Blog posts tagged data jargon

Cutting through the data jargon (part two)

Onwards with the mission to give you the heads-up and the low-down on baffling data jargon. In part two, I am focusing on spring cleaning and ensuring your data is spic and span and up-to-date. It is that time of year after all.

Tele-verification

I will start off with an easy one. A data record that has been tele-verified has been called up and the details double-checked by a call centre agent. So you know that the telephone number, address details and contact name have had their t’s crossed and i’s dotted.

Data recency

As the name suggests, data recency refers to how recently a record has been checked. So a data file that has 24-month recency was gathered or tele-verified two years ago. A file with 12-month recency was gathered or verified 12 months ago and so on. The shorter the recency, the more likely the contact details are to be accurate. Recency is especially important in business data, due to the regularity of staff changes – think about it; you are more likely to change your job than your house.

De-dupe

“What is a de-dupe?” It’s a very common question. A de-dupe deletes duplicate records. So if you have multiple records for one customer, a de-dupe will remove the duplicates. This makes sure that you are not mailing, emailing or telephoning the same company twice, which can be embarrassing and costly.

The other useful reason for a de-dupe is to make sure you are not buying data you already have. So when you are buying new data records, you should de-dupe against your existing customer and prospect data. That way you are only buying net data, i.e. data you don’t already have in your marketing database.  Again saving you time and money.

Data audits

A bit like a financial audit, a data audit will tell you what state of repair your marketing database is in. The audit identifies any dodgy records such as wrong contact names or wrong address details. It will flag any records that are on the suppression files such as TPS or MPS. It will highlight companies that have moved or that no longer exist. The audit report will also tell you what you need to do to get your data back into tiptop condition. And more importantly how much it will cost.

Data cleansing or cleaning

Once you have identified the problems with your data with an audit, a data cleanse will put it right. Think of a data cleanse as a spring clean. All the incorrect details will be updated and the dodgy records removed. Therefore you won’t be wasting time and effort trying to market to them. Happy days.

 

John Keating is an expert contributor to Marketing Donut and director at Databroker.

Read Cutting through the data jargon (part one).

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