Data, whether bought or organic, needs to be clean in order to represent any kind of value to a business. Clean data should be considered one of the most important assets your company has, but as data changes so quickly it can be a never-ending battle of regular cleansing.

Consider this alone, every year in the UK around 11% of the population move house, and over 600,000 people pass away. So how can we possibly ensure our data is up-to-date and clean as a whistle?

In this blog we look at the industries leading the way in utilising clean data and how we can follow their example.


Clean data is of the utmost importance to the automotive industry, particularly when it comes to insuring the petrolhead’s most prized possession.

When underwriting car insurance, the data we provide directly influences the premium we pay, with tools such as geocoding even going so far as to reduce our premiums based on our geographic location. Mandatory reporting of certain key data has allowed insurers to reduce the risk of miscalculating premiums.

Clean data doesn’t just extend to the drivers, but the vehicles also. With over 20,000 cars changing hands in the UK each year, it is vital that the database contains only accurate data on each vehicle, including age, mileage, service history and more in order to prevent fraud. The automotive industry has perfected the art of data cleansing to increase response rates, support compliance with their own regulations and ensure the data (and premiums) are correct.

If your business relies on the accuracy of certain key data, make capturing this mandatory and ensure the processes are in place that mean this is recorded accurately, every time.


How many individual components does it take to create a hoover? Or a new office building?

When it comes to ordering components, materials or parts, it is vital that the manufacturing industry has accurate data on unit price, shipping times, safety data, and technological capability.

The manufacturing industry depends heavily on the application of big data and the use of algorithms to guide the decision-making process, and in order for this to be reliable and accurate, the data must be clean. Choosing the best supplier or the best materials depends on interpretation of data and accurate analysis.

Learn from the manufacturing industry by analysing the data you have on your suppliers, and maintaining real-time information to ensure you make the best decision for your business.


Imagine if your recent purchase was shipped to the wrong address because the company didn’t have up-to-date information on you. What a pain!

Even the most successful of retailers can lose a customer’s trust or repeat business through late (or failed) deliveries. Retailers have learnt how to avoid this issue by validating and standardising address data in real time, ensuring that only clean, accurate data enters their system, whilst also helping combat fraud by matching the address with the customer’s name before processing a credit transaction.

Accuracy of data is vital not only in reducing costs lost due to failed deliveries, but also improves customer satisfaction, increases brand loyalty and secures that all-important repeat business.

Address your own deliverability issues by standardising your address templates, adding in real-time verification or including a validation page for your customers.


Much like car insurance companies, the utility industry is reliant on accuracy of data which used to involve door-to-door manual readings of your meters (remember the days of answering your door in your towel, still dripping from the shower as the meter man made an unexpected visit?).

Now, with residential smart metering and online submission forms, real-time communication of consumption has allowed for more accurate usage statistics, helping produce better product bundles and improved pricing models.

A final thought

Could clean data improve your company operations? Probably! If you could ensure the data you received was clean, chances are your operations would be swifter, simpler, and provide a better customer experience and service. Make sure that you are utilising the analytics from your clean data to improve your customer service.

Each industry has utilised clean data in a different way, but they all have the same end goal, improved services for a better customer experience. Implementing a solid data cleansing strategy will reduce your costs from failed deliveries, increase your response rate and return on investments, and protect your brand image through a positive customer experience. Not only that, but for those of us in marketing, it is in accordance with the Direct Marketing Association’s Best Practice Guidelines that we ensure the data we use is clean.