CRM: An Introspective

CRM: An Introspective

What can it mean for your team?

Success Derived from Data Quality

Customer Relationship Management (CRM) focuses on the movement of customers through the pipeline, beginning with a marketing classification and culminating in a service experience. Anyone discussing CRM practices on a regular basis can appreciate the depth modern CRM platforms bring to the table for information retrieval and organization. Nevertheless, the success of CRM is dependent on the quality of data utilized.

Decisions from Data

The information organizations rely on to fuel CRM relevancy has become very accessible and increasingly accurate. Data sources such as LinkedIn, Dun & Bradstreet, and Manta have contributed greatly to filling gaps in the attributes of current and prospective customers.  CRM platforms can eliminate limited data capture for important records (e.g. people, organizations), allowing flexibility in relationships for variable information (e.g. phone numbers, addresses).  However, this flexibility has its downfalls. Many organizations and teams have experienced challenges with CRM data management. Some reach to obtain too much excess data, which realistically cannot be maintained over time. While others fall victim to utilizing data that lacks in quality. Consequently, it’s no surprise that organizations are placing more attention on best practices to ensure that the data they use will add to the value of their CRM platform, not diminish it.

Best Practices from Salesforce

Oliver Demuth at Salesforce summarizes, “to ensure consistently high data quality, you’ll need to train your users, create and implement a data quality process, and use available technologies to automate the process whenever possible.” Below is a six step approach recommended to ensure consistently high data quality.

Step 1: Profile your data

First and foremost, make sure you understand your data. Know where it came from, any potential problems that may arise, and make sure there is no information that is duplicated!

Step 2: Control your data

It is necessary to attain accuracy and ensure that the right users have access to the right information.

Step 3: Integrate your data

Data typically comes from many systems. Make life easy! Integrate your systems so that updates in one system automatically update the others.

Step 4: Augment your data

Give salespeople and managers an edge by enhancing your data with valuable information such as purchasing patterns or competitive analysis. Caution: make sure this information is actually useful!

Step 5: Monitor your data

Maintaining data quality is an on-going process. Policies, processes, and tools need to be established to ensure data is constantly monitored.

Step 6: Assign ownership, train users, and commit to a data-quality process

Show users how data directly affects their work so they are committed to taking part in any data-quality initiative.

Visit for more in-depth information regarding each step.

Written by Jeff Pierson, Demand Chain Success Manager

Jeff has been leading business and technology teams through CRM projects for over ten years. As a Success Manager at Demand Chain, Jeff is responsible for guiding teams through CRM implementation and platform ideation as well as maximizing the client’s platform investment through lasting CRM value and adoption.

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