believes that web logs and knowledge logs will eventually help us compile the record of trust left by a satisfied customer. I’m interested in the mechanics of capturing the customer’s feelings before the tears of gratitude are dry. Since Trust is the key, the obvious question is…

Who Do You Trust?

Everyone has a great bullshit detector, because we were all children. We’ll accept a remarkable range of rumors as facts, but we carefully filter the facts we trust with our money. Presented with a pitch, we reject it out of hand. Presented with a fact, we assume it’s false if a statement by the seller. If it’s a quote by a previous customer, we listen with new openness. If it’s a statistic reporting the satisfaction ratings of past customers, we take notes and act on the evidence, as John reports. Companies’ failures to report their customers’ satisfaction costs them billions every year. Despite that cost, companies will refuse to report satisfaction because of the risk that even a few transactions will be unsatisfactory. Of course they will, but companies can’t release the illusion that all their efforts are perfect.

So we can’t trust the sellers to report the good, the bad and the ugly, then we have to look to the customer’s records for the truth, but we need a means to compile all customer ratings of a seller into a meaningful overall average rating compelling enough to attract a new prospect. The average rating must be supported by enough detail that the prospect can drill down into the individual tasks’ ratings and customer comments to feel the fabric of the seller’s tapestry of quality. This will require a disciplined but distributed data store comprising all buyers and sellers willing to subject themselves to its rigor and to maintain the data according to an agreed-upon standard. This looks daunting to me, but Xpertweb provides all those attributes in a way that makes it as accessible as blogs are becoming.

There’s never been such a data store, but never before was there a world wide web and XML. Their very existence implies a shared satisfaction data standard.

Brought together, they demand it.
10:56:23 PM    

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