A Blue Sheep White Paper Describing The Essential Journey from CRM to SCV to CIM

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1 Customer Information Management A Blue Sheep White Paper Describing The Essential Journey from CRM to SCV to CIM Putting Customer Information Management at the heart of your company s marketing activities can lead to significant uplift in the effectiveness of your customer retention and acquisition activity, delivering an 11% growth in sales, and a 30% increase in profits for the business as a whole.

2 Introduction Building customer loyalty and share of wallet are strategic imperatives for all businesses. Studies have shown that a 5% increase in customer retention increases profitability by an average of 50%. Additionally, acquiring a new customer is five to 10 times more costly than retaining an existing one. Attrition of a company s most profitable customers is particularly damaging taking into account the Pareto principle: 80% of the revenues or profits of a business are derived from just 20% of the customer base. Nowhere is this more evident than in the business to business sector. But companies are finding it increasingly difficult to build enduring relationships with customers in an evolving, competitive landscape fuelled by the Internet and deregulation. The average customer now has relationships with a larger number of institutions than ever before. They are also more transient than in the past. The companies that will grow and prosper in this difficult environment are those that build a base of loyal customers, and differentiate themselves through the quality of their customer service and the effectiveness of their sales and marketing efforts. Many companies have recently implemented Customer Relationship Management (CRM) programmes to address those areas, but most have not realised the returns they expected on their CRM investments. We believe this is because far too many companies have viewed CRM as a technology solution, not as a fundamental change in how they manage and use customer data. As a result, they have not focused on developing the capabilities required to leverage CRM technology effectively to drive customer loyalty, profitability and acquisition. This is why Blue Sheep has developed Customer Information Management (CIM). Our experience leads us to believe that companies will not meet their return on investment (ROI) objectives from CRM unless they use CIM as the basis for enabling the most fundamental of all CRM principles "treating different customers differently". Whether your organisation has invested in CRM technology or created a Single Customer View (SCV), we believe CIM is the next crucial step in managing customer data to drive profit through marketing insight. Iain Lovatt, Executive Chairman, Blue Sheep May 2009 Page 2 of 25

3 CRM Could it Really Manage? CRM, the major data development of the 1990s, has now become outmoded as it fails to treat customers as valuable individuals CRM vendors spent much of the past decade convincing companies that implementing new CRM technologies would strengthen their relationships with customers and increase profitability. While vendors dominated the CRM scene during the late 1990s, most consulting firms were still focused on squeezing the last drop of revenue out of Enterprise Resource Planning (ERP), Y2K and e business budgets. Only at the start of this decade did a significant number of consulting firms turn their attention to helping companies develop CRM strategies to leverage those technologies effectively. As an unfortunate result, most companies continue to view CRM from a technology perspective; witness the fact that Chief Technology Officers are often given the responsibility for managing CRM May 2009 Page 3 of 25

4 programs. CRM technology vendors are now suffering the consequences as more and more reports come out about companies who failed to realise expected returns from their investments in CRM technologies. It is not difficult to see why most companies have not realised the ROI they expected from existing data storage and use options. New contact centre desktop, sales force automation or marketing campaign management applications do not inherently drive market share or share of wallet. Years of experience in data strategy and business intelligence consulting have taught Blue Sheep that CRM succeeds only when those technologies are used to meet the specific needs of a company's most profitable customer segments and to attract new customers who fit those profiles. Until now, most businesses have invested in determining which customers fall into the 20% of the 80/20 rule, but many continue to lack a differentiated strategy for servicing, selling and marketing to those highly profitable customers. Likewise, while it is important to know which customers are least profitable, it is even more important to know how to make them more profitable, and to know which ones will never be profitable and should be managed out of the business. Much of the challenge in developing optimal CRM strategies for each business customer is the difficulty of co ordinating customer facing activities across several interaction channels. Companies that have implemented CRM technologies may have been unable to generate the ROI they expected from CRM because they are: Not able to recognise high value customers during interactions Not differentiating service levels based on the importance of each customer to the business Providing customers with the wrong level of service through the right channels, or the right level of service through the wrong channels Not optimising cross and up sell opportunities because they lack information about how to make the right offers, to the right customers through the right channels, at the right times Not effectively leveraging their diverse product and service suites to customise "bundles" that meet the specific needs of high value customers at their various life stages Wasting marketing budgets on campaigns that do not target the customers most likely to respond and buy Missing opportunities to increase share of wallet or reduce customer attrition because they are not tracking predictive purchase and "churn" indicators, and communicating recommended responses to those who interface with customers May 2009 Page 4 of 25

