How dirty is your data?

Whether you care to admit it or not, your marketing database is riddled with old and useless data. You should be worried. Data decay is costing you money. Your direct marketing activities won’t generate sales if your database is littered with inaccurate information.

Data decay happens faster than you think. Try this simple exercise. Ask a room of business people to mark every word or number on their business card that’s changed in the last 12 months. New employees should highlight the entire card as all of their data changed the day they started. You’ll be alarmed by the number of changes that have occurred. A similar study was carried out in 2002 by John Coe, President & Founder The Sales & Marketing Institute. The results were staggering. An incredible “70.8 per cent had one or more changes in a 12-month period”.

The changes were broken down as follows:

  • 65.8 per cent title/job function change
  • 42.9 per cent phone number change
  • 41.9 per cent address change
  • 37.3 per cent e-mail address change
  • 34.2 per cent company name change
  • 3.8 per cent name change.

Other studies reveal business data decaying at more than three times the rate of consumer data, with an average annual decay rate of 35 per cent. This means a typical database becomes largely irrelevant in less than 4 years.

At Outsource, we focus on three common sources of data decay:

Manual data entry – human input error, primarily when adding new data to a contact list, corrupts a surprising number of records. This can be minimised by double processing the data after it’s been entered.  A study analaysing data cleaning quality, where analysts re-checked every correction, 3 per cent of corrections still had errors.

System consolidation – when old systems are combined, phased out, or a merger takes place, database consolidation generally occurs. As the data is merged, overlapping and mismatching data can happen. Some data can simply disappear.

Workforce mobility – workforce mobility is potentially the largest contributor to data decay. The Australian Bureau of Statistics recently found that more than 20 per cent of the nation’s workforce had been with its current employer for less than 12 months.

You can test the decay rate of your business database using a simple exercise:

  1. Export your database into an Excel spreadsheet and sort your contacts by the date they were added.
  2. Divide this list into a series of age groups. E.g. less than 6 months, 6-12 months, 12-18 months, 18-24 months and more than two years old.
  3. Send an email to your newest contacts first and monitor the results. The volume of incorrect fields gives an indication of your database’s natural decay rate.
  4. Send further emails to each consecutively older list one by one, or simply run your decay rate over each date groups until you reach a point where 75 per cent of your records are likely to be dead.
  5. Once you reach 75 per cent data inaccuracy you may want to move anything older into a ‘dead’ file.

If your database or contact list is significantly aged and decayed, there are a number of actions you can take to improve your data hygiene:

  1. Hire an outbound telemarketing firm: Using a telemarketing firm to cleanse your data can be expensive. However this approach can quickly improve a contact list and pays for itself as future direct marketing campaigns deliver a higher success rate.
  2. Returned mail: Use returned lists as decayed data records. Treat each record differently based on the reason for delivery failure. For example, a change of address should be treated differently to people who’ve left the company. You can often refresh these records by calling or using simple Google and LinkedIn searches.

While data decay is inevitable, you should constantly test your business data’s cleanliness and ensure effective cleansing methods are employed. The success of your B2B direct marketing rests on your ability to maintain a hygienic and up-to-date database. If you’re unsure where to start, Outsource can help develop the right strategy for your company.

One thought on “How dirty is your data?

  1. You make some great points. I have seen this happen in my previous employment, particularly as our unit had a high turnover of staff, and coupled with system changes it was easy for data to be lost or misinformation to be entered. We implemented regular maintenance and checks to ensure data was as accurate and relevant as possible.

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