The vision of multichannel CRM is of a business where every channel touchpoint is enabled with common customer information and is able to receive and process response data from customers. Supposedly, this results in increased customer acquisition, satisfaction, wallet share and retention the multichannel value proposition. While there is empirical evidence that this is true, there has been little theoretical backing to validate it so that multichannel CRM success can be understood and repeatable. This article will examine a new theoretical basis for the multichannel value proposition and look at examples from business and the natural sciences that provide both strategic guidance and a metaphor diffuse feedback to understand why multichannel CRM really works.
Complex marketing can be described as the nearly intractable dilemma faced by corporate marketers who must formulate and integrate a coherent customer relationship management strategy across multiple products, multiple business units, multiple delivery channels, large numbers of customers and frequently overlapping or conflicting goals for customers, all in a dynamic and shifting competitive milieu such as the global economy affords. It is a dilemma faced by most of the Fortune 1000 companies.
Complex marketing poses two primary questions to the marketer:
- How do I integrate a customer strategy across multiple channels, products, business lines, etc., to provide consistent customer-facing offers and experiences?
- How do I "map" optimal distribution of channel facilities to my customer base and provide my customers the most appropriate channels and contacts for their needs?
Closed-Loop CRM Systems
Traditionally, marketing has been a linear process. You select a list of customers and prospects, craft an offer and deliver the message through appropriate media. If sales go up, the campaign was successful. In fact, this is the model that is still widely used today. However, the gradual deployment of campaign management tools coupled with online contact systems such as call centers, sales and service automation, and Web site personalization is changing the game. A new adaptive marketing model made possible by response capture (closed-loop CRM) is replacing the linear marketing model.1 This has occurred because of the availability of nearly instantaneous feedback from customers made possible by e- business technology (see Figure 1).
Figure 1: Adaptive Marketing Model Made Possible by Closed-Loop CRM
If the business is enabled with multiple channels of interactive customer contact, it can increase the number of times it is able to sense and compare customer behaviors across channels. This increases the ability of the business to adaptively learn what customers are doing. Thus, the business can craft strategies to retain and expand valuable customer relationships.
The reality is that customers respond to offers the way they want to or, in many instances, not at all. Also, customers respond by the channel they choose, not necessarily the one chosen for them. Thus, a bank might send its online customers an e-mail offer for an insurance product with a URL to click if they are interested. The customer could, however, choose to stop at the nearest branch office to discuss the offer with a service representative or might call the bank's 800-number. Depending on the level of marketing technology and process coordination, the bank's staff at these touchpoints may not be aware of the offer, of the fact that the customer was targeted or even the reason that the bank chose to direct the offer to this particular customer. Additionally, other business units in the bank might be vying for the customer's attention with offers that are not necessarily related to the insurance offer.
Diffuse Feedback Systems
The bank example illustrates a complex process of customer and business interaction, not just a transaction. The process extends over the general activities of learning about the product, shopping and comparing features, actually making the purchase and then seeking service after the sale. Each of these activities could occur at a different channel touchpoint or overlap several channels and leave a different electronic customer "footprint" along the way. In fact, it is a good exercise for a business to construct a customer experience map to view how consistently the business provides a seamless process for customers to learn, shop, buy and seek service across the business' delivery channels.
E-business channel integration is the technology and the processes associated with providing the same information to all the touchpoints of the business in order to enable a consistent and seamless experience for the customer and to capture their responses. Still, in many cases, all the data captured by these touchpoints will likely not be assimilated and analyzed to determine exactly how the customer responded to an offer and what that means for the future of the relationship. The service representative in the bank branch might not be aware of the offer or might fail to check the customer's profile to see that he was sent the e-mail offer but came into the branch instead of responding via the Web site. Other business units might also have solicited the customer for different products or services. It's a complex world out there!
For the marketer, this situation results in multiple streams of data that can give conflicting information about the customer's response to the intended offer. We'll give a name to this phenomenon: diffuse feedback. This is when the customer dialog is spread over different channels and may involve conflicting and/or overlapping goals for the customer as well as ambiguity in customer communication a common occurrence in a complex marketing situation.
A Lesson from Nature
Diffuse feedback is not unique to marketing. It occurs in other areas too (e.g., supply chains and manufacturing systems) and in the natural world (e.g., metabolic network of an organism where interacting sets of chemicals supply raw materials and energy for physical activity). In nature, diffuse system goals take the form of an organism attempting to optimize many variables such as safety, food supply, community, comfort, etc. Frequently, these goals overlap and may even conflict with each other. For example, to access a food supply, an organism must forage and expose itself to predators that compromise its safety. The organism might follow the scent of food while simultaneously monitoring for the presence of predators. It is constantly sensing its environment and making tradeoffs based on its experience and instinct. The organism's ability to monitor its world is also conditioned by factors outside of its control such as a predator's camouflage, terrain, wind, temperature, competing species, etc. The sensing of favorable conditions for its current goal (acquiring food) tells the organism to continue with its current activity; the sensation of less favorable "data" (e.g., a predator) results in changing behavior (taking cover). In most cases, the incoming data that the organism is sensing from its environment is diffuse (i.e., it is not acting on a single metric but is incorporating multiple sensory inputs). When both positive (food scent) and negative influences (predator signs) are present, the organism applies some weighting to the incoming data to formulate its re-sponse with respect to attaining its goals.
