Month: March 2015

(Photo: New York Times)

Modern CRM (Customer Relationship Management) emerged from the boiler rooms of corporate sales departments. They needed a way to keep track of contacts, leads, calls, and ping schedules.  Soon they added client information like DOB, Spouses name, neighborhood news, etc.  The customer responded remarkably well, in fact, perhaps too well – they started asking for things like better service, warranty claims, and “can I get that in purple”.

Salespersons, being so closely tied to the revenue, began telling the service department that they are choking revenue,  and telling the warranty department when customers are defecting, and telling engineering to introduce new features.  They got away with it because they had management support as a revenue driver.  Pretty soon CRM systems began migrating across the enterprise evolving along the way. Ironically, CRM now finds itself losing touch with the customer despite the ever increasing amount of data that now populates the hit sheets.

Recently, we were asked to consider scenarios for Curiosumé applications in a CRM role in the financial industry. There are several important features of Curiosumé that can reconnect the customer to the enterprise.

Top level ontology in the commons
Instead of controlling people’s information, set it free and watch where the client leads you.  When all market channels pull their information from the same network of nodes and branches, they can always be current and synchronized. When the client adds information to the commons, this becomes available to the vendor outside of a firewall eliminating many security issues.  You don’t necessarily need (or want) to know the ID of the client in order to serve them better.

Anonymity layer / autonomous matching:
AUPOT (Anonymous Until Point of Transaction) allows clients to deploy anonymous personas so that they will be more willing to;

• reveal true intentions to the commons,
• perform their own pre-analysis in the commons
• increase their insights and contribute that to the commons.

Customer Controls Their Data:
Help the client own and control their own engagement data.  Give them the same tools and opportunities to experiment as researchers as the Big Data wonks have.  Allow them to delete, save, edit or have as many different personas as they want. Let them deploy and retract personas as a way of finding you.  A better and more efficient relationship will emerge between both sides of a transaction.

User interface layer:
Instead of leading your client like cattle through an arbitrary ontology tree, show them photographs that corresponds to nodes in the common ontology.  These can then be matched algorithmically to advisors, products, or different departments in the firm, in real time.   In essence, you can create a multi-agent algorithmic game in a user interface that could be fun, engaging, and sticky as heck.

Advisor interface:
When a client chooses to engage the advisor or a product or a transaction,  they can submit their persona into the algorithm to select specialized advisors or a team of advisors. Only at the point of mutual acceptance, both players cross the firewall and engage in honest, trusting commerce. Layers and layers of bureaucracy, vetting, and security breaches can be eliminated until the actual exchange is made.

(Photo: The Philadelphia Orchestra)

Powerful Feature:
One of the most powerful and least recognized features of Curiosumé is the ability to constrain a “score” to a number or a range. One reason for this is to create imbalance around the mean – when the system is not balanced, it can never be static and will always have some movement (regression toward the mean).  It will become largely self-managing, self centering, and even a little joyous.

For example: if we constrain the client to having a Curiosumé score of zero; that means that for the total of all (+) sigmas, they must also accumulate an equal and opposite total of  (-) sigmas such that their net total is zero, in order to pass “go”. When we lay this back on to the top level ontology (Wikipedia), we can find a series of paths that unite the (+) sigmas to the (-) sigmas.  This path tells us a GREAT deal about where the client wants to go.  Likewise an older client may prefer a net (+) portfolio where a younger client may prefer a net (-) portfolio.  Decentralized CRM with Curiosumé can also be applied to risk pooling in the same manner. The deviation s from the mean and resulting movements are precisely how we would price the derivatives of intangibles, i.e. tangibles.

Outcome:
Decentralized CRM with Curiosumé is readily ready to happen. We know that people, advisors, and products can be brought together in personal and emotional engagement when they intersect paths of common interest. This is the weakness of both the barter system AND modern technological Capitalism  If we can envision interests flowing dynamically along vectors, we will have the ability to align human incentives and the markets that depend on them.