The Next Decade in Data: How to Tackle the 2020s

Collect, catalog, curate and cut

The ad industry has seen an explosion in the collection, usage and analysis of data over the past 10 years. That begs the question: What will the 2020s hold for data use?

It’s easy to argue that the rise of data in advertising has been a good thing. The industry has grown, consumers have more content and choices and advertisers have more insight and control over their media budgets.

However, it’s also easy to argue that the next 10 years of data in advertising could be radically different.

Ad technology has advanced so rapidly that consumers, publishers and advertisers are likely struggling to keep up. Governments are asking whether digital advertising is encroaching on privacy and annoyed consumers are pushing back against sloppy targeting practices with ad blockers. Publishers too are rethinking how they engage with consumers, advertisers and partners given the potential changes to the regulatory environment.

Businesses could also be struggling with the realization that the incredible data innovations of the last few years might now be standard practice among their competitors. If everyone stands up at a baseball game, no one gets a better view.

The industry is undoubtedly in a moment of transition. To navigate these changes, you should begin with a solid framework to help guide data decisions into the next decade. These four Cs—collect, catalog, curate and cut—are a starting point for thinking about advertising data in the 2020s.


Given the changes GDPR and CCPA have brought to the regulatory environment, marketers, publishers and agencies should reexamine how they collect data. Up until recently, digital data sets had expanded in the background of apps and websites without people outside of the industry taking notice. Those days are over.

Data collection will be governed by two ideas going forward: transparency and consent. Transparency means all market participants being upfront and clear about the type of data being collected, what it will be used for and why that use case is necessary. Consent means consumers and other ecosystem partners agreeing to participate in the exercise that is being described. Going forward, assume that to collect a data point from a consumer you will also have to collect consent.

This new reality could radically alter online experiences for the average consumer. Publishers could change the user experience to comply, advertisers could rethink where they source their data from and the middlemen who buy and sell data are considering how consumer consent can be transferred in a transaction. In the short term, this could cause a decrease in the amount of data collected by publishers and a flight to quality on the buy-side.


Those who have worked with large data sets from publishers, platforms, agencies or advertisers often begin data projects with excitement over the possibility of uncovering new strategic insights that can create a business advantage. But once the project starts and operators examine data sets, there is often a letdown due to incomplete, mislabeled and inconsistent data sets.

Taxonomies are not typically purpose-built for the use case at hand and operational problems emerge as the team pursues the once exciting project. Even the simple task of properly labeling and organizing data points can be a challenge. The promise of AI may also drive demand for accurate, properly labeled data sets that AI systems can understand and use in machine learning algorithms.

Advertisers, platforms and publishers should examine their data catalogs closely and make sure they understand exactly what they have and how it is organized and structured. Flying blind on a data strategy can lead to data despair.


Data collection is growing exponentially. Many assume that the growth in data is going to lead to similar exponential growth in business results. Many also assume that the thing to do in this environment is to use more targeting on ad campaigns. That could be the wrong course of action.

The explosion of data available for analysis can ultimately create an oversupply that crowds out valuable signals. This is not to say that interesting new signals will not be available as the supply of data grows. It just might be extremely hard to find them among the piles of digital data. Curating these piles is a critical part of monetizing it.

Using a valuation process to determine what really matters is a good first step. Does audience-targeting drive value on every campaign? If so, how much? Does it offset the price of implementing it? Would it be more efficient to use location-based targeting instead? What about using both? What about using neither?

These are the types of questions that advertisers evaluating their targeting data do not ask often enough. Many simply pile on the targeting with no regard for the ROI. Data should be no different than any other campaign cost and treated as such.


In my opinion, in the advertising business today, there is too much data adding too little value.

As the industry comes to terms with the oversupply of data in the marketplace and applies common business practices there should be a rationalizing of the market. This could mean low-value data sets being cut and prices increasing for data sets that work and drive value.

This would be a sign of market maturity. Advertisers would apply more scrutiny to their data purchasing and drive the market forward. Suppliers and intermediaries would then be forced to accommodate the new reality and prioritize appropriately.

It’s possible to read this article and assume that I am bearish on the future of data in advertising. That is not the case. I think the most exciting days are ahead of us as new value is unlocked by leveraging the power of data in advertising. However, I think the 2020s will be more complex and difficult than the past 10 years. Simply using data on a campaign won’t be enough. Thoughtful data strategies should consider regulation, operational efforts and ROI. There may be fewer winners, but the increased rigor will help create a durable foundation for the industry going forward.

As head of revenue for IBM Watson Advertising, Jeremy Hlavacek is responsible for all global advertising sales efforts including direct sales, programmatic sales, agency partnerships and data partnerships across Watson  Advertising’s portfolio of media, data, and AI-powered technology solutions including and The Weather Channel apps.