No one likes clutter, whether it’s in your office, your email inbox, or in your customer relationship management (CRM) software. But, unfortunately, it’s all too easy for junk to pile up unnoticed over time until it’s too late, making you feel unorganized, unproductive, and off-kilter.
A recent article by Forbes states that “After an analysis of the CRM software market, it was clear that two products are dominating in both sales and customer satisfaction: Salesforce and Microsoft Dynamics.”
For this reason, CRM users need to make sure their data is accurate. Why? Because when a company has inaccurate or poor quality information about its customers, the organization can’t provide the right product at the right price based on what’s needed. This could mean missing out on opportunities for growth and profitability. So if you want your business to flourish, then you’ll need to make sure your customer records are up-to-date! The first step is cleaning up those records with a user-friendly app like Clearbit Connector.
While we can’t straighten up your house for you like Marie Kondo, we do have some advice to share regarding CRM data cleanup. A messy CRM database doesn’t just make your data feel “cluttered”—it can also have a tangible negative impact on your organization’s effectiveness, agility, and bottom line.
Unorganized CRM data can create problems such as:
- Failure to keep proper track of your interactions with customers and leads.
- It is wasting valuable employee time by sifting through the customer contact information that’s inaccurate or duplicated.
- I am neglecting, passing over, or alienating a significant lead that might have become a valuable customer.
The consequences of not performing CRM data cleanup can be drastic for your organization’s productivity and profitability. For example, IBM estimates that poor data quality costs the US economy $3.1 trillion every year. At the same time, IT research and advisory firm Gartner projects that this figure is $13.5 million for the average business. In addition, several other studies have estimated that insufficient data may be costing companies between 10 and 30 percent of their annual revenues.
Fortunately, your business doesn’t have to suffer the same fate. Below, we’ll discuss some of the most common reasons for data quality issues and offer our suggestions for performing CRM data cleanup so that you can avoid the most common mistakes and keep your database in top shape.
3 Reasons Why You Need CRM Data Cleanup
According to Salesforce, as much as 70 percent of data in a CRM system “goes bad” (i.e. becomes obsolete) every year. This section will discuss the three biggest reasons why nearly every organization needs a CRM data cleanup.
1. Duplicate data
Duplicate data is an all-too-common issue with CRM databases, and it can happen for a variety of reasons during the process of data collection and data entry:
- The exact lead might sign up using different emails or street addresses, creating a separate record in the CRM for each one.
- The same data might be entered with different formatting, abbreviations, etc. For example, 555-555-5555, 5555555555, and (555) 555-5555 all represent the same phone number, but your CRM system might not realize this without performing data cleansing.
According to HubSpot, data duplication rates may be as high as 10 to 30 percent for companies needing a CRM data cleanup.
Duplicate data is manageable and relatively easy to fix on a small scale when doing CRM data cleanup—identify it and delete it. In the long run, though, the same data can be a disaster: every additional duplicate record makes it more and more time-consuming to sift through your database, which cuts into the time you have to follow up with leads. It’s no wonder that sales representatives only spend 36 percent of their time selling.
To avoid this, you need to address duplicate data at the source by performing CRM data cleanup. This means going through your entire dataset, discovering the start of the duplicate records, and standardizing their format. Limiting the type and amount of input options (e.g., only allowing selections from a drop-down menu instead of text boxes that will enable free entry) is another way to deal with the problem further.
2. Missing Data
Missing and incomplete data is another painful and all-too-common issue with your CRM database. For example, a lead might fill out contact data such as their email address, phone number, and company while forgetting to put down their name—and now that you’re going through the database, you realize you have no idea what to call them.
Again, suppose this is a one-time incident. In that case, it’s not too tricky to do CRM data cleanup by researching the missing information, filling in the blanks, and working on converting the lead to a paying customer. But when this pattern repeats on a larger scale, it becomes a much more time-consuming and challenging problem to solve—not to mention the opportunity costs you face from not following up with leads sooner.
