Data Analytics: Uses in Publishing Domain for user engagement, discoverability and monetization

Publications as we know today has always taken breath-taking turns of events with times, throughout history. The rapid development of digitalization within publishing firms is bringing out some new aspects of Information Technology being utilized for publishing content on digital platforms. With analytics playing a major role in understanding the demographics, audiences and seasonal content, publications are able to both produce and reach out to the audiences on a more relevant level.

What is Data Analytics all about?

Defining it in the simplest way, data analytics is a term given to a process which examines the datasets in order to extract some useful information out of the same. These data analytics and analysis, therefore, becomes an essential part of constructive decisions made within publishing companies, helping in the establishment of more logical plans, audience-based content production and attainment of operative commercial sustainability.

Data Analytics- Capturing the corporate nerves

Any publication firm runs on three basic factors – Audience relevancy, Content production and Revenue outputs. With expansions within any publishing firm, it becomes nearly impossible to keep a balance among all three factors simultaneously. Big Data analytics has proven to be of great help in such needful scenarios. With Big data technologies created to analyse the huge amount of datasets, publishing firms are able to extract the economic benefit out of it in a longer run.

  • User Relevance: A huge data is sorted by data analytic software to retrieve relevant users and audience demographics that probably associate themselves with the respective content. Tracking these users brings a clearer perspective among publishing companies, as to which content would be more suitable to the particular people of age, gender and geographical area. Data Analytics capture audiences’ core content type likings, mood and frequency of the user visits on publishing pages which helps publishing firms to highlight and advertise relevant content based to the respective set of audience.
  • Production & Discoverability: The big question lies ahead of production houses: Can there be any utilization of data analytics in content production? Well yes, the answer is affirmative. Data analytics helps publishing firms track – if the content is getting the reviews they are seeking forward to or not, and watch out if the content production is adding any value to audience attraction. This way, they can refine their content to attract audiences and even increase their reputation amidst the readers and audiences.
  • Monetization: A huge problem of retrieving the invested expenditure on content production, can be solved by Big Data Analytics. Predictive Analytics, AI/ML analytics, and Big Data have made it possible for publishing firms to structure an advanced, informed and much more guaranteed revenue model which can help publishing firms involve individual contributors more frequently, invest more on high-budget content productions and most importantly, effectively inline their profitable return on investments.

With regular advancement being made on Data Analytic software, worldwide, it is very clear that future is going to bring more opportunities for Publishing firms to craft an efficient roadmap which would help them to achieve more specific audiences that will applaud their content excellence, and eventually will become a bigger contributor of revenue generation for these firms.

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