We’re often asked questions such as: “What data should I load into MasterVision?”; “How do I get that out of my databases?”; and “What fields should I include for the most useful analysis?”.
All of these are good questions, and should be considered carefully in order to get the best value from your data. There are a number of considerations to use as a starting point:
What systems do I have and which should I use?
- Make a list of all the systems you have which are gathering details about your customers. These are likely to be fulfilment systems; editorial submissions databases; usage and denials stats from a journals platform; campaigns data; CRM information, etc.
- Which systems you choose to extract data from may depend on the quality of the existing interface of that system, and the time it takes to get what you need out of it. For example, does it provide a meaningful overview of customer activity? If the answer is no, then it makes sense to export that data to a system that can.
- There are certain key areas that are vital for your business. Many publishers choose to focus primarily on authors, subscriptions, usage and denials as the most valuable starting point for customer analysis.
How do I get this data out?
- You may already have access to export tools for business reporting. Any valid data table generated by those tools could be imported into your insight tool.
- Speak to your database provider, as they should be able to tailor exports easily to your needs. A list of required fields should be all they need.
- There could also be industry standard reports you can use, such as COUNTER reports you can access using the SUSHI protocol. It’s worth exploring which reports are already being produced, and potentially re-using those for your analytics service.
What information should I include to meet my business objectives?
This is probably the most fundamental point, i.e. what do you want to be able to achieve, and how can you get ROI from both the data and your chosen analytics system?
- By integrating CRM data, you can start to build up a detailed picture of sales opportunities by account owner, roles, region, etc. You can also easily track the progress of leads by integrating with other sources, such as campaigns. You can then create targeted mailing groups and track the effectiveness of those campaigns over time.
- When considering the often huge range of fulfilment data fields to include, there are some basic key areas to add: customer profile information; products subscribed to; the subscribed period; and values of those purchases. A relatively small and focused set of information can provide an extensive range of analysis possibilities, such as what customers are spending; who subscribed last year but not this year; who should be buying collections; who is subscribing to title A but not related title B; subs trends by country and region; and the cost per download for each customer.
- Also, consider how many years’ worth of data you should include; 3 years is often a useful rule of thumb, as it enables trends to be tracked over a fair period of time.
More is sometimes easier! Your choice of analytics tool should be able to easily drop unwanted fields, or clean up data when importing. When adopting an analytics service, planning is key: knowing your objectives and use cases will help you quickly achieve a better understanding of your customers, and win valuable new sales.
The DataSalon Blog 