5 Under investing in their most profitable customers or over investing in their less profitable customers Uniform or indiscriminate treatment of all customers is a risky proposition. Companies that fail to take into account the importance of a particular customer (or group of customers) are probably under investing in CRM projects that benefit the most profitable customers, and over investing in CRM projects that benefit less profitable customers. In addition, companies that do not differentiate between the specific needs, preferences and expectations of individual customers will miss revenue opportunities and lose valued customers to competitors. May 2009 Page 5 of 25

6 From CRM to SCV CRM was eventually supplemented by Single Customer View. But with the ongoing need to drive greater ROI from the marketing database, is either program still enough? Blue Sheep believes that companies will not meet their return on investment (ROI) objectives with CRM unless they also use CIM to establish the principle of "treating different customers differently". Companies struggle with integrating and leveraging customer data from across numerous productoriented divisions, functional silos and business partners. They cannot achieve a Single Customer View (SCV) of the relationship between the business and its customers. May 2009 Page 6 of 25

7 SCV is used by organisations to leverage their existing customer information. It produces a clear and accurate understanding of customers in a defined and logical format to gain the insight into what value can ultimately be attributed to that customer for effective communications to take place. Many client databases are held in differing formats with customer records created under various names. This is often made worse by storing old and inaccurate details. Working with conflicting data creates an inconsistent view of customers which leads to poor management and communication. SCV was developed to ensure customers are represented in the same format, and obsolete or inaccurate information is removed and updated. It certainly added value where CRM couldn t. But in order to truly make the most of your customer data, there is a new, third way for organisations to follow: CIM. May 2009 Page 7 of 25

8 CIM Heart of the Matter CIM is not only the basis for leveraging data storage programs: it is also the basis for measuring their success So what do we mean by CIM? A company s ability to identify customer needs, segment customers and build accurate customer profiles all depends on how effectively the company collects, manages and uses customer data. CIM is the application of customer data to current data storage strategies: in other words, whether your business currently uses CRM or SCV, CIM is the next step. CIM bridges the gap between data storage and customer valuation by showing companies how to use customer data to make decisions that will enhance customer profitability and loyalty. May 2009 Page 8 of 25

9 The CIM process determines the current or static profitability of customers, but also their lifetime and potential ("strategic") value. It involves learning exactly why some customers are (or will be) more profitable than others; understanding the needs and behaviours of various groups of customers and determining how to influence those behaviours. Finally, it means knowing how to leverage all of this information to balance the value derived from each customer segment with the value provided to each of those segments. A central tenet of CIM is that a company s profitability depends largely on how well it allocates capital and resources across its most profitable and least profitable customers. In terms of the customer data pyramid, companies must move beyond collecting basic demographic and product/activity information in order to implement CIM effectively. Companies should make concerted efforts to collect additional behavioural, predictive and preference oriented information about their customers in order to build robust customer profiles. Companies that view each interaction with a customer as an opportunity to collect additional pieces of required data will slowly begin to fill in the missing pieces of the data puzzle. Many companies committed to a CIM approach look to form partnerships with third party data providers to gather data elements not easily collected internally. May 2009 Page 9 of 25

10 CIM Segmentation = cimplicity Customer segmentation is the vital first step towards identifying the value of customers by applying CIM Customer segmentation begins with identifying the organisation s primary market segments, defined as major distinctions between customer groups. At the highest level, a market segment could be private versus public sector customers or, at a lower level, large corporate, middle market or entrepreneurial companies within the private sector. Customer segments are subsets of market segments and consist of companies or individuals (or households) that may be grouped into logical clusters based on: May 2009 Page 10 of 25