Similarly, a business can have overlapping goals for its customers (e.g., wallet share, retention and product depth) and utilize multiple channels to sense and process customer data in order to achieve its goals for the customer. In the bank example, bank management wants customers to buy insurance, but they also want them to increase their deposits and buy other products. Some businesses ask their call center agents to attend to customer service and also present sales offers to customers activities that compete for agent time and customer attention.2 The business gathers customer interaction data through many channels, takes note of offers that don't get a response and tunes its strategies and delivery channels to optimize the competing and overlapping goals. This is how complex marketing manifests itself in a diffuse feedback system.
The Scientific Basis
In nature, time and natural selection somehow manage to define the relative weights of behavioral rules in organisms as they respond to environmental data to promote their long-term survival as a species. A developing body of scientific theory and evidence points to the effectiveness of diffuse feedback networks across many different kinds of organisms. These investigations include both natural and artificial organisms (i.e., simulations) and use techniques borrowed from many disciplines such as immunology, biology, computer science and control theory. The bottom line of this research is that diffuse feedback (e.g., multichannel interaction) improves the ability of organisms to adapt to changing environmental conditions.
This is evident in many different situations, such as the human immune system where the body must decide how to respond to a pathogen based on multiple sensory inputs.3 The immune system releases chemicals (such as antigens and noxious substances) that kill the pathogen, but also have the potential to harm the body (through the inflammation caused by the released agents). The various killing chemicals as well as scores of other special agents encode information that is used to provide the immune system with effective diffuse feedback. The immune system acts on the basis of weighted behavioral rules, not yet fully understood, that are somehow encoded into its functioning.
Because marketers are aware that customer attention spans and patience are limited, they typically apply rules such as: Deliver a maximum of six relevant offers to a customer per year according to the customer's preference. This contact strategy is structurally similar to the functioning of the immune system as it attempts to release just the correct level of antigens (offers) to maintain health in the presence of pathogens. In the marketing example, "health" is the goal related to the customer and/or the business, such as satisfaction metrics and product penetration, and the "pathogen" is the influence on the customer that leads the customer away from these goals, e.g., competitive offers, inertia, attrition and offer fatigue.
For the marketer, relevant offers might be determined from customer profiling and propensity modeling of historical and appended data. Marketing analytics digest the "sensory" data coming from customer interaction channels including negative or zero-response data. When the responses from the different channels are factored in, the marketer has the benefit of diffuse feedback to inform strategy and to adapt. In this sense, the business rules compressed from data in an analytic repository are the "corporate DNA" that drives personalized multichannel customer interactions. Thus, the business acts like a natural organism in a diffuse feedback environment, seeking revenues from its customers, ever aware that other factors are also influencing customers.
Complex system studies support the thesis that a multichannel e-business can incorporate diffuse feedback to achieve its goals.4 For an e- business, the diffuse system tactics that nature might recommend include:
- Specify a broadly defined purpose such as attaining some level of customer profitability or satisfaction.
- Identify a list of general performance goals; these can be contradictory or overlapping, if needed.
- Install sensors (channel touchpoints) that give information about progress toward the various goals and also information on the overall state of the business and its environment.
- Define tactics (e.g., a customer contact plan) that move the business in the general direction of the overall goal, but leave room for overlapping and contradictory actions.
- Capture feedback from the channel touchpoints that can signal the desirability of putting more effort into some tactics (following the food scent) and pulling back on others (taking cover).
- Modify operations to incorporate these signals into the business' customer strategy, e.g., redeploy channel resources according to an economic framework that optimizes the efficient frontier of channel functions and combinations for each customer segment.
Taken together, these measures address the two main questions of the complex marketing dilemma and provide strategic guidance for managers who are faced with business situations characterized by diffuse feedback phenomena.
This article has attempted to show that diffuse feedback from a multichannel business environment has wider implications for the marketer than might be expected if it is considered as part of a larger, complex picture of the customer's interaction with the business environment. There appears to be a basis of scientific validity for the multichannel value proposition, a validity that is based on models identified in nature called diffuse feedback systems. Applying the lessons derived from diffuse feedback systems in nature enables managers to address the complex marketing issues that these types of systems create for an e-business.
1 Kurtyka, Jerry. "CRM in the Adaptive Enterprise." DM Direct, February 25, 2000.
2 Askin, O. Zeynep and Harker, Patrick T. "To Sell or Not to Sell: Determining the Tradeoffs between Service and Sales in Retail Phone Banking Centers." Wharton Financial Institutions Center 1999 working paper #96-07-B.
3 Segel, Lee A. "Diffuse Feedback from Diffuse Information in Complex Systems." Complexity, July/August 2000.
4 Segel, ibid.
Register or login for access to this item and much more
All Information Management content is archived after seven days.
Community members receive:
- All recent and archived articles
- Conference offers and updates
- A full menu of enewsletter options
- Web seminars, white papers, ebooks
Already have an account? Log In
Don't have an account? Register for Free Unlimited Access