In the ever-evolving realm of marketing, contextual advertising has been an essential piece of the puzzle, with its roots woven into the fabric of the internet for over three decades. It can be traced back to 1994 when Hotwired.com published the first banner ad by AT&T. It was a risky venture into the unknown as like the internet itself, no one knew what to expect and how audiences would respond. To the advertising world's surprise, it proved a triumph. With a 44% click-through rate (CTR), it became a pivotal moment that has changed the landscape of digital advertising ever since.

Fast forward to today, contextual advertising may seem like a relic of the advertising world, given the speed of modern advancements, yet it has been mirroring the digital age’s technological developments from the beginning. Harnessing artificial intelligence (AI) and machine learning (ML), it has upped its game. Now making precise predictions about user preferences, people are getting the right information when it counts the most. Given the demise of third-party cookies this year, the digital terrain is transforming, prompting a resurgence in contextual advertising, but this time with much larger boots to fill.

This three-part series will direct its attention to contextual advertising, taking a look at the basics, weighing it up against other targeting methods and understanding why it has become increasingly important. This blog will relay the groundwork, breaking down the fundamentals of what contextual advertising is, how it works and some common misconceptions. As this journey progresses, the next chapters will look further, delving into a comparative analysis between behavioural and contextual targeting, while unravelling the pros and cons for both the consumer and marketeers. Finally, there will be a focus on the fading reign of third-party cookies and a look at the future trajectory of contextual advertising.

What is contextual advertising?

Quite simply, contextual advertising is a strategy that ensures display ads align with web page content, increasing the relevance of the ad placement. Take for instance a user reading an article about sustainability, based on the topic, contextual ads can show them content related to renewable energy or a subscription to a sustainability newsletter. Since the content of the ads is related to the content the user is reading, the targeting strategy is called contextual.

How does Contextual targeting work?

Advertisers need to understand what the campaign content is about and what it intends to match against in order to align ads onto relevant web pages, requiring keyword or topic-based parameters to be identified first. By doing this, the ads will be eligible to match with web pages that align with the keywords or topics that were chosen. This process uses natural language processing (NLP) and ML algorithms which analyse content in real-time to understand the true meaning of what the web page is about.

At Smartology, our approach is slightly different - we intend to match client thought leadership content with contextually relevant articles on publisher sites. Unlike static message-focused banners, our clients have the unique opportunity to showcase their content within the context of articles, providing users with access to insightful knowledge that adds value to their journey.

Smartology also uses NLP and ML to analyse publisher content, but what sets us apart and positions us at the forefront is the ability to understand the meaning of client advert content. This elevates our matching capabilities beyond the confines of conventional keyword parameters. Enhancing the precision in ad placement means ads seamlessly align with users' current interests, fostering less disruption and maximum engagement. Not only this, Smartology challenges the one-size-fits-all approach predefined by keyword or topic-based technology, enabling a tailored matching profile for each ad.

Contextual advertising aims to blend advert content with the overall user experience, naturally aligning with people's interests and therefore increasing the ad’s relevance. This challenges advertising's unfavourable reputation of being invasive, as it intends to add value to a user’s journey, rather than be a nuisance. The Harris poll revealed that 79% of consumers in the UK preferred to see contextually relevant ads, going to show just how effective contextual advertising can be in enhancing people’s online journey.

Some misconceptions

Since contextual advertising’s resurgence, there has been a growing rhetoric, creating various myths within the marketing industry about the techniques used. Let's squash these myths by having a closer look at them:

It’s a blunt tool

All too often advertisers perceive contextual targeting to only go as far as a keyword tool, they think of a classic case like someone reading about running will get served a Nike ad.

But as discussed, contextual targeting can go beyond that. Companies like Smartology have the capability to understand the true meaning of client thought leadership content and publisher articles through the use of AI, enabling a precise match that increases relevance for the user. Since the technology understands semantic topics and phrases, rather than static keywords, it has the intelligence to know that electric vehicles are related to Tesla which is related to Elon Musk etc.

Contextual targeting keeps becoming more sophisticated in its ability to parse language as a result of advancements in AI. We will continue to see these two technologies develop in tandem for the foreseeable future, leading to greater accuracy in matching more granular content to articles - and that's without third-party data!

It’s more expensive and less cost-effective

There is a narrative that audience targeting better meets the needs of marketeers given that you can target a specific demographic. However, it's known among the industry that targeting consumers is far less black and white - intertwining consumer passion points, interests and motivations. You would think it would be a common assumption that reducing consumers to audience data points is ineffective, yet this narrative stubbornly persists.

According to a study with the Dentsu network agencies, contextual advertising saved advertisers 29% on a CPM basis, and it can increase an advertiser's ROI by up to 30% compared to other methods. Having a targeting method that allows audiences to see relevant ads will generate more user engagement, rather than going for a broader audience that cannot guarantee high-value impressions.

Contextual data is inferior to third-party cookie data

Third-party cookies track users' browsing habits, serving ads based on their previous online behaviour; this data has become an essential tool for advertisers in recent years. But it’s made people perceive contextual data as less effective than that of cookies as it can’t personalise marketing the same way.

While behavioural and contextual targeting uses different methods to increase ad recall, it does not mean one is more effective than the other, rather they are counterparts that are useful for different reasons. Contextual targeting is foundational in scaling up marketing strategies, it allows for audience layering and recency, hence ads are more well-received and viewers are more receptive to them. The most significant challenge advertisers face today is creating a cookie-free advertising strategy. Contextual targeting has been the saving grace as third-party cookies are set to end in the coming months.

The next chapter will delve further into the misconception of behavioural targeting as the superior tool. It will closely examine the contextual vs behavioural debate, unpicking the benefits, shortfalls and challenges of both and what the demise of third-party cookies will mean for advertisers and consumers. So stay tuned!