High ROI Customer Marketing

Relationship Marketing, Customer Retention, Customer Loyalty, Database Marketing, CRM,  Frequency Marketing, Permission Marketing, and One-to-One Marketing are all customer value-based approaches.  They may be different in how they are "positioned" to the customer, but all have the same objectives: 

1. Retain your best, most active customers
2. Increase the value of most customers

If your methods for retaining and increasing the value of customers are money-losers, you'll go out of business trying to keep your customers.  A customer value-based marketing plan also has to be profitable.

To retain and increase the value of customers, you have to engage them by communicating on a regular basis.  If you don't, customers will be less loyal and either abandon you for a competitor who communicates with them, or will spend less with you over time.  Marketing promotions are essential to any kind of customer retention effort; promotions drive the sales activity of customers.

Customer retention results when you make, and the customer accepts, new offers over time.  This process is an ongoing renewal of the relationship with a customer.

There are three key components to maximizing profits in customer marketing:

1. Structuring offers to get the most profitable mix of response rate and cost of the offer.  You don't want to limit response (offer too weak), or give away the store (offer too rich).

2. Creating an "early warning system" to flag customers who are likely to leave you so they can be targeted for special promotions.  This is accomplished by tracking customer behavior.

3.  Identifying customer acquisition practices that optimize the value of new customers coming to the business in the first place.  You want to identify advertising, products, and areas of the site that generate the highest value customers over the longer term.  This key concept is the subject of the tutorial.

Profitability of Offers

The profitability of customer promotions depends heavily on two data points - the response rate and cost of the offer.  This is true for "hard" offers like discounts / upsells, and "soft" offers, like service upgrades.  

At any given time, some customers are more likely to respond than others.  This likelihood to respond is then influenced by the size (cost) of the offer you make - the discount or giveaway.  A customer who did not respond to a 10% discount might have responded to a 20% discount.  Similarly, a customer who would have responded to a 10% discount may be offered a 20% discount, and take it.  Both these situations cost you money, either in lost response or extra discounts you did not have to give!

Ideally, you would like to have a consistent way to identify the likelihood of a customer to respond, so you could determine the most profitable offer to make to each customer - before you send out the promotion.  Customers highly likely to respond would be given a lower value offer; customers less likely to respond would be given a higher value offer.  You get increased response with lower promotional costs.

Does it make sense to you?  The idea is to allocate your precious budget dollars according to how much "work" they have to do to get a customer to respond.  Instead of making the same offer to everybody, you make a less expensive offer to customers likely to respond, and using the money you save, make a more expensive offer to customers less likely to respond.  This approach increases your response rate while lowering your promotional costs, and has the overall effect of retaining your best customers while increasing the value of most customers.  Here's a fact:

You can predict the likelihood of a customer to respond.   Likelihood to respond scores are created for each customer using a simple spreadsheet (or by writing a scoring program, if you have the resources).

Identifying Best Customers at Risk

Now think about this.  If you can predict the likelihood of a customer to respond, what does it mean when this likelihood begins to fall?  For example, when a customer is one of the most likely to respond and then falls to the "middle of the pack?"

That's right, they're in the process of leaving you.  Something has happened - maybe product problems, service problems, new competition - to make this customer become less likely to respond.  When you see falling likelihood to respond scores, your "early warning system" has kicked in, flagging customers beginning the process of defection - of taking their business elsewhere.  It is critical to identify this behavior in a timely way, and take action to reverse it.

In fact, when you score your customers for likelihood to respond for the first time, you will find that many of the low scoring customers are former best customers.

Optimizing New Customer Value

There's more.  Think about this - have you heard of the term LifeTime Value?  Lifetime Value is the current value plus the expected future value of a customer.  If you know the likelihood of a customer to respond, what do you know about their future value?

A customer who is more likely to respond has a higher future value than a customer less likely to respond, by definition.  So you can use this scoring technique not only to determine likelihood to respond, but also to compare the future value of customers.  

So what?

If you can compare the future value of customers, you can organize your business around customer value.  You can specifically tie any activity in your business - ad sources, search terms, products, areas of your site - to future customer value.

If the customers coming from one ad have high likelihood to respond scores (high future value), and the customers coming from another ad have low likelihood to respond scores (low future value), which ad is the more profitable ad for your business longer term?

If the customers who buy a certain product have high future value, and the customers who buy another product have low future value, which product do you feature?

If the customers who frequent one area of the site have high future value, but the customers who frequent another area of the site have low future value, which area do you promote?  Which area do you fix?

You can use the data customers leave behind through their interactions with you to create likelihood to respond scores, and use these scores to dramatically increase customer marketing profitability.  The Drilling Down book teaches you how to build and use these scores yourself in 30 minutes with an Excel spreadsheet.  If you want to increase sales while reducing the costs of marketing to customers, you have to get this book.