|
|
DSC Tech Library
This section of our technical library presents information and documentation relating to CRM Solutions and Customer relationship management software and products. Providing customer service is vital to maintaining successful business relationships. Accurate and timely information provided in a professional manner is the key to any business and service operation.
Telemation, our CRM software application, was built on this foundation. But the flexibility to change is just as important in this dynamic business environment.
Telemation call center software was designed with this concept from the very beginning.
That is why so many call center managers, with unique and changing requirements, have chosen and continue to use Telemation CRM software as their solution.
Our Telemation CRM solution is ideally suited for call center service bureaus.
Behavior-Based Marketing: Adding Intelligence to Consumer Marketing and CRM
By Mark Smith, Quadstone
CRM2day.com
Computerization: Both Problem and Solution
In the times before computerization took over the operations of banks, utilities and retailers, these organizations used human beings to interact with their customers. The local shop manager knew his regular customers personally, as did the clerk at the local bank branch, and they thus could make educated judgments on what products to offer based on when they saw the customer and what they observed in the customer's behavior.
The introduction of computers has enabled organizations to become bigger and provide more services to their customers. This has helped reduce errors and cut costs dramatically. But what has it done to increase real knowledge of the customer's desires and choices? As an example, let us look at the evolution of consumer banking beginning back in 1950s.
- In the 1950s, a clerk would write transactions in a ledger by hand and could use this book to look for patterns in account usage. Everything was done manually and the relationship between banker and customer was based upon personal contact with the individual.
- The computerization of the accounting process removed this visual guide to customer behavior through the 1960s and 1970s. But the customer still came into the branch to talk to their clerk and manager for loans, deposits, and withdrawals.
- The introduction and expansion of ATMs in the 1980s began the trend of the customer not actually entering the branch and meeting their "personal banker." People began to make deposits and withdrawals outside of the bank.
- The rise of EPOS (Electronic Point of Sale) and credit/debit payment systems further extended the gap between the customer and the part of the bank that could "see" their day-to-day behavior.
- In the late 1980s and early 1990s, telephone banking was introduced to customers allowing them increased personal convenience. Customers now only needed to go to the bank to open accounts, close accounts and apply for loans.
- In the late 1990s, Internet banking and the expansion of e-commerce systems became popular. Customers could now open or close accounts, make deposits or withdrawals, and apply or qualify for loans without ever visiting an individual.
After 20-30 years of technology being used to drive down costs and improve an organization's efficiency, we are only now seeing the introduction of technology tools that can redress the balance in terms of understanding customers and their behavior. Such systems focus on improving the effectiveness of an organization's sales, marketing and service operations.
The key factor that delayed the introduction of such tools was that they needed to operate with a speed and scale that could not be supported with traditional computer power. Significant work was also required to create the "application" around the key technologies and to deliver them to the desks of the business users who had to be the control points for such work.
Marketing as a Learning Process
The positive side to technology advances is that they now enable marketers to use best practices in marketing in a way that was never before possible. Even the most sophisticated campaign management systems for direct mail have by their very nature a lag of several weeks before marketers can assess the impact of their creative ideas. E-commerce and out-bound call center systems reduce this lag many times over, allowing offers to be changed almost by the hour, and the impact of such changes to be assessed and acted upon immediately.
The cyclic process that should be followed by an organization as it performs such behavior-based marketing can be shown in Figure 1.0.
Each time a marketing department completes this cycle they have an opportunity to:
- Observe customer behavior in response to a new product or new offer.
- Increase their understanding of the customer and their behavior.
- Learn how to improve things for the next marketing activity.
This understanding of customer responses to business actions enables continual learning about customers and their behavior. It is a perfect mechanism to support the marketing process of creating ideas, testing the market, measuring results in detail and then doing it better next time. Marketing thereby becomes a learning process about customers and their behavior - not just about campaigns and creative success.
Valuing and Using Your Data
Data exists about your organization's customers in many and varied forms. Figure 2.0 shows graphically how to differentiate between this data in terms of its value to the company, as it better enables behavior-based marketing.
The three key rules are to acquire, store, and use data that is both specific to individual customers, and also is dynamic in terms of tracking their latest status and behavior.
In order for the business analyst to achieve valuable results from all of this available data they need more than just the pure statistical processes of data mining. They need to be able to explore all the available data, on all their customers, to assess what values, segments, and pre-processing are important to enable their business objective to be framed in a way that analytical results will be actionable and relevant. They also need to be able to interactively refine their results to ensure they best fit their marketing objectives.
This hands-on control by the marketer is vital since almost no real-world business tasks can be framed in a purely statistical way. The knowledge and insight of the analyst is required to drive the refinement of the data mining process to ensure an actionable result. The business analyst must therefore take control of business processes relating to their customer data, and drive their operations based on their interpretations and learning from this data.
