She loves me. She loves me not… measuring opens and clicks is a good start but you’ll probably want to be a bit more objective when it comes to understanding how engaged your customers really are with you, your email campaigns and your brand..
Traditional email performance metrics give useful campaign-based feedback but to get anything more than a basic understanding of engagement you’ll need to measure a number of different factors and over a prolonged period of time. With the right approach, and the right tools, engagement can not only be measured, but managed and actively exploited.
Why should you care? – It’s good for business. Successful companies look at the initial sale as a way to earning loyal, returning customers. Engagement is a hugely powerful buying factor and loyal customers become brand advocates to friends and colleagues.
Engagement profiling is one of the many ways you can add precision targeting to your email campaigns. Precision targeting uses the concepts of ‘audiences’ and ‘dimensions’ to create dynamic data segmentation and targeting.
Audiences is a way of defining segmented subscriber groups according to specific profile characteristics.
Dimensions are the various ways in which that profiling information can be defined and gathered – engagement is one of them. The engagement dimension allows you to gain a quantifiable measure of the level of interaction your subscribers with your campaigns.
The problem with engagement is that it’s difficult to measure in an objective way. It depends on many different factors, each of which is subjective to a lesser or greater extent. It applies both to individual subscribers and to audience groups, and it’s not static – engagement changes over time.
At Sign-Up.to we use a multi-parameter algorithm which monitors a range of engagement characteristics. It takes into account a broad view of engagement behaviour, including the frequency and depth of interaction with each campaign. It uses a multi-parameter algorithm to automatically capture things like the quantity, frequency and depth of interaction over time and then scores each of your subscribers accordingly. You can then use this engagement to target campaigns like welcome back offers, VIP rewards and loyalty schemes.
And it’s fully automatic – the engagement algorithm continually runs in the background collecting interaction data from each executed campaign. The collected data is processed to create an engagement profile for each subscriber – we call it their engagement rating.
Based on their history of interaction each subscriber is attributed with an individual engagement rating, from 1-start (typically disengaged) to 5-star (highly engaged).
How it works
Here’s a little more detail on how the engagement rating algorithm works.
- In order to accurately reflect a range of observed characteristics the engagement rating bands are based on both theoretical and matched empirical data.
- Starring bands are non-linear between maximum and minimum values – again to better reflect observed situations.
- Each campaign interaction (open, click, share etc.) earns a weighted increment depending on the action taken.
- Opt-in is considered as a key engagement indicator.
- Multiple interactions with a single campaign gain additional engagement increments.
- Passive behaviour (non-interaction) over a period of time is considered as a negative characteristic. Non-engagers progressively decay in their star rating over time.
- Habitual non-engagers decay proportionately more rapidly.
Engagement profiling removes the need for guess work or gut-feel and provides a simple, objective measure of complex behavioural patterns.
- It’s a quantitative measure of an abstract concept – the 5 star rating provides a simple interpretation of the data.
- The multi-parameter algorithm provides a holistic view – it takes account of a wide range of interaction behaviour.
- It’s a fully automated process – as a user you don’t need to collect any data or manually take any action.
- Engagement behaviour is monitored and subscriber data is collected over an extended period of time.
- The engagement star rating is dynamic – results are continuously updated as new campaigns are executed.
- Legacy engagement data can be generated by replaying the results of historic campaigns.
- As a profiling ‘dimension’ engagement is extremely useful for segmenting audiences and targeting future campaigns.
By compiling the engagement ratings of all of the members of a subscriber database it’s possible to create an overall picture of the engagement characteristics of an audience as a whole. It also provides the ability to review both the current state of audience engagement and to monitor how that profile has changed over time. Both provide valuable intelligence that can be used to better understand an audience and design specifically targeted future campaigns.
Wan’t to find out more. Join our webinar – ‘Love is… a multi-parameter engagement algorithm’.
Friday 17th February 2017.