Meaning of Customer-Related Database:

Companies typically do not have a single customer database; instead, they have a number of customer-related databases. Large organizations, such as financial services companies, can have 20 or more customer systems, each with a separate database.

These databases capture customer-relate data from a number of different perspectives. Customer-related data bases might be maintained in a number of functional areas – sales, marketing, service, logistics and accounts – each serving different operational purposes. Respectively, these databases might record quite different customer-related data – opportunities, campaigns, enquiries, deliveries and billing.

Customer-related data might also be maintained by different channel managers – company- owned retail stores, third-party retail outlets and online retail, for example. Similarly, different product managers might maintain their own customer-related data.

Customer-related data can have a current, past or future perspective, focusing upon current opportunities, historic sales or potential opportunities. Customer-related data might be about individual customers, customer cohorts, customer segments, market segments or entire markets. They might also contain product information ,competitor information, regulatory data or anything else pertinent to the development and maintenance of customer relationships.

Basic Principles for Maintaining the Customer Database:

Maintaining the database means that users will be more likely to have their need for accurate and relevant data met. Accuracy and relevance are two of six desirable data attributes that have been identified data should be shareable, transportable, accurate, relevant, timely and secure. You can remember these desirable data attributes through the mnemonic STARTS. S- Shareable

i. Data need to be shareable because several users may require access to the same data at the same time. For example, profile information about customers who have bought annual travel insurance might need to be made available to customer service agents in several geographic locations simultaneously as they deal with customer enquiries in response to an advertising campaign.

ii. Data need to be transportable from storage location to user. Data need to be made available wherever and whenever users require. The user might be a hot-desking customer service representative, a delivery driver en route to a pick-up, an independent mortgage consultant or a sales person in front of a prospect.

Today’s international corporations with globally distributed customers, product portfolios across several categories and multiple routes to market face particularly challenging data transportation problems. Electronic customer databases are essential for today’s businesses, together with enabling technologies, such as data synchronization, wireless communications and web browsers to make the data fully transportable.

iii. Data accuracy is a troublesome issue. In an ideal world it would be wonderful to have 100 per cent accurate data. But data accuracy carries a high costs. Data are captured, entered, integrated and analysed at various moments. Any or all of these processes may be the source of inaccuracy Keystroke mistakes can cause errors at the point of data entry. Inap­propriate analytical processes can lead to ill-founded conclusions.

In CRM, data inaccuracy can lead to undue waste in marketing campaigns, inappropriate prospecting by salespeople and general suboptimal customer experience. It also erodes trust in the CRM system, thus reducing usage. This leads to further degrading of data quality.

To counter this, usage vol­umes and data quality should be monitored. Data need to be entered at source rather than secondhand; user buy-in needs to be managed; data quality processes such as de-duplication need to be introduced. News agency and book retailer WHSmith attribute high re­sponse rates of CRM-enabled direct marketing to the accuracy of their database.

For ex­ample, an offer of Delia Smith’s How to Cook book achieved an 8 per cent response rate, significantly more than was the norm before their data quality project was implemented.

iv. Relevant data is pertinent for a given purpose. To check a customer’s credit worthiness you need their transaction and payment histories, and their current employment and income status. To flag customers who are hot prospects for a cross-sell campaign, you need their propensity-to buy scores. In designing a data management system to support a CRM strategy, relevance is a major issue. You need to know what decisions will be made and what infor­mation is needed to enable them to be made well.

v. Timely data is data that is available as and when needed. Data that is retrieved after a decision is made is not helpful. Equally, decision-makers do not want to be burdened with data before the need is felt. Bank tellers need to have propensity-to-buy information avail­able to them at the time a customer is being served.

vi. Data security is a hugely important issue for most companies. Data, particularly data about customers, is a major resource and a source of competitive advantage. It provides the foun­dation for delivery of better solutions to customers. Companies do need to protect their data against loss, sabotage and theft. Many companies regularly back-up their data. Security is enhanced through physical and electronic barriers such as fire walls.

Managing data secu­rity in a partner environment is particularly challenging, as it is essential that competing partners do not see each other’s sales leads and opportunity information, despite being signed into the same CRM system through the same portal.

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