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.
For too many b-2-b companies the database is an aging record of customers spread across different lists.
Databases can be an extremely useful marketing tool, but the reality is that customer and prospect data is often spread across a number of mailing lists and records from sales to accounts and 'one off' lists such as for mailings of newsletters and Christmas cards. Apart from duplicate entries in these different lists, typically vital data is out of date and it is also surprising how quickly data ages. Contact names change, so do company names, customers relocate and even if they don't, address details can change. On some updates we typically found that for 25% of records parts of the information had changed in a year. Add to this e-mail contacts on e-mail only lists and social media followers and it is soon evident that developing and maintaining current information requires allocating budget resource.
The situation is compounded by use of proprietary customer management software that few people in the company can actually use or have adequate training in. Then records get messy because there is no consistency in data entry, typically address fields are used differently by different people, some use upper case, data is spelled incorrectly and quite rapidly the database becomes a muddle. This is often exacerbated by inputting customer data while processing a sales call, so both parties are anxious to complete this part of the call quickly and tend to skip bits and make input errors. Many companies recognise that their database is in poor shape but do not allocate resource to 'clean' lists and keep it up to date.
With a well planned and maintained database marketers can learn useful insights into customer behaviour and data mining but in many cases we come across, the 'sales' package somebody bought is totally disconnected from the software package that 'accounts' use so marketers cannot track enquiries through to sales and relate to other information such as web analytics or e-mail tracking. From a marketing perspective there are further issues. Marketing is also interested in prospects, possibly people with similar profiles to current customers along with competitors customers who make up the total population of the market sector - not just the people you know.
When reviewing the marketing budget alocate sufficient resource for database software whether custom built or off the shelf, for training to use it effectively and for cleaning data.
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. 