The complications don’t end there—without CRM data cleanup, your sales team won’t have access to a complete picture of your customers and leads. As a result, any automated marketing tools you have (e.g. sending more personalized emails to your contacts or separating contacts by their lifecycle stage) are liable to fail when trying to perform their functions. As a result, you’ll be unable to contact or split your leads correctly, if at all—so you’ll either have to do it manually and painfully or miss out on them entirely.
Finally, incomplete information doesn’t just have consequences at the level of individual leads. It can also create gaps in your large-scale understanding—things like which markets to focus on or which tips are most likely to convert into opportunities and customers. Without a dedicated CRM data cleanup program, you’ll risk falling behind in your ability to compete in a crowded marketplace.
3. Out-of-Date Information
The older your data is, the more likely it is to be inaccurate, making it useless. This fact is especially actual for your CRM data. Companies are formed or go out of business daily, employees leave their jobs or get new job titles, and people change their addresses and phone numbers.
According to the US Bureau of Labor Statistics, the average employee has been with their employer for 4.1 years. However, annual turnover rates at some businesses could be as high as 15 to 25 per cent. So even a single inaccurate data point could make it impossible for you to get in touch with or follow up with a contact.
For example, your CRM might show that you have 10,000 different contact records for leads in the Boston region—but what it doesn’t show is that 1,000 of these leads have moved to new cities since you collected their data.
Without doing CRM data cleanup, you might incorrectly assume that the health of your business is more robust in a particular region than it is. In turn, you might make bad judgment calls about your advertising and marketing campaigns to reach these (now-extinct) leads: e.g. putting up billboards in a part of town where they no longer live or buying Facebook ads in their time zone.
Like the issues of duplicate data and missing information, incorrect data due to an out-of-date CRM database can cost you dearly.
While correcting one record might not take much longer than a phone call or web search, fixing hundreds or thousands of documents will be time-consuming to the extreme (not to mention mentally exhausting for the needy team members assigned to the task).
CRM Data Cleansing: How to Clean Up Your Customer Database
How do I keep my data clean in my CRM?
Many marketers know that the contact data they have in their CRM isn’t the best quality.
Unfortunately, most companies lack the staff to check the quality, let alone manually go through their entire database to find flaws and restructure it. Even if they did have the team to allocate, it would mean pulling them away from other tasks, wasting time that could be spent strategizing, implementing, and doing higher-level work.
So, how can you keep your data clean?
1. Create standard practices around data entry
Once you have a clean, organized data set to work with, you need to implement practices ensuring future data is entered consistently. You’ll have to decide how you want your contact listings to look based on your needs. These guidelines should include what information you want to collect and the format you wish to enter.
When inputting and collecting data, the same piece of information can be entered multiple different ways.
Ensure that anyone inputting data into your CRM is familiar with your particular guidelines to ensure that everything is streamlined going forward.
2. Limit the number of people who can edit it
To reduce the number of flaws in your database, you should consider limiting how many people can edit it. For example, don’t give everyone on your team full administrative privileges, or your CRM database will turn into a mess.
Only allow those who need to edit contacts to have permission to do so. And make sure they have training on your formatting guidelines for entering data.
3. Regular data cleansing
Regular maintenance of your CRM database is essential to keeping it clean. However, no matter how strictly you implement your data-entry guidelines and how few people can edit data, you will still end up with dirty data.
Using marketing automation, like online forms, is one of the best ways to find new leads. The problem is that you have no control over how people are entering their information into these forms. For that reason alone, you will need to set up a regular data cleansing schedule to clean up your records and identify missing data.
How does data become bad?
Marketing and sales professionals estimate that about 30% of their data is inaccurate in some way. Collecting insufficient data has a negative domino effect on your marketing campaigns, sales and can even ruin your company’s reputation.
Insufficient data is any information that is outdated, inaccurate, duplicated, formatted incorrectly, or missing information. There are many ways that you can end up with insufficient data in your CRM database.
1. Outdated data
Customer contact data is constantly becoming outdated. People change their phone numbers, addresses, and job roles all the time. Here are a few stats to give you an idea:
- 40% of email users change their email address at least once every two years
- 20% of postal addresses change each year
- 18% of phone numbers change every year
- 60% of people change job functions within their organization every year
2. Data is formatted incorrectly
You can write figures such as addresses, names, and dates in a variety of different ways. However, if staff is manually inputting data or people are filling out online forms, chances are they aren’t all going to enter it in the same format.
