Flipping a coin and determining whether it will come up heads or tails depends more on the fact that a tossed coin obeys Newton’s laws of motion than a simple random chance. With sales opportunities, like pennies, a bias has a huge bearing on the result. So if you want to improve your odds flipping a coin or managing a sales opportunity, spend some time thinking about how to create and maintain a bias in the mind of your customer.

How do you forecast a bias?

As with predicting the outcome of a coin toss, you might be surprised that a bias will skew your forecast. Ivars Petersen is a mathematician who illustrates why unexpected results shouldn’t come as such a surprise. The Lincoln penny provides a striking example of such a bias. Stand a dozen or so pennies on edge on the surface of a table. Then bang the table so that the pennies topple over. You’ll find that nearly always more heads than tails are face up. Sometimes all the coins end up heads. On the other hand, spinning pennies tend to land tails more often than heads.

Probing creates awareness that creates a bias.

April is Mathematics Awareness month. I’ve instantly created a bias in your mind about April, besides the first day being All Fools Day and showers that bring May flowers and that fact that there are 22 selling days in April. Now you have a mind full of data and awareness about April.

It’s no different than creating a sense of awareness with your customer. Just answering a customer’s question creates no advantage when new bias data is added to the customers mind. Essentially he now perceives everyone your response as the same as any other response.

By probing the customer for more information and understanding what’s driving their need, you now have ample opportunity to create a greater awareness (bias) of your products and services. This is not to say that you should stand there and rattle off 100 of your best features. Quite the opposite is required. Give them only the information they will value the most. You now have the bias on your side of the coin. Find out too if your competitor has a bias e.g. brand name, better warranty, less risk and ‘one up’ your own bias.

MosaicCRM Experts Corner

Beyond the operational aspect of CRM, most databases are chucked full of analytical data. One problem we see is that this analytical data is rarely configured for optimal ‘bias’ applications e.g. learning what customers want to buy at this very moment.  What do they look like, how much do they spend, when, how often is too often seen as information overload when in fact just the opposite is true: customers now get exactly what they want because you know them inside out.

As a side note, we do see social media as collaborative CRM data used as a vehicle that communicates with customers but this isn’t the same as using your CRM database for predictions analysis.

To maximize CRM’s return, it operates best in a forward looking mode and least optimal in a rear view looking transactional recording mode. For example, one of the best known predictors is credit analysis. Wouldn’t every organization want the same level of predictability with their customer base or at least their pipeline? Start with defining CRM data models and routines to optimize predictable outcomes and biases for:

• Cross Selling/Up Selling
• Supporting Customer Loyalty/Retention
• Minimize Customer Attrition
• Improving Sales Forecasting/Decision Making
• Better marketing relationship with the customer

______________________________________________________________________________________________

Written by
Bill Noonan, CEO MosaicCRM

______________________________________________________________________________________________