Failure and Success in the Real World
Real-world examples are always a good way to demonstrate the reality behind the concepts and propositions put forward in a paper such as this. Below we present a case study of both failure as well as success. The reason for this is twofold:
We actually learn more from things going wrong than from a brief outline of success. Learning how not to make mistakes is very important.
Success stories are too easily framed in simple terms that might mask the true issues behind the cold numbers.
The Missing Millions (of Lost Opportunities)
In a large retail finance company, a marketing analyst discovered that almost 10% of all the bank's customers were either being totally ignored or mis-marketed to by the operational team. These mostly high-value customers were being missed because of a complex mix of selection rules and criteria imposed by the data analysis team through a strictly statistical interpretation of the marketing processes.
In their own right, each of these rules made perfect operational sense, but when brought together they were a real barrier to success for marketing. For example, combining a sensible operational rule that said "Don't market unsecured loans to new customers" with a reasonable systems rule that said "Reset time with bank" to zero when there is a name change on an account" caused great distress to marketing. They knew that some of the best targets for such high-profitability loan products were newly married couples (hence a name change) where one of the partners is a loyal, long-standing customer - over 250,000 such ideal targets had been missed because of the combination of the above rules.
If any of the statistical analysts had ever had the desire to stand back and look at the "big picture" of their customer base and their marketing activity, they too would have identified where their processes were going wrong. However, their job consisted of providing the most statistically correct answer based upon business rules designed by the bank. The implications or interpretation of these rules in real-world application was not their job or what they were trained to do. This example points out how important it is for the marketing professional in today's businesses to be sure that they are not removed from the customer modeling process.
Turning Database Marketing into a Money-Spinner
A leading multi-national retailer that operates over 500 stores and mails hundreds of thousands of customers each year was dissatisfied by how difficult it was to determine the effectiveness of their marketing campaigns. For the past six years the retailer had maintained a detailed customer database of their customers purchasing behavior.
For the first five years of its operation the loyalty-program marketing department targeted all offers on the basis of demographic classifications of their customers. This targeting performed reasonably well and produced the expected results of substantial cuts in mailing costs.
Last year the retailer took a massive step forward by using high-speed analysis tools and interactive graphics to identify both purchase behavior patterns and key predictive demographics in large databases of customer information. This has enabled them to target, acquire, and retain their most valuable customers according to business and marketing objectives. Since the implementation of this behavior-based marketing methodology, they have not only experienced direct mailing responses that more than doubled to well over 6%, but they have also achieved "mailing contribution" (i.e. profit) values more than 20 times better than their best results in all previous years.
The use of behavior-based marketing techniques returned the retailer all of the investment in the supporting technology within the first three months of use. Because this technology is a business-user system its value will be replicated over and over as the database marketing department increases rapidly in size - a direct result of their success in the last year because they started to deliver real profits to the organization.
Conclusion
It is now a necessary core competency for organizations to build an understanding of how customers behave and to continue to enhance this by learning how different service levels, communication methods and channels affect different customers. This approach builds a depth of market and customer knowledge that will provide a springboard to corporate survival and market dominance. The market for customer behavior analysis and modeling systems is new and rapidly expanding. It can therefore be very noisy and confusing. Below is a six-point checklist of the key issues to be considered when looking for a customer behavior solution.
Business solution focus:
Behavior-based marketing is a continual dynamic process of collecting and analyzing data on customers and their behavior, and learning how best to influence them to enhance business returns. What is also needed is a mechanism to learn how best to take actions based on these predictions; how to enhance raw data with the knowledge and intuition of business (marketing and risk) analysts; and how to interface cleanly and instantly to database, operational and planning systems.
Speed:
Understanding customer behavior in time to act before the opportunity is lost requires the speed, integration and interactivity that make it feasible for business analysts to work with all available data and perform data-driven "train-of-thought" analysis. The longer it takes for analysts to create a customer model, the less opportunity they will have to refine it to increase its business value.
Productivity:
An intuitive and easy-to-use interface that removes the requirement for programming and other IT skills will enable better, faster decisions and higher productivity from scarce and valuable business analysis resources.
Visualization:
Powerful, dynamic 3-dimensional graphics facilitate the understanding of all available customer data at every stage of the analysis and behavior-based marketing processes. This provides a mechanism for extracting valuable business insight from data, giving business analysts control, instant feedback and a better understanding from a business perspective of the subtleties of detail in their customer database.
Volume of data:
Businesses need to work with all data on all customers, and when this raw data is transactional the volumes are massive. Such access assists with customer models, values and scores being recorded for all customers interactively and immediately, rather than requiring a separate IT/IS process.
Analytical clarity:
Few business problems can be expressed perfectly as statistical fitting problems. It is important for business analysts to be able to spend time examining and developing models that truly fit their business problem, thereby enabling actionability of results and enhanced business understanding.
|