11 Relative Value Revenue is often the best proxy for customer value. However, revenue alone does not take into consideration differences in customer support, sales and marketing costs and channel usage, which have a material impact on relative customer profitability. CIM principles hold that customer profitability is a more accurate and useful measure of customer value than revenue alone. Behavioural Data mining is used to uncover behavioural associations between customers within each market segment through complex statistical analysis of numerous variables. Customer segments are typically formed by establishing performance thresholds for the characteristics, data elements or KPIs which data mining reveals are most critical for managing the customer relationship, such as: Product holdings (type of membership) Demographics or other specific attributes (e.g. type of business, size and geography) Channel usage / preferences (e.g. online transactional customers v consultative client) Transaction activities and volumes (e.g. level of activity RFV) Value based segmentation provides the only basis for knowing whether an institution is overinvesting in building relationships with low value customers or under investing in its high value customers. Over investment means that, given the profitability of a customer, the business is investing too much capital and resource on attempting to enhance the relationship with that customer. For example, the business may be allowing unprofitable customers to continue to access high touch communication channels far too frequently. Likewise, the business may be targeting campaigns toward a customer segment that is ultimately unwilling to change purchasing decisions or behaviours that would increase profitability. Under investment means that the business is forgoing opportunities to build a stronger relationship with a customer that is (or has the potential to become) highly profitable. For example, the business may not be investing in the customer data analytics necessary to determine which products and enhanced services to offer to an attractive customer segment. As a result, those customers are at risk of taking their business to an institution which properly values and invests in their relationship. May 2009 Page 11 of 25

12 Only when a business segments its customers based on their relative contribution to profitability can it knowingly optimise relationships with its customers. May 2009 Page 12 of 25

13 CIM Counting Customers Determining relative customer profitability is crucial for driving profit from an existing database The starting point for customer segmentation is customer value. The only way to eventually estimate the expected return from strategic data storage initiatives (CRM or SCV) is to begin by determining relative customer profitability. Ultimately, the data storage investments that have the highest ROI are those with a significant profit impact on the retention, share of wallet and acquisition of highvalue customers. It should be noted that current customer profitability is not as useful for developing data strategies as Lifetime Value or Strategic Value, which measure the long term value of each customer. May 2009 Page 13 of 25

14 Lifetime Value is the present value of all expected future net cash flows from its customers. Lifetime Value models the expected relationship with each customer to provide an estimate of total lifetime customer profitability, as opposed to the snapshot provided by current profitability measures Few institutions have taken customer value analysis to the next logical step of measuring Strategic Value, which is the potential profitability of a customer if the business takes advantage of opportunities to grow the relationship over time. An example of a customer with high Strategic Value is a large corporate whose relationship with the business consists of purchase of only one or two relatively unprofitable products. Once a high Strategic Value customer has been identified, the business should seek to understand the customer's needs and pitch the appropriate set of (more profitable) products and services. The goal is to increase share of wallet and potentially own that relationship over time. The end game with respect to Strategic Value is the development of an advocate who refers other profitable customers to the business through word of mouth. The next step is to use the segmentation value to drive profit from your data strategy. May 2009 Page 14 of 25

15 CIM Driving Value CIM gives companies the ability to define true knowledge of customers and tailor all marketing activity accordingly The Customer Value Decision Matrix below demonstrates how customer value segmentation can form the basis for customer strategy decisions. Customer Centric KPI Definition Many companies accumulate vast quantities of customer data across various legacy systems and interaction channels. However, few are accomplished at turning this data into useful customer May 2009 Page 15 of 25

