8 Effective Ways to Improve Your CRM Data Quality
Maintaining peak CRM data quality can help build customer loyalty, drive sales, and accelerate growth. So why—for growth-focused businesses, in particular—does it tend to be an afterthought?
The answer is simple. When you’re growing your business, you want to collect as much customer data as possible from as many different sources as you can. But the more data your CRM collects, the more complicated it becomes.
If you fail to perform consistent CRM data quality management, you’re likely to end up with a CRM full of missing, incorrect, and outdated customer information. This has lots of negative consequences, from hindered productivity to poor customer satisfaction and revenue loss.
Luckily, you can improve your data quality in several ways. Before we get into some best practices, let’s dig a little deeper into why the quality of your CRM data is so important.
The importance of CRM data quality
Your CRM data is a treasure trove of insights. Everything you know about your customers—their age, income, location, interests, purchase history, and more—can be used to improve their experiences.
But, if the quality of your CRM data is poor, your ability to create positive customer experiences is going to suffer. Missing, incomplete, duplicated, outdated, or incorrect CRM data skews the results of data analysis and directly hinders sales opportunities.
Take location, for example. A customer based in the U.S will be happy to see marketing materials with dollar signs, American spellings, and American lingo. But if you also ship to the U.K, you want to provide location-specific experiences. That means delivering marketing material that uses British spellings, currencies, etc.
A recent study by Validity found that 75% of businesses have lost customers at the point of outreach due to low-quality CRM data. 44% lose over 10% in annual revenue for the same reason.
Image sourced from validity.com
If you don’t have the right contact information, you can’t reach leads. If you have redundant data, you risk frustrating valuable customers with duplicate marketing messages. If you have inaccurate demographics, psychographics, and behavioral data, you’re not going to be able to deliver personalized experiences.
The list goes on. But maintaining high-quality CRM data does more than simply prevent these issues—it directly drives critical business improvements. The more accurate your data, the more effectively you can use it to meet your goals.
Eight effective ways to improve your CRM data quality
So, what steps can you take to improve CRM data quality? Let’s start with one of the most obvious solutions: identifying current CRM inaccuracies.
Assess existing CRM data for inaccuracies and redundancies
Inaccuracies and redundancies exist in CRM data for a variety of reasons, usually occurring during data collection, integration, or entry.
Customers can make errors when filling in lead forms, like misspelling or omitting essential information. Third-party data syncing tools can unload data into your CRM without cross-checking it against existing data, resulting in duplicate contacts. And employees can make errors when entering data into your system.
Regardless of how they happen, your business needs to conduct regular audits to assess your CRM data quality. Try to establish why these inaccuracies occur so you can tackle the root of the problem.
Let’s say you realize that the customer financial records being fed to your CRM are incorrect. This is a common problem with global businesses due to the different currencies and tax legislations that you have to consider.
You can fix this by using an accounting software for small business that automates data entry and calculates invoices and receipts in alignment with country-specific VAT and tax regulations (such as HMRC in the U.K and IRS in the U.S).
With the most up-to-date, accurate data to hand, your marketing, sales, and customer service reps can make more confident and informed decisions.
Screenshot from sage.com
Clean and update outdated or incorrect information
Once you’ve identified missing, redundant, and inaccurate information in your CRM, it’s time to clean and update it to maintain data accuracy.
Keep in mind that data quality is much more important than quantity. In fact, a CRM system that’s overwhelmed with data is more likely to suffer from low-quality data issues. So, don’t hang on to data that isn’t offering you value.
Data cleansing tasks will include:
- Merging or deleting duplicate data.
- Addressing incomplete customer records (e.g. records with missing phone numbers or email addresses).
- Fixing spelling, syntax, and formatting mistakes.
Apply real-time validation checks and alerts
Real-time validation stops incorrect or incomplete data (like emails, phone numbers, and postal codes) from being entered into lead forms.
Once the data is entered into the field—but before it’s been submitted to your CRM—validation tools will verify that it’s correct, complete, and accurately formatted.
