Prospect Pools: Annette Holmes looks at the issues

There are people who claim that prospect pools don’t offer good value. But is it the way they are used which is causing the negative comments, not the content of the pools themselves? Annette Holmes looks at the issues.

There is no doubt that data pools are a great idea. Having a universe of data from which you can select targets for your next campaign is logical and effective. Up to a point. However, many users are locked into price per thousand deals, and this leads to a way of thinking which sees the data as a commodity to be expended, and doesn’t naturally lead us to look at the quality. To really gain value from pools, we need to stop thinking volume and address this quality issue – and we also need to address the issue of quality in terms of accuracy or relevance/appropriateness of the targeting.

There is no doubt that the idea of data owners sharing their transactional information has created new ways to access leads. Some might question just how fresh some of the data in some data pools might be – and point to the reluctance to reveal original data sources as a means of covering up poor quality data lurking in the depths. It is a further issue, and one which the data industry has to address, but I would assert that it’s the way the data is analysed which could be driving the perception that there is something murky going on with pooled data.

All too often, people start with the request for a set number of names, but that isn’t the right ‘first question’. The first question should be based around the business requirement. If the need is simply to obtain 20,000 new names for an acquisition campaign, is it any surprise that in the short term response rates are falling off? By using a pool as little more than a source of names, is it any surprise that they are not seen by many to be delivering on their promises? They should be analysed - fished carefully and selectively, not merely trawled with a big net.

As an industry we are fortunate to have a range of highly effective analytical tools – and we are now seeing a new generation of analysts who have the commercial as well as the analytical skills to see how these can be used more profitably. But as long as we go on seeing data as a commodity, we will miss the real advantages to be had in weighing up its value – and then unlocking that value. Those who recognise this know that contacting the right 10,000 people can be more profitable than hitting 20,000 – but as long as the commodity mindset rules, data providers will find it hard to argue for quality – and (this is the critical bit) be able to prove that it’s worth paying for.