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CRM Data Integrity: “Garbage In = Garage Out”

Maintaining a CRM platform that works for you—not the other way around.

Clean, complete and accurate data is the key to keeping your agency in the know of your agency’s true Key Performance Indicators (KPIs). The definition of Key Performance Indicators is a quantifiable measure used to evaluate the success of an organization in meeting objectives for performance.
An agency’s KPIs provide a focus for strategic and operational improvement. They are the basis for analytical decision making and help focus attention on what matters most.
Accurate information housed in your customer relationship management (CRM) systems has the most impact on the metrics reported in your agency’s KPIs. Hence the term… “Garbage In = Garage Out”

What Is Bad Data?
To help understand the affect that bad data might be having on your business, let’s start by considering what constitutes bad data.
Bad data is defined as information that is incorrect, outdated, duplicate, improperly formatted, or completely missing from your sales and customer database. Instead of being able to rely on this data, this data could cause you to commit potential E&O errors, customer service mistakes and affect your marketing campaigns or sales interactions.
Several recent studies estimate more than 40% of company databases grow outdated yearly. The errors and inconsistencies in your CRM data make it difficult to have reliable insights and will affect your organizations operational efficiencies. Let’s not forget miscommunication to your policyholders.
A faulty database is an inefficient database which means that clean, accurate and trustworthy customer data is essential to the success of your business.

How does data become bad?
1. Human error: Customer data is inputted correctly
2. Data is formatted incorrectly with a bad conversion of the data. When combining multiple data sources, there are many opportunities for data to be duplicated or mislabeled.
3. Downloads not processed timely or not processed accurately
4. Bad Setup at the Policy or Company level in your CRM

What are the effects of bad CRM data?
We have all seen the consequences of bad data in our CRM. Ultimately, inaccurate records and poor data can result in more time and effort spent correcting the data than time spent on customer service or sales.

Now the BIG questions…how do you clean up your customer data?
1. Look for inconsistencies – Are all your carrier names, policy titles, application types, and statuses uniform? Many CRMs offer their recommendations to recognize inconsistent data
2. Purge duplicates polices and clients
3. Void AND Archive old data
4. Combine Duplicate Records – Make it a habit to search your database before you enter a new Prospect or Client
5. Identify data that you are no longer using – Often new updates or version of your CRM will make some data collection obsolete
6. Manually fill in missing data or obtain carrier downloads to flood data
7. Review important reporting data such as Current Rate, Quote Premium and Effective Dates
8. Evaluate expired policies to ensure that they are no longer active. If active, renew or reinstate accordingly

Now it is up to you to keep your data clean
How do I keep my data clean in my CRM?
1. Create standard practices around data entry – Is everyone consistent in the way to enter information on clients and prospects? Does everyone follow the same best practices to ensure consistent data?
2. Determine who can edit your data and in what way. This can usually be handled by the User Permissions in your CRM
3. Most CRMs have ‘Required Fields’. Set these requirements to align with your data collection
4. Regular scheduled and standardized data review
5. Monthly, if not more frequent, data cleansing

Five characteristics of quality data:
Accuracy: Ensure your data adheres to our agency’s values.
Completeness: Require manually entered data meets your agency requirements.
Consistency: Continually monitor that your data is consistent within the same databases.
Uniformity: All data possesses the same underlying structure.
Validity: The accuracy to which your data measures to your defined business rules.

When you trust your data quality, you have a clear understanding of your agency’s KPIs which is an important step to making efficient and effective business decisions. You can also effectively manage your book of business with time management optimization to elevate your sales performance.


Written on August 18, 2021 by Peggy Corbett