3. Customer data is input correctly
When people fill out online forms, they may put the wrong information in the wrong box or the accidental typo. The same is possible with manual data entry. For example, if a name is incorrect, all your marketing and sales communication will be using the wrong word.
4. Duplicate data points
If you’re merging lists, it’s possible to end up with duplicates. You could also have the same person take advantage of multiple lead generation opportunities and end up with their email in your list several times.
Here is an example of what a dirty data list might look like:
The Impact of Bad Data
Before we jump into the types of insufficient data and fix them, let’s talk about how big the problem is.
Insufficient data can have a significant effect on the ROI of your marketing campaigns and initiatives. As data collection has become a more substantial component in all marketing and sales campaigns, several recent studies have looked into the real-world dollar impact that insufficient data can have on a company, and the results of those studies are staggering.
- The research firm IDC estimates that insufficient data costs US businesses up to $3.1 trillion per year.
- A study by DiscoverOrg found that sales and marketing departments lose about 550 hours and up to $32,000 per sales rep from bad data ad that 40% of lead records have insufficient data.
- A Gartner survey of companies found that insufficient data was costing each $14 million per year.
- RetailTouchPoints found that insufficient data costs retailers over $9.7 million annually.
So the conclusion is that — insufficient data has a severe negative effect on your company ROI. But how does that happen? What are the different types of adequate data? How does bad data impact your returns in real-world terms?
How Does Bad Data Hurt My Marketing & Sales Results?
So it’s clear that lousy marketing data has a verifiable impact on the marketing ROI of companies. But connecting those issues to the natural ways that your campaigns and operation are impacted can be difficult.
Let’s take a look at some of the real-world examples of how bad data directly translates to a lower return on your investments in marketing and sales:
Ineffective Marketing Campaigns
Marketing campaigns that use outdated and incorrect data simply won’t be as effective. Customers love it when companies speak directly to them. 78% of customers will only shop with businesses that have had personalized interactions with a company.
Insufficient data means missed opportunities. A prospect that otherwise might have been interested in your product could be turned away when you get key details about them or their interactions with your brand wrong. Worse, insufficient data might cause them to feel like your product or service offerings aren’t. Insufficient data can also harm your targeting, causing you to waste your ad or email marketing budget on the wrong prospects.
Negative Brand Perceptions
When you get critical information about your prospects and customers wrong in your personalized marketing messaging, it will harm their perception of your brand. On the other hand, 87% of consumers say that personally relevant content positively influences their feelings about a brand.
When you get that wrong, they dislike it. 63% of consumers are highly annoyed by brands that use old-fashioned marketing strategies that repeatedly blasting generic messages.
You have a limited number of interactions to grab the attention of your audience. A simple mistake can push them away and kill any chances of developing a positive relationship in the future.
Bad Data Makes Optimization Difficult
When your campaign fails to meet expectations because of insufficient data, it can be hard to recognize that that is the reason behind it. Many of the effects of inadequate data remain hidden. When you miss a critical opportunity with a prospect because of erroneous data, they don’t typically email you back to tell you what the problem was.
Insufficient data can make marketing campaign optimization very difficult. While you’re busy tweaking your messaging, you miss the fact that the campaign wasn’t landing because of data errors. In addition, insufficient data drags down the conversion rates of movements and can cause you to second-guess messaging strategies that otherwise would have connected with your audience.
Marketing Data Becomes Sales and Customer Success Data
Your marketing team doesn’t just use marketing data. In HubSpot, Salesforce, Intercom, and other platforms, the same data that your marketing team uses eventually become the data that your sales and customer success teams use too. Unfortunately, that means that they also inherit all of the insufficient data stored in those customer records.
Your sales team will have difficulty appealing to prospects when they don’t have accurate data on hand. However, if they do become customers, your customer success team will too.
Ultimately, your marketing data reverberates throughout your organization, hampering the ROI of each department as it makes its way through. Having data quality initiatives in place will help you limit insufficient data on your organization.