Media & Publishing
Publishers hold more audience data than almost any other sector and still find it difficult to say which readers are valuable, which content retains them, and where subscription growth will come from next.
This work is for publishing and media executives: chief executives, Chief Data Officers, commercial and subscription directors, audience and product leaders, and the data teams supporting them.
You gain a resolved audience view, subscription reporting the commercial team trusts, executive reporting produced automatically, and a clear position on AI in content and workflow.
Publishing work we have delivered
Our publishing experience is anchored in company wide data strategy, executive KPI reporting and data academy work with DC Thomson, alongside audience platform work with Games Jobs Live.
Data Understood push to learn the nuances of the company, its overall strategy, its people and thus deliver solutions that benefit the company to its core and lay the foundation for a strong future in data.
They provided costed structure and solutions to create an ongoing credible data management capability.
Data Understood immediately understood what we were trying to do, both in terms of the technical aspects of the data and the implications and possibilities for the business model.
Strategy only holds when it is owned company wide
At DC Thomson the data strategy became a pillar of the company strategy, with cross functional workstreams and shared objectives. That ownership, rather than the document, is what kept it moving.
Definitions decide whether reporting is trusted
Executive KPI reporting was built from raw, imperfect data. Agreeing definitions first was what made the reporting defensible in front of the senior leadership team.
Capability has to be built alongside delivery
Upskilling with the people team, and the academy work that followed, mattered as much as the outputs. Publishers keep the benefit when internal teams can carry it on.
Common challenges
Drawn from the publishing engagements above and the patterns we see repeatedly across national, regional and specialist publishers.
Subscription systems, newsletter tools, ad technology, CRM and web analytics each describe the reader differently. Without resolution between them, nobody can say confidently how many engaged readers you have.
Acquisition, engagement, churn and lifetime value are usually reported separately. Leadership needs to see which levers move retained revenue rather than which campaign produced the most sign ups.
Content performance, audience value and commercial yield are measured with different definitions. The disagreement in the meeting is about the data, not the decision.
Board and leadership packs are built each month from exports and spreadsheets. The effort is significant, the lineage is unclear and the numbers arrive too late to change anything.
Content management, rights, syndication and print systems hold data that was never designed for analysis, so even routine questions require specialist effort.
Generative AI is being used in production, personalisation and audience work. Publishers need a clear position covering intellectual property, brand trust and editorial standards rather than an informal one.
Data & AI opportunities
We describe opportunities in commercial and editorial terms.
A resolved view of the reader across subscription, newsletter, web and commercial systems, so engagement and value can be measured consistently.
Acquisition, onboarding, engagement, churn and lifetime value connected in one model, so commercial teams can see which interventions hold revenue.
Automated, governed reporting on audience, subscription and commercial performance, produced from a single agreed set of definitions.
Content performance measured against reader value and retention as well as reach, giving editorial leaders better information without constraining editorial judgement.
Agreed principles for AI use across production, personalisation and audience work, covering intellectual property, disclosure, oversight and brand trust.
Advertising, licensing and subscription revenue analysed together so trade offs between audience reach and commercial yield are visible.
Our approach
We use our Discover, Design, Develop, Deploy engagement model, with our DIAlog framework to surface the leadership, organisational and cultural factors that determine whether audience data changes decisions.
Subscription analytics connects acquisition, onboarding, engagement, retention and revenue into one model of subscriber value, using consistent definitions across marketing, editorial and finance. It is judged by whether commercial teams change what they do, not by the number of dashboards it produces.
Stage 01
We work with editorial, commercial, product, audience and data leaders to understand the commercial objectives, the decisions that need to improve, and how audience data currently flows between platforms.
Stage 02
We agree the metrics that matter, the definitions behind them, and the platform and ownership model required to produce them reliably. Editorial independence is respected throughout.
Stage 03
We build the governed audience and commercial foundations, then the reporting and analysis the business is waiting for, testing and documenting as part of delivery.
Stage 04
We embed the reporting into the commercial and editorial rhythm, transfer knowledge to your data and analytics people, and agree how definitions are governed as the business changes.
Where to go next
Publishing engagements usually start with strategy or audience reporting and continue into platform and managed delivery work.
Buying questions
Written for commercial, audience and editorial leaders, covering how publishing data work is run in practice.
Whether you're developing a data strategy, modernising your data platform, preparing for AI or tackling a specific business challenge, start with a 30-minute conversation with Inez.