This can prevent lots of common inaccuracies from being entered into the system, preserving the integrity of your data at scale.
Provide comprehensive training on data entry and maintenance
Human error is one of the leading causes of low-quality CRM data, but by arming your employees with the training needed to excel at data entry and maintenance, you can significantly reduce this risk while improving productivity.
Train your employees on data entry and maintenance best practices. Make sure they understand your formatting rules, data standards, and the correct process for documenting lead interactions. Create interactive, ongoing training sessions that include games, quizzes, and role-play to keep employees engaged and up-to-date with best practices.
Don’t forget to onboard new employees on your CRM. Choosing user-friendly CRM software instead of overly-complicated alternatives can prevent data entry mistakes and other human errors.
Image sourced from Channel Talk
Adopt standardized and consistent data formats
Unstandardized data—i.e. data that exists in multiple different formats within your CRM—is an obstacle to data hygiene. It accumulates masses of duplicate data and causes internal chaos, reducing communicative efficiency and impairing data analysis.
Data standardization involves establishing a company standard for formatting critical data, like customer names, addresses, and dates of birth. You need to define rules for each data field, including abbreviations, character length, number formats, capitalization, and more.
So, for example, you might rule that:
- State names should be written out in full instead of abbreviated (e.g. Kentucky instead of KY).
- Dates of birth should be formatted numerically (MM/DD/YYYY) instead of month, day, year.
- Website URLs should be written out in full (https://www.domain.com) instead of in their shortened alternatives (www.domain.com or domain.com).
Standardized data is much easier to error-check and analyze, contributing significantly to good data hygiene.
To enforce standardization in web forms, consider using drop-down fields for things like job titles, marital status, and age. If you need to use open-fill data fields, communicate your required format to those entering information.
To enforce standardization within your company, make sure your rules are communicated clearly. If you have customers around the world, establish a standard for international addresses, currencies, phone numbers, etc. Also, provide employees with tools that ease the process of standardization.
Leveraging ERP in retail, for example, can be used in tandem with your CRM and other data sources, giving you a full overview of your business, from initial customer insights for marketing campaigns to tracking their and fulfilling their order. Providing the best possible customer experience.
Enforce clear data governance policies and accountability
Data governance policies define the roles, processes, responsibilities, and technologies that are necessary for effective data management. Specifically, they establish guidelines that govern how to collect data accurately and handle it securely.
Along with helping to achieve regulatory compliance and accountability, data governance improves CRM data quality. When everyone in contact with this data knows the correct procedure for inputting, storing, and handling it, its reliability increases. As such, sales decisions can be made more confidently.
Leverage data enrichment services to enhance CRM data
Leveraging data enrichment can help you resolve what 56% of businesses say are the most challenging data quality issues of them all—missing and incomplete data.
Image sourced from validity.com
CRM data enrichment is the process of expanding and refining your existing CRM data with data from reliable, authoritative third-party sources. Enriched data can fill gaps in customer records, update information, and unlock new insights.
For example, your enriched data might update your customers’ contact information, presenting you with a re-engagement opportunity. Or, it might give you insights into a new interest that you can use to inspire personalized, targeted recommendations. Whatever the case, enriched data improves the usability, reliability, and overall integrity of your data.
Consistently monitor data quality and conduct regular audits
CRM data quality management is far from a “set it and forget it” task.
Customer data is always changing. People are constantly moving locations, switching their phone numbers, and exploring new interests. As your business grows, this data only becomes more complex, nuanced, and difficult to maintain.
The more customers and data you have, the more regularly you should conduct data quality audits. Ongoing data quality monitoring and auditing prevents your CRM from becoming overwhelmed with bad data.
The result? Increased productivity, reliably up-to-date contact information, and more valuable and personal customer experiences.
Data quality trumps data quantity every time. To extract the most value from your CRM, you need to maintain peak data quality by consistently monitoring, auditing, cleaning, and enriching it.
But that’s just the beginning. By setting clear data governance policies, enforcing standardization, and providing employees with data management training, you can increase the long-term reliability of your CRM data quality. Start practicing good data hygiene today.