List quality – is the devil in the detail?
Will the data I source for my campaign be accurate and up to date?
The complexities of data update strategies should certainly be considered when reviewing database quality, as this will impact your contact rates.
Data decay will impact data sets at different rates, as external factors determine how each audience will change over time. For example:
- B2B databases are likely to have a slower rate of decay for CEOs than for IT decision makers, as CEOs are less likely to frequently move to new companies
- Younger people that rent their homes are likely to be more transient than older people who own their homes, so the proportion of decay would expected to be higher in a list targeting younger people / renters
For direct mail campaigns, ask your data supplier if there is a deliverability guarantee, based on the % of return mail you will receive. Don’t forget that the number of undeliverable communications is likely to be higher than this, as not everybody goes to the trouble of returning mail.
For telephone campaigns, ask if there is a guarantee in terms of the number of wrong / disconnected numbers. Wrong numbers will have the potential for a knock-on effect also, as they can lower caller morale.
It is worth noting, however, that a guarantee is normally simply an offer to credit back data in addition to a set ratio of data that is estimated to be incorrect. It is not necessarily an indication of actual data quality.
When reviewing a list, it is imperative not to get caught up too much on deliverability. As a glass half-full approach should be taken when considering list quality.
The successful marketer will primarily consider the conversion ratio of the campaign, rather than the number of incorrect / returned records. Therefore, management of expectations with marketing stakeholders and calling agents is highly advisable.
