Getting To The Heart Of Messaging With IAS’s Jessica Miles

Getting To The Heart Of Messaging With IAS’s Jessica Miles

In this guest post Jessica Miles, Australia and New Zealand country manager at Integral Ad Science, discusses how advertisers can get to the heart of audiences on Valentines Day…

On Valentine’s Day, research has shown Australians are set to spend $415 million. According to the research, Australians will spend an average of $111 on gifts, with flowers, chocolate, and jewellery being the most popular Valentine’s items.

I’ve seen a lot of love, creativity, humor, and beauty in the latest Valentine’s Day campaigns of brands worldwide and at the heart of it all is making connections. In this article let’s explore how to get to the heart of content and target the right ad adjacencies.

Context and brand love

Advanced technology and solutions are available today to allow for full-page contextual analysis, which means understanding the true meaning of the page by accounting for nuances in context, language, semantics, sentiment, and emotional impact of the content.

When the technology enables you to scan the story in detail, keeping into consideration the sentiments and emotions in context. The URL or the headline alone won’t tell the full picture. An always-on brand safety and suitability approach help marketers identify brand-suitable environments while avoiding potentially damaging ones.

With this approach, brands are reassured that if and when something goes wrong, they have the best possible protection in place and are in front of any controversy before it unfolds.

Matching ads to sentiments and emotions

Let’s begin by exploring what these terms mean – the sentiment is the general mood of the page and is often inferred as positive, neutral, or negative.

Emotion is described as a feeling which can be caused by the situation that you are in, such as happiness, fear, disgust, sadness, surprise, etc. So why do sentiments and emotions matter when it comes to context? It matters greatly because brands sell to people, who have emotions and do make purchase decisions on how they feel about or perceive the brand or the product.

Brands do use feelings to get consumers to buy so it’s critical that technology that’s responsible for discerning content and context is able to effectively discern the emotions, sentiments, cultural nuances to capture the consumer’s frame of mind.

What if the technology was able to read the page as a human would and understand the mood and feelings contained in a piece of content? Would that not help advertisers keep emotions at the heart of their campaigns and ensure that the ads are well placed in the “right emotional context”?

For example, the goal of a Luxury car ad is to appeal to the reader’s sense of relaxation, luxury, and comfort — and so ads might be placed entirely outside of the automobile context and next to content that evokes those feelings.

This manner of semantic targeting lets the brand values resonate in the most appropriate emotional context.

Measuring sentiment and emotion

Advancements in machine learning and cognitive technologies, such as natural language processing, can now determine the sentiment conveyed on a given page at scale, enabling more suitable ad placement decisions.

Sentiment analysis offers a unique opportunity to take control of how a message is presented in various contexts. Rather than simply avoiding content, advertisers can choose how to proactively advertise alongside the content of varying sentiments.

In particular, these technologies analyse the full text and the relationships words have with one another in order to accurately comprehend the context of the page. The overall sentiment (positive, neutral, or negative) is understood along with the associated emotional classifications.

For example, amusement, love, and hope are different emotions that can be classified within positive sentiment, even if those specific words are absent.

In order to understand sentiment and emotions elicited by the text, a probabilistic approach using keywords in isolation will never be accurate. Appropriately leveraging the full range of sentiment and emotional classifications can drive significant value for advertisers.

Granular understanding of the emotion

It’s one thing to say a piece of digital content is positive but determining whether it’s focused on love or humour is something else. The same is true at the opposite end of the scale; with fear and anger both considered negative, yet still very different and sometimes effective emotions – think charity ads placed alongside shocking or tragic content to push a call-to-action.

Once again, the key factor here is context. Being able to steer towards or away from content based on its positive or negative nature is valuable for guiding decisions about the type of messaging brands should use. But when it comes to selecting which specific environments to target, more detail is required.

Vital to achieving this is a granular understanding of the emotion behind each word; and for those who thought semantic technology was only about context and wider sentiment, this is where the good news comes in. When powered by vast knowledge graphs, the advanced contextual barometers brands have come to rely on can map words to potential meanings in all the given context, giving precise emotional reading.

Brands need comprehensive real-time intelligence that enables precise ad matching for multiple contextual factors including emotion, at scale. For example, instead of setting the parameter of “positive sentiment” for a Valentine’s Day campaign, brands would be able to apply in-depth analysis that assesses different emotions tied to the romantic event, ensuring ads appear alongside content that will reach consumers likely to be interested in gift options while avoiding potentially harmful placements.

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IAS integral ad science Jessica Miles valentine's day

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