Historically, “companies” (a term defined below) and their customers often have done business across a gap, so to speak. Product or service offerings by a company the customers' desired product or service do not fully match. In part, this gap is a manifestation of the facts that (1) companies have an incomplete grasp of customer needs, their relative preferences and the pricing utilities customers attach to those preferences (which utilities, equating to the customer's willingness to pay, are dynamic) and (2) a company's costs, profits and inventory (which may control what it can offer on a timely basis) are also dynamic. However, it is also in major part a manifestation of the lack of information technology tools which can close the gap. To collect dynamic customer and company data and then employ those dynamic datum to close the gap is a complex technical problem.
Companies have developed many approaches to increase their internal efficiencies and productivities in order to maximize their gains and profits. With the advent of the computer, companies have, for example, embraced tools to optimize supply chain resources. They have, for example, focused on internal operations and the use of automated processes to integrate the discrete steps from the supplier to the finished goods inventory floor (or service delivery), improving efficiency. Yet still the end customer typically has been treated as an indistinct, static and detached entity—a statistical profile, in the aggregate—sitting behind a wall and creating demand for the rest of the supply chain. Manufacturers (whether of goods or services) have tried to influence the customer demand via indirect means of advertising and promotions. Beyond the influence that these indirect means can have on a customer's purchasing decision, the manufacturer and retailers have for the most part (at least in mass market situations) considered customer demand fluctuations as a given parameter that can't be altered or managed directly. Moreover, in industries where a company typically has an extremely large customer base (e.g., the airline industry, as discussed below), there has been no mechanism which a company could used to tailor its offerings to individual customers, except by providing multiple selections that are fairly static.
Generally, the customer is treated as an individual and sales terms are customized only when the cost of negotiation is justified—for very large transactions. Indeed, the basis for mass marketing a product or service arguably is the “cookie cutter” approach of “one size fits all” transactions. As is said of the genius of Henry Ford in marketing the Model T automobile: the customer could have any color . . . so long as it was black.
With the advent of the global Internet, some providers of goods and services have sought ways to improve their sales and profitability by, for example, directing incentives and rewards to loyal customers enrolled in affinity marketing plans. They have surveyed the customers in efforts to improve product offerings, and they have accordingly modified their offerings. But still, with a take it or leave it approach. “Here are my sale terms and product offerings; buy or don't buy, the choice is yours.” Automation has permitted much better targeting of customer groups, but the group still has to be large. For example, a higher end automobile dealer might use a mail campaign tailored to a specific Zip Code instead of a print ad in a regional or national media.
Many products and services, though, represent complex, multi-faceted offerings and customers weigh their preferences for product features differently at different times. A customer might care more about cost one day and more about availability or delivery time or warranty if queried a few days or weeks later, to use some basic trade-offs as examples. Generally, a company's product consists of many value elements, (explained later) all of which are bundled together to be sold as a single product. But, not every customer values all the aspects of a product equally or needs all. Every customer places a different value (which may be a function of time and situation) on each aspect of a product. With features bundled together in a product, companies end up either incurring costs to sell something to a customer that he does want or lose a customer because the extra undesired value elements forced the product price too high for the customer.
The underlying problem is one of a customer whose demands can change quickly and a company whose productive capacity or service does not have the same dynamic time frame and is supported by a relatively fixed (in the short term) capacity and supply chain. Envision an oil tanker trying to keep up with a small power boat through a series of quick turns. It just can't be done. The company's capability is measured through a long cycle that in most cases starts off with a long range plan for space and equipment and a shorter term plan for securing material and hiring production staff. Production plans once set are fixed, and the result is happiness if demand exactly equals supply, excess inventory if too low and unhappy customer if demand is too high or the mix is wrong. Add in other factors such as warehousing, distribution and transportation and the opportunity for failure to meet customer demand is high.
Yet there is no systematic method or system available that allows mass-market sales to be customized around such preferences, let alone while concurrently maximizing the benefit to the company. Envision a situation where the company has a peek at the customers intentions. This knowledge allows the company to be more exacting in its ordering, staffing and delivery. Inefficiencies are reduced, revenue and profitability are increased and the company is then able to reduce cost to the customer while simultaneously improving profits.
A technology platform (i.e., system) and methodology thus are needed for customizing, in an optimal way, match between the availability and pricing of components or qualities of various aspects of a businesses' offerings of its products or services with the individual customer's changeable demand profile. If such a match could be made, both business and customer would benefit. The customer would be more satisfied and the business (long term or short term) will be more profitable. A win-win scenario is created rather than a zero sum game.