Have you ever worked in a company that’s deployed a wonderful CRM application with the magic vision that all will be transformed: more leads, more sales, better customer satisfaction, efficiencies all round, and so on; only to find the data within the application is just not good enough.
If left unattended (that’s the data), two sure negative consequences will happen:
- The user base will lose confidence in the data and speak of the CRM application being poor (when in fact it’s the data); and
- The data will naturally degrade becoming worse in quality day by day
I have seen so many users relate negatively about the CRM rather than the data, when in reality the CRM is perfectly fine.
So why is this case?
Well, initially the data is identified as the problem area, but because the CRM application is then less frequently used (due to poor data), the CRM application also receives a bad name by association.
In the reverse scenario, if the data is good, but the CRM application is poorly implemented, the data will eventually receive a bad name as it degrades over time.
So why do so many organisations cleanse their data just before migration and then don’t really focus on this until it becomes a problem.
There are many reasons but the overriding themes are: assuming new data will be entered correctly all the time as the new CRM is designed to stop data errors and secondly, no one is aware of data degradation.
The data will naturally degrade and users will enter data that’s of poorer quality than the existing data.
No CRM solution is perfect at enforcing 100% data quality, it's simply not practical.
For example, if the user does not have an email address, then the record cannot be completed.
No email address means the potential for leads/revenues from an email campaign is reduced.
Before you know it, another major cleanse is required to make the data fit for purpose.
A simpler and cheaper option is to:
- Cleanse all new data on a monthly basis (or a frequency suited to your business); and
- To implement a simple measuring technique to keep an eye on how the data is looking
By using these two approaches the data is proactively managed, the user base has confidence in the data and ultimately in the CRM application.