Data Quality is the cornerstone of your CRM strategy
How do you get more out of your Customer Relationship Management (CRM) solution? Does it always require additional functionalities? Well...enhancing the Data Quality in your CRM may already bring you nice benefits!
Why is data quality important?
Ensuring good data quality in your CRM solution brings benefits like:
- Being able to better prospect and target new customers
- Being able to more easily identify cross- and upsell opportunities
- Increase efficiency
- Retrieve the right information fast
- Increase productivity
- Easier and better decision making
How do you measure the quality of your data?
There are different attributes that help you estimate data quality:
|Topic||Description||How to assess|
|Age||When was the last time each record was updated?||Run reports to check the last modified date of records. What percentage of records have been updated recently?|
|Completeness||Are all key business fields filled in?||Make a list of which fields are required for each business use. Next, run a report to show the percentage of blanks for these fields.|
|Accuracy||Is your data as accurate as possible?||Where possible, validate the content of your records against a trusted source.|
|Consistency||Is the same formatting, spelling and language used across records?||Run a report to show the values used for date, currency, country...|
|Usage||Is data in your CRM application effectively used?||Review the available tools and resources your business uses.|
How do you improve data quality?
Ensure that you know which customer data is needed to support your business' objectives. It's also important to understand the data that is needed and how people in your company use it. You need these data to develop a data management plan.
A typical data management plan includes standards for creating, processing and maintaining data:
|Naming||Set naming conventions for records||Make sure that company names are never abbreviated except when the abbreviation is the standard name.|
|Formatting||Ensure that dates and currency fields are formatted in a uniform manner||Use dd/mm/yyyy for all date formats|
|Workflow||Determine processes for record creating, reviewing, updating and archiving. Determine all the stages a record goes through during its lifecycle||Route service requests upon predetermined rules.|
|Quality||Set appropriate standards for data quality - make important fields required, validate field content, use picklists to set predefined values||
Active leads should be updated at least once per month.
The close date of an opportunity may not be earlier than today.
- Data.com Assessment App
- Data Quality Analysis Dashboards
- RingsTrue: validation of phone fields on Account, Contact and Lead objects
Creating a data-centric culture is the best guarantee for the best data quality in your company.
You want more information on how implementing a data-centric approach? Contact us via this form.