16 knowledge about how to provide differentiated service to various customers, or how to sell and market to each of those segments more effectively. CIM ensures that the activities, attributes, behaviours and preferences tracked for each segment are actionable, material and relevant to the development of data management strategies for that segment. Identification of the most critical customer profitability and loyalty drivers ensures that CIM focuses on the metrics that will be most useful in developing customised sales, marketing and customer service strategies. By highlighting the customer centric KPIs that have the most direct impact on customer profitability and loyalty, CIM also shows how companies can "pull" those levers appropriately to have the intended effect on the behaviours of different types of customers. In addition, these relationship value drivers are an important consideration in prioritising data initiatives. The highest priority initiatives will be those that have a direct and significant impact on the drivers of customer profitability and customer loyalty for the most valuable customer segments. For less profitable customers, these profitability and loyalty drivers will provide insights into how to improve customer satisfaction while still reducing the costs of customer service and sales for those customers. CIM requires organisations to establish a balance between a customer's profitability and the level of investments made in building that individual's satisfaction or loyalty (which CIM labels customer equity). Given the level of analysis and expertise required to determine the core drivers of value in a company s relationship with its customers, CIM instead utilises Value Driver Mapping to derive customer profitability and equity drivers. Customer Profitability Drivers Value based customer segmentation is instrumental in disclosing the major revenue and cost elements in a company s relationships with its customers. Customer profitability drivers are those underlying factors in the customer relationship (e.g. activities, channel usage) that most directly influence those revenue and cost elements. Customer Equity Drivers Customer equity is the value provided to customers, as opposed to customer profitability, which is the value derived from customers. In other words, it is the degree of satisfaction that the customer May 2009 Page 16 of 25

17 has with the company s products and services and is a measure of the strength of the customer's overall relationship with the institution. The more equity a business develops with a customer, the less likely the customer is to take their business somewhere else. In fact, one of the greatest attributes of customer equity is that it can often be spent (e.g. poor customer service experiences, charging slightly higher rates than competitors) without jeopardising the relationship. Mapping customer equity drivers traces the primary measures of customer satisfaction back to their respective root causes. Because each customer segment derives satisfaction from different sources, each value driver must be evaluated separately. For example, a company s most profitable customers typically value the quality of customer service, convenience and product innovation above price. A company s least profitable customers typically value price above all else and view financial products as commodities. Another important component of the KPI definition process is the use of Predictive Modelling to identify historical purchase and churn indicators. Leveraging data mining, companies can determine which events, activities or attributes have historically been associated with either purchase or churn behaviour for customers in each segment. As the adage goes, "Those who cannot remember the past are condemned to repeat it". In this case, companies that do not study past behaviours of their customers will miss opportunities to sell products or services to customers or will fail to recognise "at risk" customers. In almost all instances where an individual takes a part or all of their business to a different business, there are leading indicators that, if monitored, would have warned the business in advance of that decision. Developing the capability to monitor these leading indicators requires only: Knowing what predictive purchase and churn indicators to track Building business rules into the customer interaction infrastructure to signal an alert when one of those indicators is "tripped", and prompt the appropriate remedial action. A by product of Predictive Modelling is additional insight into how to build customer equity with each value segment by enabling companies to anticipate future customer needs and behaviours. The ability to respond to a complaint or meet a need before a customer ever voices it is a clear differentiator in this increasingly commoditised financial marketplace. May 2009 Page 17 of 25

18 CIM What s the Score? Marking customers on a scorecard is a central element of CIM and the best way of quantifying customer profiles The next step in CIM is the development of a behavioural profile of customers in each value segment. Segment profiling evaluates the relative performance of each segment against each of the customer profitability and equity drivers, while also considering other behavioural differentiators. Basing customer profiles on key value drivers creates the clearest path to using customer analytics to identify the data storage investments that will have the greatest impact on customer profitability and building customer equity. Customer Scorecards are the most common and useful way to capture and portray customer profiles. Scorecards provide management with a real time, 360 degree view of the status of the customer relationship. A well designed scorecard partitions customer centric KPIs into logical May 2009 Page 18 of 25

