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The 6th Wave of Advertising Technology: Privacy

By Eric Picard, Originally published on AdExchanger – Wednesday, February 24th, 2021

There’s a revolution happening in digital media, primarily driven by a new focus on privacy. Major players at the core of the digital ecosystem have decided that privacy is a core value, and have made fundamental changes that block many standard practices. This change is going to upend the industry as we know it, and offers huge opportunities for anyone in the right position to take advantage of it.

Let’s work our way from where we’ve been to where we are, and then talk about where we’re going.

Wave 1: In the beginning (1996-1998)

The first wave of ad tech was about establishing scalable ways to operate the digital advertising business. Someone had to figure out how to sell ads in advance of the campaign running, how to implement and operate campaigns, how to track delivery and how to bill customers. We saw the rise of ad servers, the creation of sales and ad operations tools and workflows and the invention of buy-side ad serving. And we saw significant growth.

Wave 2: Formats, Targeting, Tracking, Attribution 1.0 (1999-2001)

After the basics got sorted, we saw innovative work in rich media ad formats (things like interactive ads, video, audio, visual effects, over-the-page, expanding ads, etc.). My first startup, Bluestreak, developed many of these formats. Across the industry we saw significant innovation in targeting of ads. (User behavior was tracked and turned into audience segments, which could be sold.) And a new attribution discipline emerged to measure what happened after a person saw or clicked on an ad.

Wave 3: Remnant Monetization, Multi-Touch Attribution, Yield Optimization (2002-2006)

When the “dot-com” bubble burst in 2001, the average CPM of display ad inventory dropped from about $25 to about $0.50 in the course of a year. All the peripheral ad tech companies that had been charging ad-on fees for rich media and targeting began to struggle – that is, until they eventually realized they could sell directly to publishers as a way to drive yield. In the hunt for revenue at any cost, and as vast numbers of smart sales people got laid off, someone figured out that secondary and even tertiary ad marketplaces could be used to monetize every single impression at some price. This model was in some ways a mistake, because it further devalued inventory, which was already under price pressure. It took a long time for this wave to end, and in some ways it still hasn’t ended.

On the buy side, advertisers began to realize that “last touch” attribution was obscuring the real drivers of conversions, falsely rewarding some channels, specifically paid search. Sadly, some advertisers still use last-touch models.

Wave 4: The rise of programmatic (2007-2014)

A few really smart people realized that remnant marketplaces were evolving similarly to commodities and securities marketplaces. And they began building auction-based exchanges that sold inventory in much the same way paid search was sold.

This wave was incredibly powerful and it supercharged the industry. As we saw with the evolution of electronic exchanges in securities, the market moved away from daisy-chained tag-based auctions to real-time bidding (RTB). This extensible infrastructure also led to opportunities for nefarious actors to make money by fraudulently selling fake ads, defrauding advertisers and publishers of billions of dollars over many years. And a massive investment in the data infrastructure has led in many ways to a “surveillance state” that allows almost any company to track people’s behavior across the entire internet and build targeting segments that can be used to buy them as advertising.

Wave 5: Privileged Programmatic and Fraud Cleanup (2015-2020)

As it matured, programmatic advertising continued to walk in the footsteps of the securities exchanges. The largest ad buyers and sellers began to recreate privileged relationships inside the new RTB infrastructure. Examples include PMPs, “first look” mechanisms like header bidding and Prebid. It is now possible (but will take a while) to completely recreate all the ways ads have been sold historically on top of RTB infrastructure, but the eventual result will be a much more scalable and automated way of doing business.

Similarly, the massive and hidden problem of fraud was uncovered, and measures were taken to root it out. Industry efforts like Ads.txt and Sellers.json, and whole new companies and technologies for fraud detection and prevention, has set the industry on a path to solving this crisis. The result: a massive maturation of the ecosystem.

Wave 6: Privacy – Centric Advertising, New Format Innovation and Supply-Chain Optimization

Meanwhile the “surveillance state” we’ve found ourselves in has led to a huge backlash against third-party tracking that is upending the ecosystem again.

