These 4 data platforms are helping media ad teams monetise audiences

By Abhishek Dadoo



From the lens of a digital publisher, it’s like a kitchen sink when it comes to the various data platforms that exist.

There is a lot of literature about the advantages of first-party data for digital publishers, but there is little information about the types of data platforms digital publishers can adopt to monetise audiences and improve yields.

Here is a bird’s-eye overview of how data platforms evolved over time and how digital publishers can leverage each to maximise monetisation.

Broadly speaking, there are four types of data platforms.

1. Ad networks

With the rise of digital publishing in the early 2000s, many ad networks evolved to provide third-party, cookie-based advertising solutions. News publishers simply fed their ad inventory to the ad network, and the ad network made sure those ad slots are filled with the most “relevant” ads for the publishers’ audience.

This is a grossly oversimplified view of an ad network from a digital publisher’s lens, but it largely holds true.

Ad networks build anonymous user personas based on the ad network’s unique digital fingerprint of the user, which travels with the user across mobile apps and Web sites as long as the user is on the same device or using the same browser. This is why, if you ever considered buying a sofa for your living room on one e-commerce Web site, ads of the same sofa follow you on every publisher Web site you visit thereafter.

This mode of advertising is coming to an end. With the permanent expiry of third-party cookies in sight, the monetisation potential from such ad networks is quickly diminishing for digital publishers. Therefore, many ad networks started moving toward context-based advertising solutions and providing white-labeled data management platforms to store and manage first-party data on behalf of digital publishers.

2. Data management platforms (DMPs)

DMPs allow digital publishers to gather and analyse huge amounts of anonymous data to make marketing and advertising decisions.

By 2015, ad network-based programmatic advertising started showing early signs of declining yields for digital publishers. After all, publishers had been relegated to providing dumb ad slots. The intelligence about their users resided with the ad networks.

Sophisticated publishers started using their first-party data to create their own audience segments, and that gave prominence to the usage of white-labeled data management platforms. Publishers could further enrich their first-party data with secondary or tertiary data sources by matching on common identifiers between the two data sets.

Armed with their own audience segments, digital publishers could sell their ad inventory to specific demand sources, thereby generating a higher yield from the digital advertising value chain.

3. Customer data platforms (CDPs)

CDPs focus on unifying customer data to help digital publishers deliver better personalised experiences across the customer life cycle. By 2020, we were living in a world with too much content, and online traffic was through the roof. There was just too much ad inventory supply with digital publishers.

However, advertising dollars had gravitated in large parts with social media platforms, Google Search, YouTube, etc., that had proprietary audience segmentation better than what the publishers’ DMPs and independent ad networks had on offer. Further, the privacy regime had become mainstream by then, and advertising identifiers based on third-party cookies or device identification were on their way out.

With flattening ad yields, unpredictability of demand from advertisers, and the recent success of subscription-based revenue models, digital publishers started exploring reader revenue-based models en masse. In the reader revenue business, however, the customer is no longer the advertiser; the customer is the end user with personal identifiable information (PII).

Providing personalised experiences and re-circulation is paramount in the reader revenue business. The main purpose of a CDP is to create a unified customer profile that can be used to personalise customer engagement across channels like the Web site, e-mail, SMS/text, and chat. They help digital publishers create a more targeted and relevant re-circulation strategy, as well as improve customer engagement and loyalty.

4. Reader networks

We are now in 2023. The pageviews and mass audience era is long gone. While CDPs are great for building engagement and loyalty with existing users, they don’t expose digital publishers to new audiences worthy of reader revenue.

CDPs do not provide the full spectrum of services that a reader revenue business needs. This is where reader networks (a new term coined by Fewcents) comes in.

Just like ad networks bring advertiser demand to digital publishers, reader networks add value to digital publishers in exchange of publishers’ user data.

Reader networks provide a PII-based and privacy-compliant identity management system such that a common identity is established based on user login. Reader networks collect and manage user data to provide value-added services such as audience segmentation, content pricing, subscription management, micro-access management, payments, re-circulation, audience development, generate advertiser demand, analytics, and more.

Reader networks are evolving fast and the largest digital publishers are pursuing early experiments at this stage.

About Abhishek Dadoo

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