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In 2020, you’d be hard-pressed to find an organization that doesn’t use a CRM. But while more than 90% of organizations use some CRM software, adoption rates are still quite low, with an average adoption rate across industries of just 26%. (AgileCRM)

This proves that while nearly every data-driven organization uses a CRM, nearly 3 in 4 have fallen out of love. Relationship Status = It’s Complicated. But that’s okay! Dirty data can make even the most well-planned CRM seem ugly to the end-user. Whether it’s a budding romance or an old flame, every CRM could benefit from a quick data spruce-up.

CRM and Data: A Love Story

How to Fall Madly in Love with Your CRM

“The first thing I noticed about my new love (a.k.a. Salesforce), was that it was unhappy. We had transferred all of our data from an old CRM, and my beautiful Salesforce was full of unstandardized data, missing information, inaccurate information, and tons and tons of duplicates.”

Data quality is a valuable metric for measuring adoption. Poor data quality, however, can cause users to fall out of love with their CRM. Here are some key steps you can take to improve the quality of the data flowing through your CRM, and therefore improve your relationship with your CRM

1. Develop a Normalization Plan

Looking at critical fields and making sure users complete them uniformly across your entire organization is important. Design a protocol to ensure users fill out all fields consistently and accurately. This creates strong data integrity and reliability, which translates into higher user confidence and adoption.

Non-normalized data is a type of dirty data which has numerous negative effects on the love you feel for your CRM: from sending bad emails to mailing to bad addresses and losing customers altogether. For example, review the following ways to write:

Improve Data Quality

  • Director of Human Resources
  • Director, Human Resources
  • Director of HR
  • DIRECTOR OF HUMAN RESOURCES
  • Director HR
  • Human Resources Director
  • HR Director

Don’t expect perfection: data normalization is an ongoing process for improving data hygiene over time, and with it comes a deeper bond and love of your CRM.

2. Normalize your CRM

Now that you have a plan in place, you must execute it. The standards determined for job titles, cities, states, countries, etc. should now be rolled out into your existing CRM data, and be part of training for those entering data going forward. Use an automated normalization tool to get the job done more efficiently and effectively. In your quest to revive the romance between you and your CRM, RingLead can help you:

  • Standardize all possible variations of titles, names and other common data
  • Keep a healthier database and run more effective campaigns
  • Help your team to work more efficiently
  • Customize your data formatting in your CRM globally

3. Merge Duplicates

Research from Salesforce cites that 50% of teams leverage data to produce timely, accurate forecasts. However, these reports can be severely skewed by duplicate records.

Merging duplicates is always better than deleting data. Every piece of data holds value, so merging is the way to go. 30% of marketers say having disparate data sources is the main reason why they can’t get useful insights from customer data (Getbase). When you really love your CRM, you’ll do whatever it takes to correct these mistakes.

A duplicate removal application merges the duplicates and cleans up the database quickly. Once your data is clean, you want to keep it that way. Duplicate prevention stops the bleeding and ensures you’re not simply putting a cap on that leak. Dirty data will continue to infiltrate your system as your contact data changes, but with strong prevention apps, your data will be checked before it enters your system to avoid duplicates.

[LEARN MORE]: RingLead Cleanse — Boost Salesforce data performance with powerful deduplication, normalization, and automatic lead-to-account linking

To make sure the duplicate is merged with the right contact, you’ll need to set master rule settings. This way, all new data matching the original record, or master record, will automatically match and merge. If you have five records in Salesforce, you likely only want to keep the lead source from the first/master record, but use all of the current title and phone number fields from the most recent entries.

With these plans and practices in place, love will be in the air.

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