Manage-Wise

The CRM philosophy

After ERP and SCM, Customer Relationship Management (CRM) alias Efficient Customer Relationship (ECR) has been touted as the next business elixir, the ultimate business enabler that would make the customers jump up in glee and would drive them to any shop to part with their hard-earned cash (or at least a part of it). Suddenly the ailing retail businesses all over the world are looking at this miracle drug to rejuvenate their businesses. Millions of dollars have already been spent, with billions in the pipeline, to implement the perfect CRM strategy. Not surprisingly, hundreds of software vendors and solution companies have overnight arrived at the retailers’ doorsteps with their “CRM” solutions, each solution being better than the other. Equality unsurprisingly, the benefits have been scant and scarce. Most importantly, the greatest benefits have been accrued to companies who didn’t necessarily go for the best and the costliest solutions. Before we try to analyze what they did right that others didn’t, let us look at something that needs to be done before one can think of implementing a CRM strategy.

Pre-implementation plan

I would like to take recourse to a saying from the recently released movie “Spiderman”. Spidey says—“with great power comes great responsibility”, in the same vein it can be said—“Great strategies require great organization preparedness”. Also, we should try to remember that simplicity is the hallmark of true sophistication.

So before you can think of implementing CRM, you need to make sure that you have the enterprise and the so very important back-office all geared up to implement the strategy—in other words, your organization is ready for CRM; culturally, operationally and intellectually. You also need to make sure that the CRM strategy is simple, scalable and focuses right on the most important customer touch-points.

This is what differentiates the success stories from the spectacular failures. Any strategy requires planning, execution, review and refining. CRM is no exception.

Getting retail specific

So let’s now talk about CRM in retail. Well, to build a real good CRM model, one needs to identify the valuable customers first and then to make sure that he/she manages at least to keep this customer base intact (which means replenishing and updating the customer base).

But how does one know who are the best customers? What are their characteristics? How long does he/she going to be with you? Do they give any indication when they are going to leave or when they are getting more interested in your product and service offerings?

The secret lies in a simple thing. Any high ROI customer-marketing program works on a simple concept—tracking, understanding and profiting from the customer life cycle.

What is a customer life cycle?

It is simply the behavior of a customer with your company over time. Customers begin a relationship with you, and over time, either decide to continue this relationship, or end it. And any point in this life cycle, the customer is either becoming more or less likely to continue doing business with you, and demonstrates this likelihood through their interactions with you.

If you collect data from these interactions (purchase for commerce, page views or log-ins for publishing, contacts for service) you can use this data to predict where the customer is in their life cycle—is the customer becoming more or less likely to do business with you? If you can predict where customers are in the life cycle, you can maximize your marketing ROI by targeting customers most likely to buy, trying to “save” customers who have declining interest and not wasting money on customers unlikely to continue doing business with you.

Great! We need to model the CRM strategy in such a way that we can understand the customer life cycle and we can measure where he is in the life cycle and then can take necessary actions. But how do we calculate the customer’s life cycle and his LTV (life time value)?

Analyzing behavioral patterns

Simple, we calculate the customer life cycle just by looking at the customer data and analyzing the behavior. We don’t need to determine the length, just need to analyze the behavior over a pre-determined time period. Whoever buys more, is a better customer! And as far as LTV is concerned, instead of getting into rigorous calculation of lifetime values, we just need to look into relative lifetime values over a predetermined life cycle. The higher relative lifetime value would automatically indicate higher absolute lifetime value. The important thing to remember that lifetime value is the profit given by the customer over the life cycle, so other things remaining constant, and the longer the life cycle, the greater the value. And the better we interact with the customer, the longer is the life cycle.

But now, how do we know which customer gives, or would give, a better LTV? Of course from their purchase behaviors.

Customers talk to us through their purchase behavior. I would take this opportunity that the behavioral profile is a far greater enabler than than the demographic profiles. What is more important to you as a retailer—“The customer is in his early 30s, earns INR 50,000 and above, lives in the upstate neighborhood and reads Times of India” (demographic profile) or the fact that “He came to the shop twice in the month before last but hasn’t visited the store ever since!” (behavior profile)? Obviously the second one. You may customize the heck out of your store for a certain type of customers but it won’t mean a dime if the customers don’t visit your store.

So in order to assess a customer’s LTV, we will focus on certain behavior metrics. And now we would introduce the concept of “recency”, in whichever way one conducts customer data mining, recency always come out as the top parameter. Stated simply, it means that the most recent customer is your most valuable customer. The customer who visited your store a month back is more valuable than the customer who visited the store six months back. This is the reason we get a mailer immediately after we buy something from a catalog stores.

After recency, the second most important parameter is “frequency”. The more frequent the customer is, the more valuable he is. The third metric is monetary value and it makes intuitive sense. The more money the customer spends upon you, the more valuable he is. But remember that a person who spent 1000 bucks on you six months back is never as important as the person who spent 250 on you yesterday.

Excerpt from ‘RETAIL STORE`e’ by Dr Raja Roy Choudhury. Published by 3rd Eye Knowledge Foundation. Copyright @ 2008. Rs 325