#57: Quo Vadis Green Shoot AdTech Interviews
With Marc Guldimann, Founder and CEO of Adelaide Metrics
Reading Time: 5 minutes of salience
Welcome back to Quo Vadis Green Shoot AdTech Interviews.
In this series, we’re stepping into the shoes of “AdTech Equalizers” — the greenshoot companies changing how the advertising job gets done. We delve into their worldview and unveil new strategies, tools, and thinking that make advertisers better off.
Today we’ll hear from Marc Guldimann, the serial entrepreneur and founder/CEO of Adelaide Metrics, the leading attention metrics company in the rapidly growing field of real-time attention measurement bringing transparency to media quality.
As our Quo Vadis readers already know, we are huge fans of attention metrics as the best alternative to make ad quality data observable and fungible across channels.
Q: Why should advertisers make the switch from viewability to attention metrics?
A: Marc Guldimann
Metrics like viewability and VCR provide an incomplete picture at best, incentivizing a focus on cost over value and fueling a marketplace flooded with low-quality yet viewable impressions that fails to serve advertisers and audiences. With the advent of new channels, platforms, formats, and devices, audiences have become increasingly fragmented, further exacerbating the challenges associated with media quality opacity.
Attention metrics are unique in that they process granular media quality signals to help advertisers pinpoint the placements that offer the highest probability of attention and impact. As a truely fungile measure, they can be leveraged to assess media quality and effectiveness across channels thus eliminating the need for diverse KPIs for multi-channel campaigns.
At Adelaide, we’ve partnered with dozens of advertisers to prove the connection between our attention-based metric AU and business outcomes—our latest Outcomes Guide shows attention measurement and activation delivering an average of 31% upper-funnel and 56% lower-funnel lift in outcomes.
Q: What’s the biggest misconception about attention metrics?
A: Marc Guldimann
The biggest misconception is that maximizing attention, measured in time or seconds spent with an ad, means better outcomes. While it’s true the duration of attention correlates with impact, it’s misleading as a campaign target, often steering marketers toward suboptimal and unintended results. This approach overlooks the complexity of attention, which is not only driven by media but also creative relevance and audience.
Maximizing attention creates incentives for salacious or distracting creative that holds attention for longer but doesn’t necessarily produce positive outcomes. Worse, it can result in targeting audiences who are the most likely to pay attention for the longest. According to research, these audiences are often older, over-frequencied, or already brand-aware, a phenomenon Adelaide calls the “Attentive Audience Paradox.”
Q: Okay, so if attention metrics shouldn’t be used as a KPI, what’s the solution?
A: Marc Guldimann
Instead of relying on attention metrics as a campaign target, marketers should utilize them to guide media investment decisions. This necessitates an attention metric that extracts the influences of both audience and creative. A media placement’s job is to create an opportunity for attention, therefore, measures of media quality should focus on the likelihood of attention and resulting outcomes, rather than the duration of attention sustained.
Advertisers can then tune media buying strategies and algorithms to business outcomes while using attention data to factor in important insights about media quality and value. This method avoids the attention-maximization pitfalls and promotes an outcome-driven strategy.
Q: How can advertisers leverage attention metrics programmatically?
A: Marc Guldimann
Advertisers can deploy attention metrics through their preferred DSPs and SSPs via high-attention PMPs, attention-based custom bidding algorithms, and prebid segments. Programmatic activation of attention metrics — while varying in its application and dependent on both the specific use case and platform — is unified by a central goal: simplifying the deployment of attention metrics to drive better outcomes.
High-attention PMPs, for instance, are one of the most efficient and flexible ways to activate attention metrics programmatically. They don’t require an integration between an advertiser’s DSP and attention vendor, and media buyers can layer DSP targeting on top of inventory curation. Alternatively, custom bidding algorithms tend to be a bit more involved in terms of set up, but they offer an extremely granular and nuanced use of attention data, intelligently bidding up higher-quality placements and reducing bids for lower quality. In effect, bidding based on attention data creates the best opportunity to bid the true intrinsic price for the media.
Irrespective of the intricacies of each method, programmatic activation reduces friction, allowing advertisers to easily—in many cases, automatically—secure more impactful, high-quality media. For this reason we’ve seen rapid growth in the space, with brands like Audi driving remarkable results, including 60%+ higher programmatic conversions and a 53% lower cost per conversion when using an AU-based custom algorithm versus standard bidding.
Q: Okay, so that means attention metrics can also help mitigate the effects of increased privacy legislation and decline of cookie-based attribution, right?
A: Marc Guldimann
Yes, attention metrics can offer a privacy-safe alternative to cookie-based attribution. Attention metrics measure a placement’s probability of attention and outcomes to provide a precise and nuanced understanding of media quality. This enables advertisers to make informed investment decisions without connecting every impression to an individual shift in attitude or behavior, eliminating the need for user-based identifiers, identity resolution, and privacy infringement.
2023 Attention Metrics Outcomes: Learn more. Get it today.
Adelaide’s analysis features 38 case studies across 14 industries, detailing how AU measurement and optimization has helped advertisers see an average of 31% upper-funnel and 56% lower-funnel lift.
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