5 Steps to a clean contact database

The problem

Two and half percent of all first class mail is returned.

Twenty percent of emails in your database could be wrong.

Five percent of phone numbers in your records are no longer applicable.


Root Causes

There are a number of factors driving higher costs. The most important of these are poor quality address and the challenges of accurate data capture; and of course database decay resulting from people moving.

The factors compound other problems such as handling, re-mailing and extended cycle time.

Poor Quality of Data

Alas it’s human nature to make mistakes. When customers or staff are tasked with providing their address information on physical or web based forms, it is inevitable that some mistakes will be made and incorrect data entered.

On a recent event I was involved in at the NEC in Birmingham, I was provided with the data of people that had attended the show, to provide follow up emails to the visitors to thank them for their attendance. The data was of course imputed by the visitors themselves, either on the day as they made their entrance, or in advance with the advance sign up facility. 23% of the information provided was incorrect.

Taking into account the fact that this data was extremely fresh and had little to no decay over time, we are already experiencing nearly a quarter of the data pool being incorrect.

Companies on the whole have also adopted a questionable practice of sending emails and or conventional mail correspondence to a first time customer and or contact, regardless of whether or not the address is known to be wrong. This practice will result in bounced emails or return mail and undoubtedly leads not only to increase in revenue, but also loss of sales.

Natural Database Decay

Personnel changes within businesses vary, not only by company, but also by sector. However, an average across the UK can be between 12-17% per annum. If you are trying to engage with a person within a business, a sixth of your contacts could have changed position or company in a 12 month period. Take into account this doesn’t even include the number of businesses which have ceased trading or been involved in a merger.

It is widely recognised that over two thirds of these changes will not inform their client base.


A Case Study Worth Considering…

I could have used a case study of a business that lost millions of pounds due to bad data, but I thought I would use an example that everyone could get to grips with.

A business sends out its brochure to its client base twice a year. Its brochure is glossy and full of all their products and no doubt brings them in great orders. However, the brochure isn’t cheap. It costs the business nearly £5 each by the time it’s been produced and posted out.

It sends its brochure out to 8000 people that it has met or engaged with  in the last 12 months. In depth database analysis showed that 20% of the data was incorrect in the first place from when it was imputed. 15% of the people they were trying to contact no longer worked with the businesses they were trying to engage with. 10% of the businesses had closed or gone into receivership in the last 12 months.

In short… close to 40% of the people at the various businesses they wanted to send brochures too were never going to see the brochure. Extrapolate this out further and you’ll see that the business was about to spend £16,000 they could and should have spent elsewhere.


Where to begin solving the problem

It can seem very doom and gloom, but it needn’t be that way. The reality is that the figures above are completely natural and affect all businesses, your competition as much as you.

The difference between what you do to manage it and what your competitors aren’t doing, is what will define your business and how successful you are?

A data cleanse and validation scheme will take your database and bring it as up to date. It has the opportunity to review address, update employee records, verify email address to ensure that your marketing activity is getting to the people that you need it to.

5 Simple Steps

1 – When you source data, ensure that it is as accurate as possible.

2 – Whenever you interact with a client or customer, always take a minute to double check their records on your database.

3 – Endeavour to have your client pool or database cleansed every 6-12 months.

4 – Don’t accept ‘sales@ or info@’ – If someone wishes to engage with your business, get their proper email.

5 – If you have an employee leave or change within the business, let your customers know. If we all do it to each other, everyone will have a much better pool of data to work with and everyone will benefit from the savings of bad data.

Daniel McHugh

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