19 groupings and presents them in a user friendly format to various end users to assist them in differentiating service levels, targeting offers and identifying "at risk" customers. Each of the key customer profitability and equity drivers is reflected on the scorecard, as are other historical trends or statistical data that may help to illustrate relative performance and highlight key segment differentiators. Building an actionable and useful Customer Scorecard requires a robust customer data warehouse. All of the data elements needed to populate the Customer Scorecard are mapped in a data model that sits behind the Scorecard. In fact, the first step after the design of a Customer Scorecard is a data gap analysis to confirm data availability and determine the sources of both available and previously uncollected data elements. Of course, the cost of acquiring new data must not exceed the value of that data to the business, which depends on how important the KPI (which the data element will support) is in the effective management of customer relationships. Bringing together customer data from across all of the organisation s business units is a significant challenge for most companies. All companies are able to identify account level transaction and volume data, but few have become accomplished at building comprehensive customer data warehouses and customer profiles that encompass: Relationships between account holders (e.g. corporations) All of a customer's relationships and activities across divisional, product oriented and functional business units (i.e. a comprehensive "relationship view" of the customer) Demographic attributes, life stages, specific needs, and preferences (e.g. channel preferences) Companies must move beyond collecting basic demographic and product/activity information in order to implement CIM effectively. Organisations should make concerted efforts to collect additional behavioural, predictive and preference oriented information about their customers in order to build robust customer profiles. Companies that view each interaction with a customer as an opportunity to collect additional pieces of required data will slowly begin to fill in the missing pieces of the data puzzle. Many companies committed to a CIM approach look to form partnerships with third party data providers to gather data elements not easily collected internally. May 2009 Page 19 of 25

20 CRM+SCV+CIM = Formula for Growth With data given a value, profiled for behavioural trends and segmented, CIM will begin to drive profit over and above existing programs The three major steps in the CIM process (Value Based Customer Segmentation, Customer Centric KPI Definition and Customer Segment Profiling) form the analytical foundation for developing personalised, multi channel and cost effective customer service, sales and marketing strategies for each customer segment. First, the relative value of each customer segment tells the business how much it should be willing to invest in building equity with those customers. May 2009 Page 20 of 25

21 Second, the profitability and equity drivers for each value segment tell the business how to make the best use of its previous data storage investments to build prosperous and lasting relationships with customers in those segments. Third, customer segment profiles turn abstract customer data into applicable customer knowledge. All three components focus the organisation around critical customer centric KPIs and provide the basis for disseminating that information to customer service, sales and marketing personnel to help them make more informed decisions. The first step in translating CIM findings into actionable strategies is to plot the customer lifecycle and identify key interactions with customers across that lifecycle. The customer lifecycle spans the customer Selection, Acquisition, Conversion and Retention processes, as illustrated (at a high level) in a Customer Lifecycle Map. Examples of key interactions along this lifecycle are "Purchase Events" where customers typically consider acquiring new products or services from an institution and "Loyalty Events" where customer defection may be occurring or where opportunities exist to establish a more enduring relationship. The next step is the development of Customer Experience Designs for each customer segment during each of those Purchase or Loyalty Events. Focusing on critical Purchase or Loyalty Events points the organisation toward opportunities to achieve the greatest ROI from existing data and streamlines the strategy development process. Keeping in mind the goal of optimising customer relationships and armed with profitability and equity drivers for each customer segment from the CIM analysis, the business must answer the following types of questions to design appropriate customer experiences: What will the impact be on customer profitability and loyalty of meeting (or not meeting) the service quality expectations and channel preferences of each customer segment? For example, since price is the key equity driver for most lower value segments, a customer experience that migrates those customers toward lower cost self service channels, yet leaves prices or fees unchanged, should not materially impact retention? What will be the appropriate response at each interaction point across each channel when predictive purchase or churn indicators are tripped? For example, a desktop application sends an alert to a Customer Service Representative (CSR) in a branch that the gold level customer with whom the CSR is speaking is at risk because they hadn t purchased any products that May 2009 Page 21 of 25

