CRM data entry best practices: improving CRM data quality
Published September 27th, 2022
Data, data, data. Like eating, sleeping and exercising, it’s what increases our performance. So, why do most B2B teams fail to grasp that CRM data quality is the foundational block that every marketing and sales team needs?
Marketing Communications Manager at Tiny
Perhaps, it’s because data’s boring. While that’s very true, data is crucial. When you maintain the quality of data entered in your CRM, it ensures the contact and account information that's generated (and relied on) is accurate, connected, compliant and actionable. That then ensures your outreach, campaigns and results are better, and your activities are less prone to failure. Convinced yet?
Then let’s get more concrete. If you’re not maintaining your data quality, it’s costing you money: reportedly around US$100 for every bad record. But bad data in your CRM isn’t just wrong data. It’s also missing, out-of-date, and incomplete data.
Your data is aging – even when you do nothing
Data ages at an alarming rate. It’s in a fluid state of constant change, because people change jobs, move, retire, change industries, and lives change. All the time. But the aging of data can be very costly for businesses.
According to pre-pandemic research from Sirius Decisions (now Forrester Research), between 10% and 25% of B2B customer and prospect records include critical data errors, causing 40% of business objectives to fail. Errors range from incorrect demographic data to a lack of current disposition, which can spell failure for any marketing campaigns reliant on the CRM data.
More recently, the news on poor quality CRM data got worse.
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In a post-pandemic 2021 study by IT ProPortal in the UK, it was revealed that the estimated rate of organic data decay had accelerated by an average of 0.5 percent per month, resulting in an annualized decay rate of 37.5%. The rise was directly attributable to the pandemic’s high mortality rate and the number of people moving house.
In addition, a recent Gartner report estimates that when it comes to B2B contacts – especially in sectors with high job turnover like Silicon Valley technology and those suffering from ‘The Great Resignation’ phenomenon – the data decay rate is estimated to be 70.3% per year.
What’s the cost of data decay?
Data decay and aging is the gradual loss and degradation of both data quality and quantity within a CRM. The data tends to decay from inaccuracies, outdated information, information coming from an unreliable source, or simply aging out.
It’s hard to estimate the exact cost of data decay, because its effects are spread across an entire organization. Bad contact data insidiously sneaks into processes and disappears profit by many means – through returns, mis-addressed invoices and communications, lost sales time, wasted marketing, and email blacklisting (from sending too many undeliverable emails). Its reach is wide and deep.
In an attempt to better quantify the cost and using the most verifiable data available, let's take some conservative numbers and do a little math. For illustrative purposes, here’s a basic calculation of the cost of data decay:
Total number of contacts
Average cost per bad record
37.5% decay rate per month
156 records monthly
Decay rate over 12 months
1875 records x US$100
Based on 5000 contacts, with an average cost US$100 per bad record and a data decay rate of 37.5%, 156 contacts changed their name, addresses, phone number, job or email address in the last month. You now have 156 stale (or bad) records on your CRM database that haven’t been touched, changed or updated. After six months that’s 936 records or 1875 annually, translating to an annualized loss of US$187,500.
As you can see, even doing nothing with your data is guaranteed to hurt your business.
What does bad data affect?
Bad data doesn't just affect the marketing and sales funnel. It affects the entire organization. Back in 2016, IBM’s estimate of the yearly cost of poor quality data, in the US alone, was $3.1 trillion. In a post-pandemic world of constant change, it’s daunting to think of the current cost estimate.
The same HBR article noted that 50% of the time “knowledge workers waste time in hidden data factories, hunting for data, finding and correcting errors, and searching for confirmatory sources for data they don’t trust.” That's likely not dropped either.
Without accurate, up-to-date data, companies waste huge resources targeting the wrong people with the wrong messages and making poor, ill-informed business decisions.
Left unaddressed, bad data can result in:
Incorrect segmentation leading to poor personalization
Failure of marketing automation campaigns
Inaccurate reporting and forecasting
Wasted time for all team members
Wasteful, unnecessary spending
Breakage of integrations with other software
Diminished sales revenue
Longer sales cycles
Higher churn rates
Wrong decisions made
Brand reputational damage
The reason bad data costs so much is that it affects everyone – because a CRM is useful for more than sales. Decision makers, managers, knowledge workers, data scientists, and many other team members feel its effects in their everyday work.
Data is fundamental for business processes, especially lead nurturing and customer retention, therefore CRM data entry best practices need to be established and maintained, to improve the data quality inside your CRM.
What is CRM data quality?
