Lisa Bradner is the Chief Commercialization Strategy Officer at programmatic ad exchange Yieldmo. We sat down with Lisa to discuss advances in programmatic, including contextual targeting, behaviour modelling and ad budgets.

Image: Lisa Bradner, Yieldmo

Tell me about your role… What does a typical day look like for you?

At a macro-level, I’m the voice of our customer internally at Yieldmo. I partner with my revenue stakeholders to learn, identify trends and become a champion and advocate for customer needs across the product and business organizations.

Being deeply connected to our clients’ success is extremely important, as I’m tasked with recommending solutions and offerings that aid and accelerate revenue growth, as well as support achieving the company’s long-term vision and strategic goals.

What are some of the benefits (and challenges) that come with contextual advertising?

I think the biggest challenge to contextual advertising is reputational. Contextual has had many different iterations over the years, and previous versions fell short of delivering what was promised in their sales pitches. Understandably, many are now cautious when they hear the approach being suggested again.

But the contextual solutions of today are a whole different machine. It’s like comparing a horse and cart to an electric car: the objectives may be the same, but the technologies powering them are generations apart. Recent years have seen incredible accelerations in data science, data architecture, and machine learning. By blending them together, inventory can be judged for contextual alignment on a granular level, driving the performance of programmatic purchasing to new heights.

As the death of the cookie gets closer, it’s important to have both audience based and non-audience based approaches, with constant testing to provide an understanding of the costs and benefits of each. Being able to continue to reach audiences in an effective and privacy secure way is going to become of the utmost importance. Contextual allows advertisers to do just that, and now the ability of AI to gather, filter, and analyse huge swathes of privacy-compliant consumer data gives contextual targeting the ability to scale.

As the death of the cookie gets closer, it’s important to have both audience based and non-audience based approaches…

The self-improving cyclic nature of machine learning (ML) means that contextual solutions are constantly improving and, therefore, able to adapt alongside rapidly evolving digital environments.

What other advertising formats do you think are underrated or misunderstood?

The pace at which technology has evolved has created a gap in awareness about what can be done with the tools available today. Things such as ad formats and creative testing have really improved and are now a much lighter lift than they used to be, from a tagging and trafficking perspective.

For example, our Hyperscroller is a new type of ad format that progresses a site visitor through an animation as they scroll the page, creating a dynamic and elegant interactive ad experience. Despite often just being seen as something simply to entertain the user as they scroll, this beautifully designed format is also highly effective for advertisers.

It’s been wonderful to see brands realise the value of this tool, with creative that evolves and transforms in eye-catching ways as audiences move around a site. For example, user-controlled 360-degree 3D models of a product or step-by-step demonstrations of a service.

This design also means that Hyperscroller ads are able to effectively track users’ movements, clocking when they paused, when they touched the ad, or when they doubled back. This mix of engaging content and data collection allows advertisers to maximise campaigns to be even more effective thanks to the ever-evolving power of ML.

What are you seeing in terms of media budgets right now? How has Yieldmo tackled any challenges in this area?

Despite the economic turbulence, we’re seeing most advertisers stay away from the scythe and avoid sweeping cuts to their media budgets. Lessons have clearly been learnt from the pandemic, and marketers are increasingly aware of the importance of maintaining engagement with consumers.

What we are seeing is the need for spend to be more effective than ever before and I think we’re perfectly positioned to provide that to marketers. As the twin issues of the third-party identifier phase-out and the recession collide, marketers are going to have to be brave and embrace new targeting methods to reach consumers.

Contextual targeting has a huge role to play in this. The ability to track customer interactions such as phone tilts and scrolls also allows our partners to track consumer content in greater detail than before, and the more detail advertisers have, the more they can refine the cost-effectiveness of their campaigns.

Of course, no amount of improvements to programmatic’s pipes will matter if advertisers can’t deliver attention-grabbing creative. We’ve made this as easy as possible for advertisers with our Frictionless Formats, which are intuitive templates for high quality, high-impact creative that require minimal investment in time and resources through the repurposing of existing assets. As always, our goal is to remove pain points for brands at all stages of the advertising process.

As the twin issues of the third-party identifier phase-out and the recession collide, marketers are going to have to be brave and embrace new targeting methods

What trends or innovations do you think will come to the forefront of your industry in the next 12 months?

Already we’re seeing the growing importance of measuring the attention of audiences as they interact with advertising, but I think we’re going to see the industry take this a step further and look deeper into tracking the behaviour of groups of consumers. Finding new audiences by the tracked behaviour of previous customers is nothing new, but the power of ML allows this to be done at scale, and in a privacy-secure fashion.

Neutral networks can trace the behaviours of audience groups thanks to huge data sets, evolving how marketers understand the purchase journey. AI models can then help predict future behaviour of audience groups going through similar life events, or with emerging interests. Messaging and advertising efforts can then be fine-tuned to best reach consumers depending on their predicted behaviour.

So far, the industry has been disproportionately focused on the shrinking pool of addressable inventory. Those who look beyond exclusively relying on IDs to predictive models that can reliably target non-addressable audiences will have a tremendous advantage in the post-cookie ecosystem.

Finding new audiences by the tracked behaviour of previous customers is nothing new, but the power of ML allows this to be done at scale, and in a privacy-secure fashion

What’s next for Yieldmo?

We’re always looking at how best to develop our products so our partners can run campaigns effectively and efficiently. To give a sneak peek at future developments, we’re working on expanding our custom models to include partner audiences with KPI models, or a customer defined KPI rank priority; incorporate better tracking behaviour of audiences in a privacy secure way; and support advertiser-specific companion audiences.

In the end, the more data we can ingest, the better our ML capabilities will become. We’ve already scaled our data capabilities an impressive amount to deliver seven million KPI predictions per second, but we need to continue these efforts to make our partners’ advertising campaigns successful.

The contextual advertising boom: What is it, and how can brands take advantage?