22 week or sales were down by 10%. The application prompts the CSR to ask the customer whether they are satisfied with the quality of service they have received and what else the business can do to meet there financial needs. Warning customer service personnel about profitable customers at risk before they leave at least gives the business a chance to respond. The responses designed for each channel should be based on the customer's profitability, on the specific indicator that has been tripped, and on the likelihood of a churn or purchase decision (i.e. strength of the indicator)? What does the intersection of product and customer profitability indicate about where to focus sales and marketing efforts? Which types of customers are most likely to respond to an offering for a particular bundle of products or services? What will be the most effective channel or channels through which to sell those bundles to those customers? What have the results been from past marketing campaigns? Why were those campaigns successful or unsuccessful with certain customers? More specifically, what are the common characteristics of customers that purchased products and services as a result of past campaigns? How can collaborative filtering the study of past purchase decisions to infer likely purchases by current customers be applied to the sales and marketing process? The conclusions drawn from CIM analysis and Customer Experience Design must be made available and utilised at each critical interaction point with customers across each interaction channel. In essence, CIM must be woven into the fabric of the organisation. Awareness must exist during all interactions with customers, whether online, in the branch, or via the contact centre, according to the customer's value segment, service expectations, and likely financial product and service needs. However, it is not necessary to provide all CIM data about customers to all customer service, sales and marketing personnel. In fact, most CIM data sits behind the scenes and is analysed using a set of defined business rules built into the data storage infrastructures that determine and recommend the appropriate action at each interaction point. Some business rules will be founded on the value based segment of a customer, while others will be based on specific elements of the customer profile. In most cases, value based segments are too broad to determine the right offer to make to a particular customer at a particular time. Value based segments are intended primarily to provide guidance as to the customer's overall priority in the organisation to ensure appropriate levels of attention are paid to building equity with that customer. So CRM business rules should also evaluate specific elements of the customer or segment profile, such as key profitability drivers, equity drivers and predictive indicators. May 2009 Page 22 of 25

23 The Customer Scorecard is ultimately the device that the business will use to measure the impact of customer experience design on the profitability, share of wallet and retention of customers within each customer segment. For example, a strategy focused on enhancing relationships with customers in a particular customer segment should be reflected in trends in several KPIs on the Scorecard for that segment, such as: Number of New Customers Customer Attrition Customer Satisfaction Share of Wallet % (estimated) Revenue Per Customer Number of New Accounts Per Customer Penetration % of Most Profitable Products Response Rate to Targeted Marketing Campaigns The extent to which customer management has impacted each of these metrics will provide insights into what adjustments should be made to the overall strategy. The answer may lie in tweaking the customer experience design, or it may be a more fundamental adjustment in the definition of customer segments or KPIs. Either way, measuring the results of CRM only provides value if the business learns from that information and takes the appropriate remedial action. Companies that do a good job of determining the fundamental drivers of customer profitability and equity will find it easier to pinpoint ineffective aspects of the CRM strategy and make the appropriate changes. May 2009 Page 23 of 25

24 CIM A Scenario As an example of CIM in action, a Computer Telephony Integration (CTI) application recognises that an incoming call is from a customer placed in the Platinum value segment and is a frequent trader, so it routes the call to a contact centre agent who specialises in high net worth brokerage. Intelligent call routing increases customer profitability and builds customer equity by reducing the number of times the customer has to be transferred and increases the odds of First Call Resolution. CTI equipped with accurate CIM data and appropriate business rules will also reduce Average Handle Time (AHT) of most calls. However, it should be noted that in the case of highly profitable customers, companies are learning that reducing AHT is not an appropriate goal. In fact, most are finding that the opposite is true because each interaction with those customers represents an opportunity to obtain additional data to build the customer's profile and to uncover additional opportunities to sell. Well trained contact centre agents will know the amount of time they should be willing to invest on the phone based on each customer's current value segment and potential strategic value to the business. May 2009 Page 24 of 25

25 Summary The success of any business s data strategy hinges on effective CIM, and on the development of appropriate business rules that leverage CIM data to prompt appropriate customer service, sales and marketing responses. Data storage technologies such as contact management, sales force automation and marketing campaign management provide important features and functionality to customer facing personnel. Many companies have acquired CRM technologies and loaded them with customer data expecting this programme to pay for itself. But numerous failures have shown that simply employing software provides poor ROI unless the business turns that customer data into useful customer knowledge that effectively drives the strategy and results in treating different customers differently. Whether your business currently employs CRM technology, or has invested in SCV, CIM can augment your data strategy smarter and ultimately drive revenue for your organisation through smarter marketing. May 2009 Page 25 of 25

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