They understand that old-school, handwritten thank-you notes are a low-cost, high-impact customer retention strategy.
Incorporating customer requirements into operating processes Creating a customer-focused value proposition Measuring and managing the Total Customer Experience Increasing share of wallet Each of these tools can be used individually and quite often are. However, when used in combination to create an enterprise-wide, holistic view of revenue and profit opportunities in prospective and existing customers, they produce a customer-focused operating framework that improves marketplace performance and business results.
An existing customer base contains real growth potential, but many companies fail to realize its full potential. Often, more energy goes into attracting new customers than looking after current ones. However, it is generally recognized that the longer a customer stays with a company, the more that customer is worth.
Long-term customers buy more, take less of a company's time, are less sensitive to price, and bring in new customers. Best of all, they have no acquisition or start-up cost. The difficult challenge in developing effective approaches to reducing both kinds of churn is to be able to identify predictors of each type of churn and take corrective actions to address the problem.
Predict Customer Defections and Reduced Purchasing Most companies have large amounts of data on customer purchasing behavior, although it is frequently in several different databases. Fortunately, technology is available to merge these disparate sources of data and provide the necessary predictors of churn.
Predictive Analytics Predictive analytics is data mining technology that uses your customer data to build a predictive model specialized for your business. This process learns from your organization's collective experience by leveraging your existing logs of customer purchases, behavior, and demographics.
The wisdom gained is encoded as the predictive model itself.
Predictive modeling software has computer science at its core, undertaking a mixture of number crunching and trial and error. A predictive model tells you which new customers are likely to return and which are probably one-timers.
The model is created with data mining methods that "learn" from the collective experience of your company contained in your sales records. The model then applies what has been learned to produce a predictive score for each new customer in real time.
In this way, new customers you would otherwise never see again are targeted and enticed to stay. Because you don't waste the retention offer on new customers likely to return, the numbers work out very well.
The growth rate and medium-term profits potentially skyrocket, and immediate-term profits are not put at risk. These tools can identify trends of customer segments in various ways: Typical sales trend analysis includes: Which customer segments are having highest growth in dollar terms?
Which customer segments are having highest revenue decline in dollar terms? Which customer segments are having highest growth rates in percentage terms? Which customer segments are having highest revenue decline rates in percentage terms?
How solid the growth or decline trend is? Which customer segments are showing exponential growth or decline? Once churn detection models are developed, they can be applied to your customer databases on a regular basis.
This will let you identify customers who have potential for defection but have not been contacted for retention purposes recently.
Preventive actions can be followed for customers who have been identified as potentially at risk of either defecting or reducing purchase volume.
IBM Institute for Business Value Segmentation is a well-known and widely-used marketing practice used to identify prospects and customers who are similar in terms of specific criteria and different from other prospects and customers in terms of these same criteria.
These similarities and differences allow the customers and prospects to be segmented into distinct groups. Unfortunately many companies take an overly simplistic a priori approach and end up with segments that are not maximally differentiated.
Limitations of A Priori Segmentation A priori segments are the most basic way of creating market segments.Business leaders can't develop and execute effective strategy without first gathering the right information, says Harvard Business School professor Robert Simons.
One way to think about customer acquisition management is to consider it the link between advertising and customer relationship management, as it is the critical connection that facilitates the acquisition of targeted customers in an effective way.
The Customer Acquisition Process. Customer acquisition requires forethought and strategies. Strategy Growth. Strategy. Customer Value Proposition. Internal Perspective Learning & Growth Management Processes -Supply, Production, Distribution, Risk Mgmt. Customer Management Processes -Selection, Acquisition, Retention, Growth Innovation Processes Mapping Your Corporate Strategy, HBR Working Knowledge Interview with Robert.
EES&OR Strategy and Marketing Primer (version ) This set of "crib notes" is a review of marketing and strategy tools and concepts that you may find useful for your project in EES&OR