How contextual, attention and creative data unlock ad relevance for brands

For starters, there’s a highly fragmented media landscape and a seemingly infinite amount of ads and places to put them. Added to that, the industry is constantly reshaping itself based on signal loss from privacy, as well as legislative changes and technology updates. 

The current approaches can limit a brand’s scale and impact, distort the view of the customer profile and lead to low ad relevance and wasted spend. Too often, marketers are employing outdated methods of targeting by following people based on past behaviors instead of reaching them based on their current behaviors. All of this creates a growing matching problem between advertisers and their target customers.

Why contextual is more effective when leveraged with other data

Contextual advertising is rising in popularity as a solution to this industry change. The idea of using context as a signpost for the mindset of the consumer (and therefore their likely receptiveness to the ad) is a solid notion, but in practice, it can fall down. 

The reason is that marketers are not always accurate at guessing where to place their ads. Context can be used in a way that is overly simplistic or prone to individual or historical bias. Selling running shoes? Target running keywords. Selling perfume? Target beauty contexts. While these may be a starting point, they are often limited in scale and constrained to the obvious, causing brands to miss out on other potentially high-performing placements. But, branch out too far and perhaps risk not reaching category buyers at all. All this makes the delicate balance between reach and effectiveness hard to attain. 

This challenge is amplified by the lack of a reliable, non-sparse and predictive feedback loop on ad relevance, leaving many brands wondering if their ad is reaching people in the right mindset or not.

Bringing contextual, attention and creative data together for effective ads

To solve the matching problem, it’s important to consider what goes into ad exposure. There’s the context (where the ad is placed), the creative (the ad itself) and the consumer response to that context and creative combination (the attention it receives and any subsequent actions taken).

To expand on how these three categories work together, more platforms and tools are using advanced AI that goes past simple classifications and into categories, topics, keywords, sentiment, moods and more. This analysis provides a deep understanding of the content being viewed. Others use the same technology to understand and adapt the ad’s various creative elements: the advertiser, the vertical, the product, the images, the copy, colors, scenes and so on. Lastly, by measuring the consumers’ response to the context of the content and the creative together in real time, brands can link attention to downstream effects.

By fusing this data together into a unified datastore and predictive engine, these tools enable marketers to deliver ad experiences that resonate with consumer mindsets at any given moment.

Finding new audiences via endemic and non-endemic matches

While brands will of course still advertise in those contexts that are endemic and intuitive (like an ad for athletic apparel on a fitness website), the real magic happens when they’re shown all the other places they should put their ad. This is validated by showing the consumer response (via attention) was higher than average. For example, the athlete apparel brand may discover that their ads outperform others on a non-endemic website like a travel blog because consumers like to wear athleisure in transit.

This technology also opens up a whole new world around creative optimization. Perhaps certain treatments (like a beach scene versus a mountain scene) resonate in different contexts, or perhaps by moving its branding forward in a video, an ad would capture and retain attention better. 

With data as the divining rod for finding and delivering against additional contexts, brands can seize opportunities for further reach and new verticals to align with.

Responsive technology allows brands to adapt to trends in real time

No two pieces of content are identical, and no two creatives are the same. This uniqueness can drive anything from small to large changes to the attention an ad receives. Perhaps changes to a product shot, the imagery or even the call to action can tip the scales. 

Marketers are also tapping into an ever-changing cultural zeitgeist. For example, Taylor Swift became associated with the NFL last year due to her relationship with Travis Kelce, people jumped onto the “very demure, very mindful” conversation and Oasis announced a comeback tour. All of these enhance the potential connections between consumers and brands by opening new avenues.

This is why it’s important to be nimble, have a responsive approach and be equipped with the right technology. Using AI to analyze billions of data points allows for predictions and insights into potential performance. Equally crucial is the ability to measure and optimize in real-time, ensuring ads are most effective in the contexts where they resonate the most. The key lies in understanding and leveraging the data available to make informed decisions.

In an over-cluttered advertising landscape, using the cutting-edge technology available helps cut through the noise and deliver greater alignment and value. Ushering in a new generation of digital advertising that thrives on meaningful data helps brands achieve that precious balance of reach and effectiveness, ultimately bringing value to all parties in the ecosystem.

Sponsored by GumGum