A white paper on how companies should analyse customer data to gain better Business intelligence and how they can use that knowledge.

In an increasingly competitive world, using your client database smartly, to gain a better understanding of your number one asset - your customers - can make or break the success of your company.

Most companies use databases to store information about their current customers, previous customers, business partners, and potential customers. The challenge lies in finding a way to harness the useful information contained within these high volume databases in order to produce intelligent Business solutions.

Business intelligence (BI) refers to the process for increasing the competitive advantage of a company by intelligent use of available data in decision-making. Business intelligence consists of sourcing the data, filtering out unimportant information, analysing the data, assessing the situation, developing solutions, analysing risks and then supporting the decisions made. This white paper describes the business intelligence process, some elementary methods of data mining, and how you can use Business intelligence in your company.

Database Enhancement

The first step towards gaining Business intelligence is to start with a 'clean' database. Incomplete and inaccurate data invariably translate into incorrect management decisions. Duplicate data is also a problem as it can wrongly weigh management decisions to one side. Whilst a good quality database does not automatically lead to intelligent management decision-making, it is a pre-requisite for all types of analysis that attempt to elicit intelligent management. We could draw an analogy with cooking, where starting with the right ingredients does not guarantee you will bake a good cake, but there is very little chance you will bake a good cake if you start with the wrong set of ingredients.

One of the primary reasons companies do not fully realise the potential competitive advantages they can gain from their own databases is the lack of proper integration of datasets across departments. Even though all the information might reside within the company, it may remain elusive due to a fragmentation of the data across incompatible databases. Regrouping all internal data into a single dataset or a series of interconnected datasets could be the single most useful step a company might take towards providing a solid foundation on which quality Business intelligence can be developped.

In some cases, data entry errors and/or missing data can also severely impair the quality of information that can be derived from corporate databases. Sorting these issues can range from very straightforward fixes (e.g. matching one list against another) to more time consuming processes (e.g. contacting all client companies to update contact details of individuals working there). Ideally, all inaccuracies should be weeded out of the databases. However limited time and monetary constraints dictate that you should bear in mind how this database will be used. The level of accuracy required will vary greatly depending on the expected use for that data.

Data cleansing and database integration can provide significant advantages for a company over the medium to long term. However, they are both extremely time-consuming activities and can create a significant strain on internal resources, making them difficult for a company to justify. Hiring a third-party to do this job is often the best solution, allowing valuable information to be gained, without disrupting day-to-day Business activities.

Data Mining

Analysing the information that your company stores in connection with all customer interactions can reveal a lot of remarkable facts about the buying behaviour of your customers, what motivates them and what might make them stop buying from you. It also provides a scientific method to monitor your Business performance.

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