Over the last few years we’ve seen major initiatives by the technology industry to establish and enforce new privacy controls across all media. This trend is accelerating and broadening, and many of the mechanisms we’ve taken for granted in online advertising have been ruled privacy-unsafe, and are being phased out. Many companies in the space have doubled down on a commitment to these older tracking approaches, and are trying to find a path through that perpetuates them. I will hazard a prediction that this is not going to work.

The time is coming to an end when companies with no relationship to the consumer can track those consumers’ behavior across the internet and then sell that data. This evolution will strengthen companies that do have a direct (i.e. “first party”) consumer relationship, such as advertisers and publishers. It also is helping the largest incumbents like Facebook and Google, who have immense amounts of first-party data.

Technology providers will need to find ways to evolve their offerings such that they support the direct consumer relationships held by the advertiser and/or the publisher. This will mean in many cases either a completely new approach, or a set of innovations in how technology is integrated with the first-party companies’ infrastructure. The great thing about disruption is that it leads to new innovations.

Because the third-party data and tracking infrastructure is becoming less valuable, new ways to increase the value of ad opportunities will come to the foreground. Format innovation is back in the mix as a way to increase the value of inventory without breaching privacy protections. And the next wave of supply cleanup, after the war over fraud, will ensure supply chains are clean and optimized, with low-value suppliers shuffled out of existence.

Supply-chain optimization has been emerging as a focus area since around 2014, but now is becoming mainstream. The first round of supply-chain optimization was ‘brute force’ and ugly, but we’re now seeing intelligent and powerful supply-chain optimization enter the market, as well as industry initiatives like Sellers.json. These new technologies, initiatives and approaches are driving advertiser value and publisher yield significantly.

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Why dynamic creative has bounced back from failure

By Eric Picard (Originally published on iMediaConnection October 14th, 2013)

Back in 1999 (when the moon did not have a moonbase Alpha, nor did an explosion send the moon rocketing across the cosmos — a reference for old-timers like me) while at my last startup, Bluestreak, we started experimenting with dynamic creative.

The idea was that there were e-commerce companies with thousands of products available online, and that based on location we should be able to test and optimize which products led to the most clicks and purchases. Over the next few years, we worked with several customers to experiment with this. We ultimately ran ads with several publishers that would rotate through a list of products, and we used our creative optimization technology to determine which combination of offers was getting the best results (based on clicks, interactions, or conversions).

It turned out that there were various combinations of location (publisher) and product that worked much better than others, and the tests were successful. But the question was really about matters of degrees. We saw significant improvements in results, and we developed great technology that supported all this. But after the bottom dropped out of the market in 2000 and 2001 and the price of inventory dropped significantly, the improvements in performance stopped mattering as much.

Essentially, the price of inventory was so low that it was cheaper to just run much higher volumes of unoptimized ads than to pay for optimization service.

But I knew that creative optimization and dynamic creative would have its time and place. Either the impact of the creative optimization would drive significantly better results, the price of inventory would come back up, or we’d be able to optimize the offers based on user targeting rather than just by publisher.

Creative optimization and dynamic creative dropped out of the industry for eight to 10 years, but it came screaming back. As I guessed, the major driver was targeting based on user data. And over the past few years, the growth of real-time bidding and audience targeting has led to significant improvements in dynamic creative and optimization.

There are now several significant companies that have built their business around the idea of optimizing the offer shown to users based on their profiles, including a lot of retargeting. They build advertising campaigns that are driven by databases — ones that pull together the creative in ways that include hundreds or thousands or even millions of possible combinations. The best offer is selected based on a variety of criteria, including audience targeting attributes such demographics, behavioral data, and retargeting data. This information is extensively available and can be used to drive significantly better optimization than just location.

We all know that with real-time bidding and ad exchanges, ads can be targeted based on this kind of data. And we all know that with basic tracking of impressions, clicks, and conversions, bid prices in ad exchanges can be adjusted to optimize results based on the number of clicks or conversions. But dynamic creative optimization can take things to the next level. Using all of these technologies and techniques in combination can significantly drive up ROI. The only question is how many different products, offers, or options are available for optimization purposes.

The more opportunities to adjust the creative — especially if those products or offers can be somehow predicted to match against different audiences’ preferences or interests — the more likely the user is to act.
Read more at http://www.imediaconnection.com/content/35170.asp#sxRJhl1kvggxUiAe.99