List management: 4 steps to keep your data clean

Okay, hands up, how many of you really work your data and keep it clean? For many marketers, there are just too many things to do and this is always left at the bottom of the list. Once that campaign has gone out, you’re on to the next one, but good practice with list management can make a big difference to your email results.

As an agency, we get to look behind the scenes at how marketers set up their marketing automation platforms and how they manage their data. More often than not, lists are left languishing and the filing structure and naming conventions aren’t the best – making managing the lists difficult. So what would be best practice and how should you structure your list data?

1) Think about your sources

First off, there are two ways to acquire data. You either buy it, or you generate it yourself through campaigns or website sign ups. Either way, these are your two main pots that should be kept separate, as one set is warm (self-generated data) and the other is cold (bought data) – so they’ll perform differently. Keep all the sources separate as well, so you can manage them easily later.

2) Work them demographically

Within these posts, I’d suggest segmenting them demographically. How you segment will depend on who you’re targeting and how you split your messages to meet their needs. For example, I wouldn’t want to send the same message to an IT director as I would to IT manager – they have different needs so it makes sense split them into different pots.

For some businesses, you may also want to go further and split them geographically too, or by any other field within the database. For many of my clients, they have rich data, and so segment based on the technology the contact has – tailoring the message depending on the specific points of difference.

I don’t want to dwell too much on data segmentation in this post as we covered it over here. That said, well organised lists that have a basic segmentation applied is a great start to quickly delivering better results.

3) Keeping lists clean through campaigns

Most email dispatch systems and marketing automation platforms are smart enough to manage hard bounces and unsubscribes. This kind of housekeeping is a must, but what about non-responders? When do you filter those out and how should you manage them?

For us, we use common sense, but first we work the data.

Any email campaign should have systematic processes that work the data hard. With our campaigns, we take the following steps:

  • A/B split test on subject line and then roll out the winning line
  • Send appropriate messages to relevant segments
  • Resend to those that don’t open (3 days later)
  • Resend to second set of non-openers (3 days later)

We know that we can get the maximum result from this route. It’s best practice and fairly commonplace across most of the campaigns we see.

4) Quarterly data refresh

What we don’t see often enough are ‘flushes’ where all non-responders over a given period are given a killer message in an attempt to encourage an open. If there are still non-openers, we move them into a non-responders bucket and pop them on a monthly ‘keep in touch’ campaign. Three or six months later, we’ll try them again with some killer content. Usually, we get a little flurry, and the contacts move back on to the regular, sales or value orientated messages.

Persistent non-openers are given the heave-ho after a given period, depending on the product, service or campaign. Sometimes, this is one year, sometimes longer.

By taking them out of the main pot though, we can monitor the performance of them and know what kind of campaigns activate the data. Likewise, if contacts go quiet after a period of engagement they go into a reactivation programme – all depending on the particular product, service or campaign.

We’re constantly gathering data, monitoring performance and seeking to improve the results. And by taking a systematic, planned approach to driving email marketing campaigns, the results are better.

How do you handle your list management? Tweet me @N1colaRay and let me know.

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