Data collated to understand and predict customer demand has become an important issue in ensuring the right product is in the right place at the right time.
Wider choice, reflecting the shift from the supply of mass-produced goods to mass-customisation, a demand driven market and the need to manage product availability to match actual customer preference, calls for better user data. In the business-to-business world the expectation has shifted significantly towards a rapid supply of product, where once several weeks wait was acceptable. As knowing more about customers and prospects becomes increasingly important, so legislation and privacy concerns as to what information is held on databases becomes a bigger issue. But many businesses do not yet really fully utilise their existing customer knowledge to provide better targeted marketing. Few extend beyond a basic address list and often operate several unrelated address lists divided across field sales, marketing, service and accounts. When this information is pooled into a single database, then patterns begin to emerge, helping to classify your customers, by product preference or usage requirements, for example and to create a profile of their main interests and motivations for buying your products and services. These profiles can be matched to the total market population. Profiling the total population including those with similar needs to your customers, can extend your prospect database. Sending information can then be selective, so that messages they receive by e-mail or direct mail have far greater relevance.
Experience shows that recipients of highly relevant information return a far better response rate to direct marketing campaigns, leading to improved sales closure. Mining data, generating and understanding customer and prospect profiles, helps target messages with high relevance to the recipient - leading to higher response rates.