Why Your Email Marketing Program Is Like A Dead Badger?

Driving home last night, I saw a dead badger on the roadside, and I started ruminating on similarities between dead badgers and email marketing programs ! Not so much from the perspective of being a bit flat, somewhat run down, or showing the first signs of decay ( although all of those are potentially applicable ). Rather, that badgers are notoriously shy, so to be able to estimate their population size, a simple rule of thumb is to take the number of dead badgers on the roadside, and multiply that number by 10 to arrive at a rough estimate of the number of living badgers in that area. The key point is that an apparently small cause can provide a pointer to a much larger effect, hence my unlikely association between badgers and email marketing.

Consider spam complaints. Provided that they are being monitored ( that’s another point ! ) they will form around 0.1% of a good sender’s broadcast . Such a small number is easy to ignore, but it can point to bigger issues:

  • According to Return Path’s recent Sender Reputation report, 0.1% equates broadly with a sender reputation score of 90+, with the program achieving ISP accepted rates in the high 90% as a result. By comparison, a complaint rate of 0.4% maps roughly onto a score somewhere between 50 and 80. The corresponding accepted rates decline markedly – anywhere between 27% to 88% – as a result.
  • There is also churn to be considered. Let’s say you have an email list of 1M addresses, sending on a weekly basis. That 0.4% complaint rate equates with losing 1/5 of your subscribers over the course of a year, and every single one of them is leaving because they are unhappy with your program.

Unsubscribe requests are a similar case in point. The most recent edition of the DMA’s Email Benchmarking Report shows average opt-out rates for retention campaigns at 1%. As above, that small percentage actually provides the frame for a bigger picture. There are also some additional points to consider :

  • Leading on from my comments about spam complaints – if you aren’t reporting on this metric, and are only using unsubscribes to measure levels of disaffection with your program, then you are under-reporting the true state of affairs by a probable factor of two, and possibly more.
  • Disengagement should also be regarded as a form of opt-out. Your recipients may not physically request their removal, but if they stop responding then they have become “emotionally unsubscribed”. A re-activation program is your first step, but all the non-responders should then be opted out.

Another small number that can conceal bigger issues is bounce rates. The same DMA report shows average bounce rates for retention campaigns as 2%. Using the same example as above, you would lose your entire database in slightly under a year at this rate !

But there is another alarming dimension to this metric – bounce rates for new subscribers are nearly always substantially higher than the average bounce rate for your entire list. For example, if new subscribers form 2.5% of the total broadcast, then an average bounce rate of 2% might easily mask a new subscriber bounce rate of 20%. To counter this, email marketers need to be doing the following :

  • Report separately on the first-broadcast performance of new email addresses.
  • Ensure new registrants have a strong imperative to supply a good address.
  • Validate new addresses using a process such as double entry, or confirmed opt-in.

So – at the risk of mixing my metaphors, my advice is to look between the trees ( the small numbers ) and see all the badgers that are frolicking in the woods ( the larger considerations ). Learn to interpret these metrics, and act quickly on what may at face value appear to be small variances. In this way, you can remain confident that the first whiff of putrefaction really is coming from that poor badger alongside the A5, and not from your slowly decaying email program instead !

This entry was posted in Data Management, Deliverability, Metrics and tagged , , , on by .

About Guy Hanson

Guy has spent more than 20 years working in various aspects of marketing and data management. His current employment with Return Path’s professional services team represents a natural fit - providing response consulting solutions to a broad range of international clients to optimise the performance of their email marketing programmes. Guy is a regular contributor to the EM press and a frequent speaker at major industry events. He has also led the delivery of numerous whitepapers, including the DMA’s Email Marketing Best Practice Guidelines.

  • http://twitter.com/emailupdater Email Updater

    The calculation of bounce rates (the 2% average reported by the DMA) needs some extra explanation. If you continuously bounce 2% on average you will not loose your entire base in a year. For the calculation is made on the mails sent per emailing (not the initial number of email addresses).  

    Also the bounce rate is calculated per emailing, so the bounce rate per emailing will go down if you mail more often (weekly) opposed to less often (monthly).

    • Guy Hanson

      Two good points, and I fully agree that results of the calculations will vary dependent on list size and broadcast frequency. While I was thinking about this post, I came across an interesting piece of research from the guys at MailerMailer which showed that bounce rates vary in accordance with broadcast frequency as follows :

      * Once a day or more – 0.4% bounce rate
      * Few times a week – 0.7%
      * Once a week – 1.0%
      * Few times a month – 1.2%
      * Once a month – 2.2%
      * Less than once a month – 5.1%

      See http://www.mailermailer.com/resources/metrics/2011/bounce-rates.rwp for the full article.

      So absolutely – bounce rates do go down as frequency goes up. However, these key metrics, which are often reported as a fraction of 1%, have a material impact on the success of an email marketing program, and marketers will do well to pay close heed to them.