Should you disregard or include ex-customers in your marketing plans?

The previous post ‘How many customers do you have? Really.’ identified 8 distinct groups of customers based their current status. Two of these groups that rarely receive as much attention as they should are:

• Customers don’t exist – the customer company doesn’t exist for various reasons.
• Customers not using – customers that don’t use your product/service/solution.

Why should you pay attention to, and spend marketing resources on ex-customers? Because, firstly you can learn valuable insights and secondly there is potential revenue from your ex-customers. Most companies tend to disregard ex-customers because they view them as a lost cause and it’s too unpleasant or difficult to communicate or deal with ex-customers. But they’re missing out on a significant opportunity to improve their business by learning from ex-customers. And there is still potential revenue to harvest.

Customers that no longer exist – nothing you can do about customer companies that shut down, go out of business, merge, get acquired or cease to exist for whatever reason. However, there were people inside those companies that used your product, maybe even liked your product. These people have moved on to other companies, they know about your product/service/solution, you probably have their names in your database. Find out where they are now and reconnect. Someone with a positive previous experience with your product/service/solution can be a valuable contact to market and sell into the company where they currently work.

Customers that have stopped using your product/service/solution – this can happen for a variety of reasons including dissatisfaction, new management preferences, a competitive product/service/solution that better meets their needs or many other reasons. Losing customers is painful and costly and has a direct impact on Lifetime Customer Value (LCV). The customers you have lost can provide valuable insights to prevent losing more customers by applying those lessons for improving or correcting whatever caused them to defect. Proactively taking action based on empirical research and analysis from these ex-customers can greatly improve retention and loyalty for current customers.

“The Customers you lose hold the information you need to succeed.” – Frederick F. Reichheld

Just as most companies do a win/loss analysis on current sales deals, you need a continuing Customer Defection Analysis program to gather information from ex-customers for business and marketing plans:

• The first step is to categorize the reason for defection – let the information from ex-customers guide you to the right categories rather than preconceived internal opinions.
• Identify the underlying causes in the ex-customers’ context, that led to the defection. Look for commonalities and trends to determine appropriate corrective action to avoid or minimize future defections.
• Get information about when they stopped using your product, what they’re using now, whether they’ll make the same decision again, etc.
• Determine what other useful and relevant information to gather for the Customer Defection Analysis based on your specific business/ product/service/solution circumstances.
• Identify possible revenue opportunities with these ex-customers:
• Can you provide paid services to help them migrate from your system to their replacement system? I know this sticks in one’s craw, but getting someone from your company into the ex-customer environment to provide services can yield significant insights in addition to the services revenues.
• Can you sell them something that is either complementary to their new system or addresses a completely different functional area of the business?
• Put them on the contact list for appropriate marketing programs to stay in touch and consider your business/product/service/solution for future needs.
• Although gathering information from ex-customers may seem difficult, most people are usually willing to share the reasons for the decisions. Don’t be defensive, argumentative, judgmental or try to rectify the past – just listen and learn.
• Being understanding, supportive and helpful during this information gathering process can put your business in a more favorable position for possible business opportunities with ex-customers.

Are you currently disregarding or including ex-customers in your marketing plans? Has this article given you food for thought to reconsider your practices in this area? Your comments are always welcome.
Copyright © 2009 The Marketing Mélange and Ingistics LLC. http://marketing.infocat.com

Is the RFM customer analysis model relevant for B2B marketing?

Continuing the discussion about customer metrics and analysis from previous posts; this post explores the relevance of the RFM (Recency, Frequency, Monetary) customer analysis model for B2B marketers and businesses.

The RFM customer analysis model has been around for over 40 years and is commonly used by Retail, Database Marketing, Direct Marketing, Non-profits and other primarily B2C businesses and marketing organizations. I have personally only encountered minimal use of RFM in B2B marketing but believe there is value in using this model in some aspects of B2B marketing depending on the specific circumstances of a business.

The premise of the RFM model is straightforward:

• Recency – when did a customer last buy? Research shows that Customers who purchased recently are more likely to respond to an offer than those who purchased some time ago.
• Frequency – how many times has a customer bought? More frequent buyers are more likely to buy again.
• Monetary value – what is the value of their lifetime actual spend? Big buyers are more likely to spend more than small buyers.

The RFM analysis ranks each customer for each RFM factor on a 1 to 5 scale (5 is highest). The 3 scores together are the RFM ‘cell’ for each customer ranking their historical propensity to buy with a 555 customer ranking being the best.

The RFM model has limitations and risks such as:

• Historical behavior does provide indicators for future behavior, but it’s not truly predictive.
• Continually targeting high-scoring customers could annoy or alienate them.
• Neglecting lower-scoring customers that should be nurtured.
• Just analyzing the numbers without relating the RFM score to specific business, product and marketing events and circumstances.
• The 125 cell (5x5x5) RFM model is too granular – rather group scores into clusters or bands to get a better picture of what the data are communicating.

The RFM model could be a valuable marketing analysis and segmentation tool to complement and qualify other analysis and segmentation tools used by B2B marketers:

• Relating customer RFM scores to lifetime customer value (LCV) can provide insights for developing and improving revenues from existing customers.
• In addition to the RFM score, the trend or migration between cells over time can provide further actionable information for marketing.
• The RFM score trend over time for major customers or segments of similar customers can provide insights into changing buying behavior and revenue performance.
• Relating RFM scores to results for various campaigns can provide insights into the effectiveness and appeal of particular campaigns for different RFM segments of customers.
• Relating RFM scores to products or product categories. For example, if a customer buys something in a product category do they usually buy more in that category or does it lead to cross-sell opportunities in other categories. Or if they buy something of low monetary value does that lead to buying something of higher monetary value or vice versa.

Do you use a RFM analysis in B2B marketing and if so, how has it worked for you? Your comments are always welcome.
Copyright © 2009 The Marketing Mélange and Ingistics LLC. http://marketing.infocat.com