Smart Data Initiative priorities this year: personalisation, first-party data, data strength

By Ariane Bernard


New York City, Paris


Hi everyone. I’m Ariane, and I’m new to INMA. 

I just joined as the project lead for the Smart Data Initiative, taking on the mantle from your esteemed steward Greg Piechota. Greg is not going anywhere and is still the researcher-in-residence at INMA — he’ll continue driving various initiatives, including the Reader First Initiative.

So that we’re not complete strangers, here’s a tiny bit about me. My expertise is on the product side, specifically in publishing and delivery platforms: for content (CMSs), for subscriptions (paywalls), and for data and analytics. I spent 14 years at The New York Times, after which I went to Taboola and was the head of digital at Le Parisien in Paris. I went the independent route in 2019, and have been working with publishers and technology vendors across the spectrum of publishing technology: CMSs, subscriber revenue capability, customer journeys, and data strategy — whether in planning big bang replatforming or creating custom solutions and tools.  

I split my time between New York and Paris — because I cannot pick one side of the ocean. As I write these lines, I am in Paris. 

So now, I’m no longer a stranger to you. But I’d love to hear from you. E-mail me at to say hi and tell me how the Smart Data Initiative could be useful to you — from programming to speakers, to big questions you see in your midst.

Smart Data Initiative’s 3 tentpole topics for 2022

In my early days in this new role, I have spent some time decanting some of the more global trends in our overall space of data to identify the three tentpole issues the Smart Data Initiative would take on this year. 

There are, to be sure, many competing problems and opportunities to look at — but three stood out:

  • Personalisation.

  • Acquiring and using first-party data.

  • Accelerating the change toward a data-strong organisation.

I have informed this choice of priorities with interviews from leaders in our community, and I’ll share some of the avenues for these three tentpoles here.

1. Personalisation: How do we build better products that leverage the most of what the organisation offers while building habits and driving revenue?

Personalisation is one of these words that means different things to different people: 

  • From cohort-personalisation to one-to-one personalisation. 

  • From content personalisation to user experience. 

  • From pricing and customer journey variations.  

But there is one common thread to how this word is used, which is that personalisation is the leveraging of data that we have acquired about a user (or a cohort of users) to propose an optimised experience to this user. 

Personalisation is how media companies leverage acquired user data to better target the user experience.
Personalisation is how media companies leverage acquired user data to better target the user experience.

There is a lot of room in the term “optimisation” here — from content optimisation (content recommendation), to UX optimisation (emphasising the visual presentation of elements the user has interacted with in the past or new features we think would further habituate her); from customer journey optimisations (judiciously exposing new activities to a user who has already completed some journey steps and no longer prompting her to download an app she has already downloaded), to personalising some of the commercial offers she might see. 

Degrees of personalisation are achievable whether with a logged-in user or a brand new anonymous cookie. But, of course, the deeper and more personal the data, the more options are available to the product and commercial side of the business to optimise the experience and, ultimately, the chance of higher revenue from this user 

One topic that came back in my conversation was the North Star goal of one-to-one personalisation. For some, this felt like a promise that couldn’t be delivered on the open Web: 

  • Too many anonymous, transient cookies.

  • Too many screens and limited capacity for tying up these cross-platform activities under one clean user profile. 

  • Taxing computing resources needed to deliver these differentiated experiences.

But do we accept that because the journey is long it cannot be done? I think we can surprise ourselves.

In other conversations, the imperative was that we collectively progressed on the journey to personalisation — understanding that depending on the type of publisher business and the user’s journey, the ability to personalise and optimise everything was going to be thinner at times.  

So what can we learn from each other that is valuable at whatever step of the journey your organisation is at? Concretely, what are data strategies —from framework, to the acquisition, to the delivery of the data — that enable this path to personalisation? 

2. Acquiring and using first-party data: How do we approach privacy and cookies in a changing world?

The news last week that Google was moving to another approach for its post-cookie advertising targeting framework (we went from FLoC — Federated Learning of Cohorts — to the Topics API) was met with as many Twitter hot takes as questions. 

This illustrates something about where our post-cookie world may be headed: We know we’re going there, but even Google isn’t quite sure how to get there without massively impacting certain business corners of the Internet (as well as its own business). 

As Google keeps changing its mind on the future of post-cookie advertising, the exact path and timing remain unclear.
As Google keeps changing its mind on the future of post-cookie advertising, the exact path and timing remain unclear.

For publishers, we rely on cookies not just for ad revenue. We also are more and more dependent on our ability to track a user as they journey and habituate in our products. Our usage of third-party data is for our immediate profit (ads), and our usage of first-party is for our long-term benefit — and a better experience for our users (see first point on personalisation). 

The billion-dollar question is: How do we transition to acquiring and leveraging first-party data in places where we relied on third-party data to which we may have less access in the future? 

There is also the question of how user expectations for their experience with us are changing: How they are tracked or not? What is their expectation for being able to exercise their choice in the matter? 

