Data Cleaning Is It a Cost or Investment?
We don’t do any Data Cleaning, because it costs. This is one of the main reasons I hear why companies don’t invest in data cleaning.
Well, let me ask you…
- How many negative media reviews would I get if I sent a marketing letter to a dead person?
- What if you had to contact a customer, but didn’t have their correct telephone number?
- How much would it cost for a replacement item to be sent to the correct address, if the original went to an old address?
Any one of these issues would be a severe detriment to your business, and not just financially! Now tell me cleaning is it a cost or investment!!
What is Data Cleaning?
Data cleaning is the verification of accurate data, plus the identification and rectification of inaccurate data from a contact database.
According to industry research, an average of 35% – 40% of data deteriorates every year. People move home or job, companies move address, people die and companies close. Given this information, it’s clear to see how quickly a database might deteriorate. In this fast-moving world of competition, it’s increasingly important to keep up your data cleaning routine.
Reasons why you should keep your data clean
To save money – inaccurate data can cost you in many ways, including wasted phone calls, mailshots and emails, not to mention time costs!
To make money – accurate data can win you business through promotions, marketing etc. These avenues would be severely impaired using inaccurate data. Clean data is the single-most important element of any direct marketing campaign’s ability of generating Return on Investment
Customer Satisfaction – it’s a dog eat dog world out there with customer service being the only differentiator between companies in many industries. We all know that bad reviews travel faster than good. If you get a client’s name wrong, how quickly do you think the world would know about it?
It’s the Law – Current legislation requires you as a company to retain clean, accurate customer records. This legislation will only tighten when GDPR is adopted fully in the UK come May 2018. The fines for non-compliance are eye-watering!
You Do The Maths
Data Cleaning need not be an expensive exercise and in many cases, when compared to the alternative – working with unclean data – avoiding the perceived “cost” of Data Cleaning is counter-productive and, in some cases, nigh on insanity. Put into simple terms, Data Cleaning is an investment, not a cost. Let me give you an example, using a not uncommon percentage of 50% inaccuracies:
Scenario 1 – A company has a budget of £1,000 and for that budget, sends a mailshot to its “uncleansed” database of 1,000 customers. Of those 1,000 customers, 500 receive the mailshot and 500 are returned “Gone Away”. Of the 500 received, 5% take up the offer – 25 customers. They spend an average of £100 each with the company, bringing in revenue of £2,500. After deducting costs, the profit is £1,500 and the company has a database of 500 good, clean records to continue marketing to.
Scenario 2 – With the same budget of £1,000, the company first spends £250 on a Data Cleaning exercise. After cleaning, it has 750 “Good” records to send its mailshot to (370 records were already good, 380 more have been updated with correct information, but 250 businesses have closed or can’t be matched etc). It sends 750 mailings (for £750) and all are received, with 5% taking up the offer – 38 customers. They spend an average of £100 each with the company, bringing in revenue of £3,800. After deducting costs, the profit is £2,800 and they have a database of 750 good, clean records to continue marketing to.
It’s clear that investing part of the total budget on Data Cleaning results in a much improved Return on Investment, not only in financial terms, but also in the fact that a larger clean database is held for future marketing efforts. This will, in turn, deliver improved future financial returns. So, if you’re labouring under the misapprehension that your unclean data “will do the job”, you’re missing a trick!
This example only becomes more stark when an older database is in question. An inaccuracy rate of 50% is not uncommon for a database just two years old. So if yours is older still, you need to think long and hard.
Other Reasons for Data Cleaning
Data cleaning can benefit your business in other ways, too:
- You will likely make fewer errors
- Your customers’ experience will be improved
- Due to 2), the chances of repeat business are greatly improved (Remember – people are more likely to share a bad experience than a good – and that’s a fact!)
So tell me again that data cleaning is too expensive.
Contact us now to find out about how you could be entitled to a FREE data audit call us on 01274 965411 or email firstname.lastname@example.org