Data quality is the cornerstone of customer relationship management. It encompasses the accuracy, integrity, value and uses of the data you’ve collected. It sets the standard for everything that you're intending to collect, enter and maintain – so every piece of data needs to be high-value.
Data platform Atlan says: “If your data is: accurate, available and accessible, complete, relevant and reliable, timely, gives the right degree of granularity, and helps you with decision making, then your data is of good quality.”
Why is CRM data quality important?
Strong customer relationships can only be built with access to relevant customer data. Therefore your CRM database needs to not just be up-to-date, but incrementally improved.
While that seems a burdensome and time-consuming task, there’s clear linkages between high quality CRM data and positive impacts on your business activities – specifically segmentation, marketing campaigns, more efficient spend, lowered compliance risks, as well as higher sales revenue and brand reputation.
Pre-pandemic McKinsey research showed that organizations who leverage their customer data outperformed their peers by 85% in sales growth and more than 25% in gross margin. Then in their 2020 research, McKinsey found that sales teams who actively leverage CRM data using automations, see up to 10% sales uplift.
Those two snapshots show how essential clean, organized, and accurate data has become to the success of campaign personalization, sales outreach and email marketing automations. When companies champion data quality, and continuously assess the usefulness of their data, they reap the rewards.
That's why successful B2B teams are [re]committing to improving their CRM data entry.
Possible CRM data issues
The quality of data in a CRM depends on the accuracy of its contributing sources. Rubbish in = rubbish out. Always consider the quality of your data sources and the reference files used to populate a record and question both “How good is this data?” as well as “How trustworthy is this to use, as the basis for a bold business decision?”
Poor quality CRM data entry prevents sales teams from being productive and efficient. From manual entry errors to poor activity logging and duplicate contacts, CRM data entry that doesn’t follow CRM best practices, negatively impacts your sales revenue.
Eight of the CRM issues resulting from manual data entry errors and other processes are:
Too much data
That’s a long list for a never-ending issue.
How can you keep your CRM data clean?
With a quick Google search, you’ll find there’s lots being said about having cleaner CRM data. However, while the need to fix it is indisputable, there are different views on the how.
Many recommend data cleansing and periodic hygiene practices. Thankfully, in an era of third-party cookie depreciation and privacy concerns, some of your data quality and accuracy issues can be addressed through the use of identity resolution platforms. These tools comply with privacy legislation while also providing valuable insights by connecting customer data from multiple touchpoints.
As great as these tools are though, something has to be said. CRM data is always going to be messy. It’s a lot like a bird cage – clean it once a month, week or even daily. You can be certain it’s dirty again, almost immediately.
That means establishing data practices to fix the majority of issues, before they start.
CRM rich text editor advantage
It’s clear: CRM data entry that doesn’t follow best practices, negatively impacts your sales revenue. What else affects the quality of the CRM data used across an organization? The rich text editor that’s embedded in the CRM software.
Integrating the best CRM HTML editor components in your tech stack can help you achieve your goals of data quality, integrity and increase your sales. In many cases, using the best technology can also increase the engagement with and quality of the outputs from your CRM.
That’s especially true when you use state-of-the-art content authoring components that help resolve your data quality issues. You’ll get cleaner data (better for reporting and the next person using the record) and rules that can be enforced by the editor automatically at the point of data entry, rather than a manager having to monitor every data entry point and person.
CRM data entry best practices
There’s three golden rules to CRM best practices data entry:
- Clean your existing data and regularly assess its health
- Stop bad data from being added
- Remember data gets stale immediately, so data quality is a never-ending mission.
The first rule is beyond the scope of this article. However, here’s four best practices you can implement immediately. By integrating a quality WYSIWYG text editing component in your CRM, you can satisfy the second golden rule listed, and elevate the reliability of your CRM data.
1. Streamline your documentation methods
Organize your CRM data contributors to understand where bad data may potentially be introduced.
- Start by mapping the sales and marketing funnels and workflows, then extend it into other areas of the organization that use the CRM. Understand where the data comes from, who enters it, who accesses it and what procedures (if any) are used to vet and store it throughout.
- Then outline a clearly defined process, to ensure that low-quality data no longer makes its way into your database.
- Establish a retraining program for all existing team members, on the new process, and an onboarding process for new appointments.
2. Tighten your data collection
Some of the data you’re currently collecting may well not qualify as being usable, and ends up piling up in a corner of the CRM as defunct bad data. That data then becomes difficult to manage, time-consuming and a burden to your resources, so it's easier to tighten your initial collection methods and locations.
