How to clean your customer database
Are you experiencing an increase in mis-deliveries and returns respectively from your direct mail campaigns to customers and when distributing products to them? Are you noticing gaps in your customer data, such as missing phone number, email and postal address data? Are you seeing an increase in duplication of customer records? And have colleagues mentioned they have lost trust in the organisation’s customer data?
If your answer is yes to any of these questions, it’s time to clean your database.
Why clean customer data is important
Poor quality data leads to mis-deliveries and returns which can significantly increase costs for brands, and have a negative impact on the customer experience and therefore customer retention. Also, incorrect data, gaps in contact data and duplication of customer records prevent a clear view on your customers and therefore obtaining valuable insight that can be used for sales, marketing and business intelligence, to drive long-term business growth.
Losing customers because of poor data is a big issue for any ambitious brand, when it costs around five times more to acquire a new customer than retain an existing one. Whereas, increasing customer retention by 5% can increase profits by 25-95% and the success rate of selling to existing customers is 60%-70%, compared with 5%-20% for new customers.
Four steps to deliver a clean customer database
Step 1: cleanse and standardise data
Without constant attention the quality of data in a customer database will decline. After all, customer data degrades at 2% per month, with 25% of data being corrupted on an annual basis as customer contact details change with home moves, new mobile phone numbers, etc.
Furthermore, the growing reliance of brands on customer provided data in the mobile age is leading to an increase in collecting inaccurate customer data at the onboarding stage. Customers typing in their contact information on a small screen are much more likely to mistype.
Call centres make mistakes too when inputting customer details. So it’s perhaps not surprising that approximately 20 per cent of addresses entered online contain errors such as spelling mistakes, wrong house numbers, and inaccurate postcodes.
To rectify the issue of poor customer data it’s critical to source data cleansing and standardisation services that can efficiently deliver data quality in batch, in real-time. Ideally one that’s scalable, can integrate with your CRM platform, and can cleanse, correct and format UK as well as global name, address, email and phone numbers.
Step 2: deduplicate data
In our experience, a database will contain almost 10% duplicate records, which results in inefficiencies and prevents achieving that single customer view.
The issue is changing customer names and addresses can sometimes lead to duplication of details on a database. And if you merge additional data on your customers into your database from third-party sources, this can exacerbate the problem.
What’s required to deliver effective deduplication is a powerful and accurate matching and deduplication solution with deep domain knowledge of international address formats and advanced fuzzy matching that can merge / purge the most difficult to spot duplicate records.
Step 3: data verification
Verifying data – such as name and address - is a critical step in making sure customer data is clean, up to date and ready for use.
For maximum efficiency and best value source a data verification solution that corrects, cleans, standardises and adds missing components to a customer record related to their name, address, email and phone number.
Ideally, any data verification service sourced should also have the functionality to be used during the customer onboarding process – to ensure the data is correct and verified from the moment it’s collected. It’s also a much more cost-effective use of the service and helps prevent cross-contamination from new data inputs into your newly cleansed database.
One verification tool that’s particularly important at the customer onboarding stage is address autocomplete. Such a service will automatically reveal a suggested correct version of the address as the customer completes an online contact form, enabling them to select one that’s not only accurate but easily recognised. Another benefit of autocomplete is that as well as preventing mistakes caused by fat finger syndrome, it reduces the number of keystrokes required when typing an address by up to 70 per cent. This speeds up checkout and reduces shopping cart abandonment.
Furthermore, on the addressing side, make sure the verification service can format the address to relevant postal authority specifications around the world. This will reduce expensive mis-deliveries and returns.
Ideally, the address verification service should also be able to enrich your data by adding latitude and longitude coordinates to any address to aid effective delivery scheduling and logistics - helping to cut costs. For example, using this information it’s possible to calculate the customer’s distance from distribution points, enabling a real-time calculation of shipping costs; and allows retailers to present a number of price levels depending on how fast the customer wants delivery. Furthermore, such insight can power sales and marketing efforts such as sales clustering.
Any phone verification service should be able to carry out registered user checks, validate phone numbers and ensure they are live and callable, in real-time. For sales and customer service reasons it should establish the international format of a number making it easier to determine the dominant language in that area. While an email verification service, along with correcting and standardising email addresses, should be able to validate the actual mailbox in real-time. This ensures confidence in email deliverability, while protecting brands from spam traps.
Step 4: enrich data
Once your data has been cleansed and verified it’s time to enhance it to truly understand your customers; to enable better targeting and the delivery of more effective communications, increasing response rates and sales.
This could include using a demographic solution that defines the unique attributes of your best customer, to help predict likely future buying behaviour and identify prospects most like your best customer.
Protect your customer data from decay and fill in the gaps
It’s vital to protect your customer data from decay and fill in any gaps to ensure it’s always accurate, up to date and therefore delivers maximum value for your organisation. This means have a strategy in place that successfully allows you to deliver a data quality life cycle, so that you continuously maximise your CRM efforts.
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Barley Laing joined Melissa in 2014 during an exciting expansion phase of the California headquartered company.
As UK Managing Director with 15 years of data industry experience, his role is focused on meeting the data quality and compliance needs for organisations in the UK and worldwide.
The team that Barley heads at Melissa’s...