Subscription data normally sits at the heart of a publisher’s view of the customer, because it’s crucial to know who has paid for what. But, the same rules don’t apply to Open Access (OA) journals, whereby content is made available for free and a publisher’s revenue stream comes instead from an ‘author pays’ model. Let’s take a look at the various ways an OA model might change your marketing activities:
1. The Author is King. In a model where authors pay you for your peer review, content production and distribution services, accurate author data displaces subscription information as the most critical information source. You might already be analysing data from your manuscript tracking system, but does it include details relating to each author’s submission history and publishing outcomes, author interests, and also editor activity? You’ll want to ensure that every drop of author information is available to your staff for searching, segmentation and analysis.
2. Follow the Money. Who is paying you to publish OA content? It might be the authors themselves, or more likely their research funders. These could be academic institutions or other organisations already known to you as paying subscribers, but it’s possible there could be gaps in your knowledge here and further research to capture the details of all potential funders might be necessary. Of course, wherever possible, you will also need to know the connections too, ie. which authors are related to which funders?
3. Who’s Who? With author and funder records taking centre stage, the need for standard names and common identifiers becomes critical. An author’s name is a poor basis for identification because there are so many different authors who share the same name. The ORCID initiative which is aiming to solve the author/contributor name ambiguity problem in scholarly communications, is very relevant here, and it’s likely that this ID will soon become a must-have field in every author or manuscript database.
4. Article Usage. Usage is another data source that you may already be including in your single view, but your statistics are probably only at the journal level and integrated from an institutional perspective. Clearly, high institutional usage remains important to satisfying existing authors, attracting new authors and enhancing your brand overall, but you will now need to provide authors with statistics on the performance of their individual articles. The PLoS article-level metrics are interesting food for thought here. Your single view should therefore be capable of segmenting on usage at the article level too. In this context, the PIRUS projects and a new COUNTER standard for journal article usage are also very relevant.
5. Data Mining. You will want to include and explore any data source that might lead you to new authors, as ‘prospecting for new authors’ replaces ‘prospecting for new subscribers’ as a key sales and marketing priority. This might draw on data sources already at hand (eg. alert recipients, society member records) but it could also be sources not yet on your radar, such as conference proceedings or third party resources listing authors and their past papers or interests.
In summary: it’s clear that OA publishing can turn a lot of current journal marketing practice on its head. Any publisher involved in OA publishing should therefore give careful consideration to all of the issues highlighted here, and consider taking steps to ensure that all the relevant data is being captured and made available for author-based analysis.
The DataSalon Blog 
Agree with the article. But for people working in the stm-publishing industry this should be old news. Should have been implemented in the strategy and workprocesses