Remembering back to my last post, the amount of data kept on a customer is increasing within organizations and tying this data to customer survey data could help us gain better insights into the customer experience.
Potentially fulfilling every researcher’s dream, using this data could open the door to massive amounts of data to analyze while answering business questions. However, with that we can’t lose sight of the quality of the data. In other words, more bad data isn’t necessarily better. So keeping that in mind, before we use this data to help aid us in understanding our customers, we need to evaluate the data itself.
The first thing to do here is look to see what data you have available. This will help you gain a better understanding of where/how this data could enhance your understanding of the customer experience. For example, if only product information is kept for customers, then it would be logical to look at this data alongside a customer’s product ratings. This could help explain trends you are seeing in the data, as well as gain a profile of the type of customers that use particular products. A few examples of things to consider are…
· Type of data?
o Is it sales history? Customer demographics? Account Information (ex. size, tenure, etc)?
o Do we have information for individual contacts within an account or simply account level information?
– How easily can this be linked to customer survey data? Are there common fields, such as customer ID, which can be used to link the data?
o Is data tied to an individual/account or is it tied to departments within your company (ex. call center, agent)?
o If there are metrics in the data (ex. Issue Resolution Days), how is it calculated by your company?
· Location of data?
o Is all this data stored in a central database? Spread out among different parts of the organization?
o Is this data available for you to access? Format you can use?
The second thing to assess is the quality of the data to ensure that it is giving us accurate information about our customers. We don’t want to use customer data that has never been updated or doesn’t reflect the current customer’s situation. Instead we want this data to accurately reflect our customer as they are today so this information can be paired with their current perceptions of your company. A few examples of things to consider are…
· Who owns this data?
o How is it populated?
o How often is it updated?
· Is there a lot of missing data?
o Do we have data just for select segments of customers or for all customers?
This assessment will give us a better understanding of what the data is telling you, where it may be best used in the analysis, how best to link the data, how easy it will be to obtain and then any cautions/limitations that could be kept in mind with the use of this data. More to come next week on linking and benefits of using the data…
Director, Marketing Sciences