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Alternative indicators of customer acquisition success: email open rate

Many marketing reports I have reviewed over the years have focused on ‘vanity’ metrics like impressions, likes and views - which look impressive on the surface - but made no mention of profit or return on investment (ROI).

 

In the spirit of challenging assumptions, this is the first in a series looking at whether any of these ‘vanity’ metrics are correlated with or predictive of profitable growth, based on the work we do with our clients to create a single customer view across their various marketing data sources.

 


 

First up in this series is email open rate. We have looked at this in two contexts: in a long sales cycle business (think B2B enterprise software or high value consumer goods) vs conversion to purchase, and in a transactional B2C business vs lifetime value.

 

Example 1 – long sales cycle conversion

 

This example represents a very high value B2C purchase, with a sales cycle of c. 1 year – so I think of it more like a B2B sales process. We see that there is a linear relationship between marketing email open rate (i.e. excluding 1-1 contact with salespeople) and ultimate conversion.


Email oper rate vs conversion

Example 2 – transactional B2C lifetime value

 

In this typical B2C ecommerce example, in a category with a high purchase frequency, the relationship is slightly different – getting email open rate above c.20% correlates with a meaningful increase in customer lifetime value (measured in terms of profit of course). Above this, there is a still a positive relationship but less strong than in our first example.

 

What we have also looked at here is whether there might be covariance with the number of emails received – but when you isolate to just those customers who have received >50 emails, the trend is almost identical.


Email open rate vs lifetime value

How can we use this insight to drive growth?

 

Of course, you may be wondering- is this just correlation or more fundamental causation? In the first example, common sense says that a prospect who is more engaged is more likely to open emails. In the second example, a customer who feels a connection to a brand and its content may well be more likely to open emails.

 

I would make the case that in some ways this does not really matter, because the most valuable way to use this insight is as a correlation, in other words a predictor of prospect conversion or customer lifetime value. This could allow you to prioritise sales resources, direct churn prevention activities or indeed simply to produce a more accurate forecast of business performance.

 

As to whether working on your email strategy can increase the correlated business metric – that is something you should test. With both client examples described above, the next layer of detail suggests the opportunity to make gains – looking at the specific email campaigns, automated journeys, and scope for more A/B testing.

 

One of the best characteristics of email marketing as a Chief Marketing Office (CMO) is that compared to your website, app, or other digital products, you are likely to have full control of A/B testing without the need for your tech team to get involved. Send days, times, subject lines, and email content can all be optimised.

 

If you have the data available, check this comparison to conversion rate and lifetime value for your business. If you do not have this at your fingertips, it is worth the effort to start to tie your different marketing data sources together to create a single view of the customer journey to uncover insights such as this. Next up in this series will be enquiry response time – please do suggest any other indicators you would like to see tested.


If you’d like to discuss how you can join together your marketing data sources to understand these relationships for your business, please Contact Us.


All views expressed in this post are the author's own and should not be relied upon for any reason. Clearly.

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