An understanding of customer engagement underlies all of a journals publisher’s operations from editorial policies to sales drives. Engagement profiling looks at different types of customer interaction and assigns a relative score to each customer based on that interaction.
The specific customer activites that feed into engagement profiling will vary from publisher to publisher, but there are some common categories that will generally be included:
- Subscription spend: this is clearly a key piece of information, but it becomes even more meaningful if you look not only at ‘active’ spend but also at ‘lapsed’ spend – high active spend becomes less signficant if there is also high lapsed spend.
- Usage: again, there is more to consider than the raw data relating to numbers of downloads – what is considered a ‘good’ level of usage may vary according to the type/size of institution and the subject area.
- Cost per download: this brings together spend and usage figures in order to identify ‘safe’ and ‘at risk’ customers.
- Pay per view and alerts data: purchases of individual articles and sign-ups for alerts and newsletters can provide a good indication of interest in your content, both for individuals and for the institutions to which those individuals belong.
- Article submissions: submitting manuscripts, as well as reviewing other people’s submissions, is another aspect of an individual’s engagement with you as a journals publisher – and again, this is the type of activity that can also beneficially be aggregated to the institutional level.
Even from this brief summary, we can see that, despite the basic principle appearing fairly simple, the mechanics of assigning an engagement score are less so. This is where DataSalon’s MasterVision service comes in:
- First and foremost, it brings together all the activity by a particular customer into a single record. This makes it possible not only to assign an engagement score for a particular metric, but to combine those individual scores into an overall score (potentially with different weightings for different metrics).
- Its hierarchical structure associates individuals with their affiliated institutions, thus allowing the activity of individuals to feed into the assessment of an institution’s engagement.
- Its analytical tools make it well-placed to handle all the nuances involved in assigning an accurate engagement score, for example taking into account upwards or downwards trends, as well as setting baselines by segmenting customers into similar types.
- DataSalon staff are experienced in capturing complex requirements and setting up rules to implement them – thus the assignment of scores can be customised for each publisher and, as those scores will automatically be updated each time the underlying data changes, they will always reflect the most current situation.
To find out more, please get in touch for a chat about how engagement profiling could help you to create actionable insights from your data.