- One source of lead information that's often overlooked, comes in via the contact, opt-in and lead-gen forms embedded on websites and landing pages. As a website expands, old pages are often forgotten and different data formats continue to come in from various sources. Close down this data entry point by standardizing your forms across all channels.
- Manual data entry leaves a significant margin for errors. However, it’s generally not possible to eliminate it completely. Often a single misplaced or misused letter can determine the deliverability of an email, so it’s important to create a centralized set of rules for the creation of contact records – to establish and maintain checks and balances on each entry.
- Another way to shrink errors is to add proper validation to your standardized forms (see above). Validation ensures the data entered meets certain criteria – correct email format, correct length zip or postcode, or appropriate capitalization for names and locations.
- Pre-set dropdown option lists can also help to limit error rates. These can offer country, state and other established location information, to help cut back on standardization issues from people entering abbreviations that need to be cleaned up at a later date.
3. Create rules or guidelines for uniform data entry and processing
Having standardization rules that apply to all CRM entries helps to ensure the quality of your data. Start by reviewing the input fields in the CRM to collect consistently formatted customer data, including:
- Name capitalization
- Forcing proper sentence capitalization and preventing common typos (using the TinyMCE Autocorrect plugin)
- Standardized salutations, including gender neutral (eg. using TinyMCE’s text_pattern option to automatically replace Miss with Ms.)
- Converting abbreviations to long-form or vice versa (eg. also can be done by using text_pattern)
- Utilizing one standard dictionary for spelling (eg. specifying American English, but not British English as the language, by using Spell Checker Pro)
- Updating all customer records after every interaction
- Make the necessary fields mandatory
- Mandate certain data types when inputting values
WYSIWYG HTML text editor features for CRM
There are some common CRM system data errors that can have a profoundly negative effect across your database. A quality rich text editor can help to automatically counter these at the point of data entry, instead of letting the errors accumulate.
|Rule or guideline
|Why establish the rule
|Do not copy over formatting from other apps into the CRM
|Keeps CRM data clean and easy for the next person to understand
|PowerPaste plugin can be configured to strip out CSS formatting, but maintain HTML structure
|Lock down the creation of unacceptable formatting and styles
|Keep CRM data clean and easy to understand
|Customize the menu and toolbar of the editor to restrict styling to only what you want in your CRM records
|Limit the field character length of free-test areas
|Forces users to enter concise information
|Word Count plugin can show how many words/characters in the editor and a hard character limit can be added
|Use consistent shorthand
|Keeps CRM notes easy to scan and read
|noneditable_class option lets you specify content that can’t be changed (eg. headings in call notes).
|Set rules around abbreviations – whether you want to use abbreviations in your CRM or avoid them entirely
|Makes CRM records easy to search and scan
|text_pattern option can automatically replace or highlight disallowed text, for example automatically replacing abbreviations with their long form
|Ensure any merge tags (also known as personalization tokens) are read-only and belong to the approved dictionary of tags
|Avoids display errors when content is rendered
|Merge Tags plugin lets your users insert predefined, read-only merge tags into your content
4. Improve UI, UX and use better templates
CRM adoption and usage is greatly influenced by poor, clunky and onerous user interfaces (UI).
- Regular audits and reviews of typical user behaviors and usage should be undertaken to continually improve the user experience (UX).
- The review should also include checking whether template layouts are still the best fit for current usage, and whether workflows truly reflect the way the business currently operates.
UI in TinyMCE
TinyMCE has several options to customize the UI of the editor. From custom skins to a configurable toolbar and menu bar, you have the freedom to make the editor as minimal – or as full blown – as you need.
CRM data driving data-driven growth
The Gartner Future of Sales 2025 report reveals that by 2025, 60% of B2B sales organizations will likely have transitioned from experience- and intuition-based selling to data-driven selling. Why? B2B buyers now prefer to engage with suppliers through digital and self-service channels, therefore making multi experience selling a must-have.
However, you can’t deliver that without solid, accurate CRM data.
Your team needs to understand the fundamental importance of data: how, when, and where it’s used in workflows, how a data-driven decision is better than a hunch, and why precise, personalized communication is vital to clients.
Most importantly though, managing the quality of the data in your CRM is both an art and a science. And it's a never-ending task.
Marketing Communications Manager
Messaging strategist and copywriter whose passion lies in working with brands like Tiny, that have deep-seated values and embrace the power of their story. She gets a kick out of solving problems, loves learning new things and making stuff, every day. When she’s not thinking through clever copy lines or clarifying value propositions, she’s knitting amazing socks for everyone she knows.