A key first step to a better understanding of your customer relationships and to tailoring your communications to contacts is to bring all of your customer data together into a single view. This is a good starting point but it’s not necessarily ‘actionable insight’. What might be really useful here are comparative measures ‘sat on top’ of the raw data. You could then use these to inform how you interact with different customers to get the best outcomes for your business.
Engagement profiling is a technique that identifies different areas of activity/interaction and assigns a relative score to each customer, ranking them on a scale from 100 (top) to 0 (bottom). These scores can be both overall for each metric you’re interested in as well as per product. A total engagement score, combining all measures together with weighted percentages, can also be inferred for a high level overview.
What activities/interactions might you consider for engagement scoring?
1. Subscription Spend. Knowing how much a customer spends on your products is a very significant piece of data. Ranking customers by their ‘active’ spend and perhaps also their ‘lapsed’ spend for each product and overall is a must-have measure of their engagement with you.
2. Usage. The number of full text downloads this year/last year is one thing but do you know how a customer’s usage compares to others and how it varies across different products? Is the trend going up or down? What might be causing high engagement on spend but dipping usage? Spend and Usage engagement metrics – when taken together – give you a great means to identify both ‘safe’ and ‘at risk’ revenues.
3. Individual Contacts. Another good indicator of engagement is how many related individual contacts you have at each institution. If you are inferring these connections via email domain and institution name matching techniques then assigning a relative score to each institution for their total number of contacts is just one step away. You could score at more granular levels too, e.g. ranking institutions by the number of newsletter/alert recipients.
4. Pay-Per-View Spend. Linking pay-per-view transactions made by individuals to their related institutions and then ranking those institutions by that total spend figure can provide a good indication of the level of interest in and demand for your content.
5. Authors & Reviewers. Linking manuscript submissions/review activity by individuals to their related institutions and then ranking those institutions by that activity is a similar idea but a different perspective on your customers’ engagement with you.
These are just a few examples and we’ve focused on institutions here but the same technique can be applied equally well to your individual customers too. With relative scores for each customer along a number of important dimensions, plus an overall engagement metric, you are taking your single view to a new level with valuable additional insight. It’s then an easy next step to use this to better segment your customers and drive communications that can help address risks and achieve growth for your business.