When to stop flogging a dead horse

There’s a strong tendency when planning a data selection for a forthcoming campaign or programme to pull as much as possible in order to maximise the reach of the activity and corresponding response. This is nearly always self-defeating however, and not least when it comes to using every record meeting your selection criteria, regardless of how long ago it was collected or when any kind of response was last received. Even if such data is not obviously out of date, there are many reasons to exclude it from ongoing activity.

Although this is likely to be an issue restricted to email activity rather than relatively more expense direct mail, it’s still applicable to both. The greater cost involved with DM creates a natural incentive to fine-tuning selections ahead of launching a campaign. Even so, it’s extraordinary how poorly targeted such activity can often still be, with the obvious parameter of data age not taken into account.

The seemingly next-to-nothing cost of email though makes it easy to think that that there is no impact to using all available data, but as we all know (albeit don’t necessarily acknowledge) this is not the case. Diligent email marketers will of course remove bounced email addresses from their lists in order to maintain a clean database and eliminate records known to be no longer active (although not always, see Email bounces and database updates). And it goes without saying that opt-outs and unsubscribes must be removed in order to maintain privacy compliancy. Other than that, if you’ve got a usable record, use it, right?

Well, an obvious effect of taking this approach is to actually diminish your percentage open rates, since the opens that you do achieve will be diluted by all those disengaged recipients. Now you might be thinking that this is just damned lies and statistics, since the overall number of opens isn’t changed by the total number of recipients. If you’re monitoring these metrics however, they will be giving you a false, and unnecessarily pessimistic, impression. It will be much harder to achieve improvements due to the dead weight of of those recipients who are never going to look at what you send them.

Continuing to market to an artificially inflated list also obscures the number of people you’re actually reaching. The absolute open and click rates are crucial of course, but continuing to hope that non-responsive recipients will at some point come to life again may mask deeper issues with your database. Perhaps you should be looking for fresh subscribers or prospects via external data acquisition or increased social media activity to encourage opt-in. (Don’t just rush out and rent a list though – see the point on Data acquisition in my recent post How to take advantage of a recovery.)

How then should you go about honing your list selection when preparing a new campaign? Well obviously it goes without saying that your activity should be carefully targeted at individuals meeting relevant criteria across role, industry, interest, behaviour and so. A quick and easy way to eliminate the unresponsive element of your database however is to apply a filter I and others often refer to as “recency” (accepting this is a made-up word!). This is by no means rocket science, but takes a little discipline and good data management. Put simply, those individuals in your database that have not responded or interacted in any way for a defined period of time, usually 2-3 years, should be excluded from activity going forwards. Even if their email address is still in use they’re simply never going to respond and are just skewing your results as discussed. The minuscule possibility that they will respond in the future is just not worth the negative impact of continuing to include these recipients in your activity.

The trick here of course is the ability to effectively determine who these non-responders are. You will need the outcomes of your email and other direct activity to be fed back to your database in order to readily make a selection based on these criteria. As well as email opens and clicks, you should also take into account website log-in if applicable, event attendance, purchase (obviously) and any other behaviour you can identify and track. Increasingly, this might include social media activity, such as Twitter or Facebook. It’s quite possible that lack of actual response to email doesn’t mean lack of interest, but you need to demonstrate this, not just make an assumption. The ability to make this part of your selection criteria clearly needs to be a “production” capability, built-in to your marketing operations, and not a hugely labour intensive task for every campaign execution.

It’s worth noting also that the lack of response to marketing activity could itself be used as a trigger for some other kind of follow-up, particularly for high value contacts. If a past customer or senior-level prospect has stopped responding, a quick call using a low-cost resource (i.e. not an expensive Inside Sales rep) to check their status could be worthwhile. Maybe the contact has left and been replaced, changed roles or allowed your company to fall off their radar. You might be able to re-engage, but if not, move on.

Recency should be a field in your database that is constantly calculated based on all the criteria outlined above, which can be readily included in a selection. Just to make the point, this is completely different from “last edit date”, which can often be set when a record in a database is merely viewed, regardless of whether a real change was made or activity performed by the contact. Implementing this simple addition to your campaign selection will have an instant, positive effect on your marketing metrics and save you from flogging dead horses.

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