STO is wonderful – but have you done your STT? (Send Time Testing)

Lister Digital

Jul-14, 2016

Campaign Send Time Optimization does produce remarkable results. MSPs today claim to have an innate feature of exploiting typical customer open/click timings to schedule critical promotional programs. While some look at a brand specific campaign events, other MSPs use the learnings across the plethora of brands using their platform and offer an aggregated, verticalized campaign scheduling out of the box. For example, banking and financial services customers in a particular demography and even political affiliation, tend to have a higher mode of email opens between 8 and 10 AM on weekends and between 6 and 7 AM on weekdays. Simple, yet an amazing feature that can drive CTRs big time.

But most of these features are post facto – they analyze, slice and dice optimal open click through timings based on Customer email behaviour.

What doesn't seem too right about this process is that

  1. There's no testing –The web optimization guys got it right – Test & Target.
  2. There is no accounting for seasonal fluctuations of opens and clicks.

Here's a list of the top grand Slam singles players of all time. Well Roger is No.1 and that's a no brainer. I don't see Becker anywhere in this list- in fact he hasn't completed a grand slam – The French Open and RG has always negated his style.

Anyway, are your customers grand slammers or are they pure grass court demons –like Becker? Well, you don't really know unless they have played in each tournament. Here's my point, Look at a simple four zone split - Morning, Afternoon, Evening and Night, across which customers are categorized. STO provides a neat output like the following after analysing the open and click times across all customers.

Makes sense right? But look at the columns with 0% on it. How are you so sure John has been equally targeted across Morning, Afternoon, Evening and Night for you to make a decision that the ideal open time is Morning? John has received 20 campaigns in all – 16 at night time, he has opened three and just four campaigns in the morning zone - he has opened two out of those.

The interesting questions that pop up are,

  1. How are we so confident that Morning emails work for John?
  2. How do we automate the process of testing for the right slot without bombarding John with emails?
  3. How can we systematically test John's responses equally across zones so that we understand his preferences?
  4. How can we shorten this prediction cycle and get to the optimized zone as quickly as possible?
  5. John is a runner and gets outdoors during summer pretty early – catches up with emails quite early in the morning. During winter he seldom opens emails before evening. How do we keep up with these behavioural changes?

We'll get you answers in the next post!

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