Five reasons why data is difficult

For any organisation collecting customer data, there are several common challenges which mean that data is always a difficult thing to do well. Here’s why:

1. More than one system. Companies often need to use multiple systems to get ‘best of breed’ functionality from each (think finance, campaigns, e-commerce …) While clearly necessary, this creates several separate pools of data, making it hard to see the complete picture. This means that integration is always a tricky issue whenever there is more than one system being used to handle customer information.

2. Capturing clean data. Customers filling in online sign-up forms are often in a hurry and are prone to making mistakes: they’ll often care a lot less than you do about whether the form is complete and correct. Validation is a great idea where possible (eg. email addresses, postcodes) and using pick lists is also helpful (eg. lists of states, countries). However, there will always remain some free text fields for name, address and so on, which will never be 100% accurate and consistent – giving you another data difficulty to handle.

3. Keeping data clean. Even accurate details will become out-of-date over time as customers change their email address, move home, get married, or even die. There are several paid-for verification and suppression services which are designed to address this issue, and it also helps to ensure that customers can edit and update their own account details at any time. But put simply: the more time which passes since the original sign-up, the greater your doubt over the correctness of a customer’s details.

4. Removing duplicate records. Duplicate records are another standard data problem which is hard to avoid: the same customers are likely to interact with your organisation in different places (eg. sign up for newsletters and register separately) and some will also sign up more than once. There is then a challenge in finding the duplicates, and also in deciding which details are the right ones to use – for example, where duplicate sign-ups have conflicting contact permissions.

5. Differing staff requirements. Different groups of staff are likely to want different things from customer data. Management may require top-level trends presented in a dashboard format. Sales and marketing may wish to create segments and export contact lists. Customer services may need to quickly look up a single customer and view an integrated record of all of their activity. With such a diverse range of requirements, serving all of these audiences adds up to another good reason why “data is difficult”.

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