Your customer data is the key to sales success. It’s how you get in touch with prospective clients, keep existing customers coming back for repeat purchases, and ensure you’re sending out personalised emails, offers and communications. It’s crucial, therefore, to include customer data cleansing as part of your sales process.
What is data cleaning?
Data cleaning is the process of identifying and updating or removing incorrect data from your records. This could be duplicate data, information that’s been incorrectly entered into a form by a customer, irrelevant data, or incorrectly formatted data – any of these constitute ‘bad data’ and should be cleaned up as a matter of course.
Why is it important?
A study carried out by Experianfound that 30% of companies hold inaccurate data about their customers, and one-fifth of the 1,000 employees surveyed believed that more than half of their customer data was incorrect.
Why is that an issue?
Ensuring you have clean data helps everyone in your business from your customer service to sales teams. The benefits include:
- No errors where multiple data sources are used
- Reduce employee frustration and dissatisfaction
- Use contact data for the purpose it’s been collected, to get in touch with customers and prospective clients
- Improve business processes and streamline sales and marketing
- Understand where the data includes errors so you can fix or minimise them in the future
How does data become bad?
We briefly touched on bad data, but let’s look at this in more detail.
Outdated data
Data you’ve gathered from customers, through contact forms or other research, could simply become outdated over time. It’s common for things like phone numbers and email addresses to change – in fact, 40% of people change their email address at least once every two years, and 18% of phone numbers are changed every year. That means you could quickly end up with over half of the information on your customer data platform being incorrect.
Duplicate data
If someone signs up for your email newsletter and then downloads a whitepaper at a later date, you could end up with them on your CRM system twice – perhaps with two different email addresses.
Incorrect customer input
Sometimes, customers will add the wrong phone number or accidentally spell their name incorrectly. It might not be your mistake, but when you carefully craft email marketing campaigns that get everything right apart from their name, it’s your business that will look unprofessional.
Poor formatting
In some cities, it’s conventional to write the building number first, then the apartment number, whilst in other locations, it’s the norm to do it the other way around. If you’re relying on manual data entry and data management, this inconsistent formatting could lead to bad data.
Missing data
If any information is missing, from a client’s name to their job title, that could also be considered bad data.
What’s the impact of bad data?
It doesn’t matter whether your customer data is incorrect due to user error or the passage of time – it still has an impact on your bottom line. Gartner found that the average financial impact of poor data quality on organisations was $15 million per year. That figure alone should be enough to make a business case for a clean-up of your CRM system.
As well as this, by cleaning up your contact records, you can expect:
- Improved customer satisfaction
- Improved employee efficiency
- Increased brand perception
- Compliance with data rules and regulations
- Improved conversions
- More efficient marketing campaigns
When it comes to CRM systems, 86% of companies believe that it’s either important or very important to achieving their revenue objectives, but half of all state that the quality of the data in the CRM is either “very poor” or are neutral about it. If you fall into that 50%, it’s time to cleanse your customer data.
Data cleansing process best practice
Ready to make the most of your CRM? Here’s how to clean up customer data.
Identify what the data is used for
When you understand what data you need to collect from customers, and how it’s used, you can get a good idea of where you need to start the cleansing process, and what data you need to collect in the future. Consider:
- Do you need the full names and addresses of your customers?
- Do you have telephone numbers?
- Do you have up-to-date email addresses?
- What is the absolute minimum information you need?
- Who needs to use the data?
- Do the sales and customer service teams need to collect different data?
Conduct an audit
Start by exporting all the data you currently hold and look for duplicates and missing data. It should be easy to spot any omissions, and when you go through the data with a fine-tooth comb, you should also quickly see whether there are any data errors.
Remove any duplicates from your data – you don’t want to send two or three of the same email to a customer, which can look spammy and unprofessional. You should be able to set up your CRM to block duplicates in the future to avoid this manual process in the future.
Once you’ve dealt with the missing data, see what missing information you can find online. Job titles can easily be found on LinkedIn, and if you’re missing email addresses, physical business addresses and phone numbers, you may be able to find these on company websites.
Archive old data
As you work through your data, you may notice that you have older data that you don’t use currently. Keep your CRM clean and healthy by archiving this data in a safe place for potential future use, helping to speed things up when your team is searching for data in the future.
Outsource it
If that all sounds like too much work, you can outsource your data cleansing process to a specialist company. Many companies offer this as a service, meaning your team doesn’t have to spend time on manual data clean up and can instead focus on closing deals or answering customer service queries.
Use a tool
You might also choose to use a third-party tool that integrates with your CRM to cleanse your customer data. There are many on the market, both free and paid-for, that will help you keep on top of data management.
Ongoing cleanup strategy
Once you’ve started cleaning up the data – or engaged a third party to do it for you – keep it in good health going forward by assigning each team a section of data to be responsible for. You could, for example, ask sales teams to keep all client job titles up to date, whilst your telemarketing team could be responsible for phone numbers.
Avoid silos
This approach to data management should also help to avoid silos between sales and customer service teams if you can centralise your customer data across departments. Rather than each team having separate customer data lists, keep everything in one place.