To put it in the words of a publisher to me last month, “Is the data yours because it happened on your site, or does it belong to the user because she is the one who made these interaction decisions?”

The regulation pressure around our collection, usage, and protection of user data is something we need to learn to weave into our data strategies — both to remain compliant but to also to anticipate where we may see regulator-imposed changes to what we do. 

The European Union’s GDPR was an important fog horn, but after California, the U.S. may see some regulatory changes of the same order: Massachusetts has a bill moving along that has echoes of California’s legislation, and further changes like the (forever work-in-progress) rewriting of the European ePrivacy legislation may cause further pressure in our businesses.

While these topics always look like they are territory-specific, there is a certain arc of history that seems to bend the trend toward data privacy as the default paradigm for our products. And for many of our digital businesses that operate across multiple geographies, we generally want to have one global approach to data privacy so we don’t create an incredibly complex technical or legal burden. 

This, in the end, means that observing where these trends are taking us — or how organisations located in geographies that have been affected earlier by these changes — can provide useful learnings for all of us.

3. Accelerating the change toward a data-strong organisation: How do we handle culture change, the building or scaling of teams, and informing our priorities with data?

One of the strong propositions of news publishing is that clever and well-informed humans should arbitrate the often complicated calls of what is selected to be published and when and how. 

When an editor faced with a breaking news scenario has to decide on what play to give the story and what angle to shape the headline or article, these decisions aren’t made based on A/B tests and careful analysis of user data. It is the entire expertise and experience of the editor that is being called upon to deliver a decision on what to do. In news publishing, experience is the base of many calls and decisions. 

But there, much has changed already and continues to change.

Data offers editors non-biased information on which to make news judgment calls.
Data offers editors non-biased information on which to make news judgment calls.

In our digital world, we can learn things about users and business that our organisations simply could never have learned just 10 years ago. Instinctual decisions have their place, but data represents an opportunity to deliver an even better product to users and even more value to business stakeholders — to say nothing of seeing past our blind spots.

In my conversations with the INMA community last month in preparation for this year’s Smart Data Initiative, pretty much every person I spoke to touched on these topics of cultural change: 

  • How to orient our businesses to the changing paradigm of using data in the decisions we make for the business or the product.

  • Bringing the practitioners of data science, analytics, or user research to equal seats as other key roles of our organisations.

  • Generally infusing our strategies and decisions with data. 

  • Prioritising investment in data capabilities: Operational leaders who cannot get their data project prioritised because they are neither the next big subscription project nor small enough that they can be negotiated on the side of a large technical roadmap.

  • Subject matter experts are concerned that data is often seen as a convenient accessory when it can tell a desirable story and ignored when it seems more contradictory.

  • Mid-career analysts who see their seat at the table reduced to being a provider of PowerPoint when they feel they are sitting on so much useful information — if only they were given a chance to contribute to the right conversations. 

But there are also more hopeful trends:

  • Smaller media organisations making their first hires in data.

  • Organic collaborations and partnerships happening across the organisation between data folks and editorial folks who’ve come to appreciate what they could bring to each other. 

  • Grassroot knowledge-sharing programmes often just born from a casual conversation and the ferment known as human curiosity. 

  • Heads of data being brought to the c-suite as chief data officers. 

  • Data and analytics embedding in cross-expertise teams to de-silo data as “step” in a linear process, bringing this as an equal partner of everyday operations.

To be sure, all stories of change in organisations (or humans) are stories of zig-zags. Part psychology, part tactical; part aspiration, part bet; and partly defensive, too. Are we responding because we see big platforms eat what we considered our lunch? Or do we feel inspired by the product experience of a Netflix that brings to bear all its data in service of a user experience we recognise for its quality? We change because we eventually convince ourselves that we should, and sometimes because change agents have made it harder to resist change rather than embracing it. 

The practice of data is a team sport at media companies.
The practice of data is a team sport at media companies.

This last tentpole item is about what we can teach and learn from each other on a journey where a new practice — data — becomes an integral part not just of our products, but also our organisations.

Further afield on the wide, wide Web

One good read from the wider world of data. This week, MIT researchers have created a model to teach robots how to stimulate certain skills that are unique to humans: The ability to interact socially.

Dates to remember: March 10-24

The Smart Data Initiative’s first master class for 2022 is next month: Transforming what we build using data. You can find out more here. See you there!

Meet the community

For each installment of this newsletter, I am hoping to introduce one member of the community in this space. Want to be featured here? A few questions to get to know you better: Thanks!

About this newsletter

Today’s newsletter is written by Ariane Bernard, a Paris- and New York-based consultant who focuses on publishing utilities and data products, and is the CEO of a young incubated company,

This newsletter is a public face of the INMA Smart Data Initiative. You can e-mail me at with thoughts, suggestions, and questions. Sign up to our Slack channel.

About Ariane Bernard

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