What is contextual advertising? Everything you need to know

By IBM Watson Advertising

Contextual advertising uses various factors to determine which content is most relevant to users when placing an ad. It targets potential customers by relying on context such as the content of a webpage, location or weather. Machine learning can take these pieces of information to deliver the right ad to the right users. For example, if a user is reading an article about wedding planning, the user might see an ad for wedding dresses on the page.

While advertisers have traditionally practiced behavioral targeting, that is, using a potential customer’s data surrounding their browsing and shopping habits, rising concerns about privacy have led advertisers to find alternative options. Advertisers no longer must rely on cookies or behavioral signals to deliver relevant ads. By using insights surrounding the context of the ad, companies can still create messaging that resonates with audiences. Companies are beginning to make this shift in how they approach their advertising, with contextual advertising projected to reach over USD 376 billion by 2027.

Why is context important in advertising?

Context is important because it provides advertisers with useful information about the type of content a user is interested in. Advertisers can then target them with an ad that allures the user with related content and messaging. 

While relevant behavioral data expires as consumers navigate an ever-changing environment, using context tells advertisers what users are interested in right now rather than relying on past behavior. Advertisers can use this to their advantage by delivering highly relevant and timely ads.

Companies may also struggle with ever-changing regulations and attitudes toward privacy and tactics that use cookies to inform them about a user’s online behavior. With this shifting attitude, advertisers are realizing they may not be able to collect data in the way they once did. In fact, four out of five technology challenges that companies cite when trying to personalize their customer experience are related to data. For companies ready to embrace a cookieless world and an environment where consumer needs are constantly shifting, contextual advertising is a way forward.

 

How does contextual advertising work and how to get started?

Contextual advertising uses AI and deep-learning algorithms to analyze content like text, speech, imagery and geolocation in real time. Predictive advertising tools like IBM Watson Advertising Accelerator analyze all of this data and the content a user is browsing to determine if a user will take a particular action like clicking your ad. The deep analysis provided by AI is like what a human brain would do when deciding where to place an ad manually, which helps ensure your ad placement is relevant, timely and of interest to the user. This also creates a more personalized experience for consumers, which is becoming increasingly important to consumers when deciding what brands they want to align with.

To get started, each contextual ad needs a unique landing page to help ensure there is a central place for driving conversions. Contextual advertising requires a high level of creativity and relevancy—and a solution like IBM Watson Advertising Predictive Audiences can help.

 

The importance of contextual advertising in a cookieless world

Contextual advertising is having a resurgence due to the impact of privacy laws like the GDPR and announcements made by Google to scrap third-party cookies—meaning advertisers will no longer be able to track users across multiple sites to target them.

With a desire for greater privacy online, contextual advertising is increasingly becoming a better option for advertisers. It’s privacy-friendly and you can still collect compelling data on consumers without the use of cookies. It may also help keep advertisers compliant while allowing for greater personalization—without being invasive.

 

What is the difference between contextual advertising and behavioral advertising?

Behavioral and contextual advertising doesn’t need to be an either-or decision; there’s a place for both. The main difference between the two is that contextual advertising targets context, that is, the environment in which the user is browsing and the topic and content of the page they’re viewing. On the other hand, behavioral advertising is more focused on the actions a user made before reaching the web page, whether it’s clicking a particular link, product page or article. Both kinds of advertising have their own benefits and can work together to achieve the desired result.

 

Benefits of contextual advertising

There are many benefits to contextual advertising for advertisers. Companies are beginning to implement tools to deliver higher levels of personalization based on the context of their advertisements such as weather, content and other factors. Below are some of the benefits of implementing contextual advertising across your organization:

 

Contextual advertising doesn’t require using cookies and personal information

It’s no secret that consumers are becoming increasingly wary of giving out personal information. In fact, in a recent survey from Startpage, it was found that 72% of Americans are “very concerned” to “extremely concerned” about their online privacy. Contextual advertising doesn’t require cookies to deliver relevant ads, which can help you spend your budget more effectively while targeting the right people.

 

Contextual advertising is easier to implement

Behavioral targeting is notorious for requiring vast amounts of data, which requires not only the right tools and technology to collect it, but a team to analyze it. Contextual advertising, on the other hand, focuses on predictions that AI makes based on trends and other insights that can make it an easier tool to implement.

 

Adding context leads to more relevant content

Even small personalization efforts can pay dividends. In a study done by Forrester, respondents with an immature personalization strategy saw a 6% increase in sales and a 33% increase in customer loyalty and engagement. Relevancy is becoming more important to consumers and 64% say it’s important that brands give them relevant, personalized offers. Knowing this, your strategy should reflect these changing consumer preferences.

Unfortunately, brands are still falling short of these more personal messages with only about 40% of consumers perceiving the communications received as relevant. Additionally, 45% of consumers said they would either not purchase or be less likely to purchase from an organization that failed to personalize the customer experience.

 

Context can be more telling than behavior

Past behavior is not always relevant to present wants and preferences. And with so much change happening regarding lockdowns and the ever-evolving state of COVID-19, consumers are rightfully shifting their habits to adjust to the new normal. While advertisers may feel anxious to keep up with these changing shopping habits, we have developed the IBM Watson Advertising COVID-19 Triggers solution, which can help advertisers adjust their strategy based on the course of the virus and what’s happening now.

Changes in weather or other external factors can also affect purchasing decisions. For example, a snowstorm approaching the Northeast will influence purchase behavior. As a result, advertisers can highlight relevant products such as shovels, gloves and hats to those in the geographic area the snowstorm is approaching.

 

Advancements in AI have improved context accuracy

Due to technological advancements, AI has become increasingly smart about analyzing page content and placing your ad in front of audiences who are more likely interested in seeing it, which can increase your number of leads and conversions. AI also removes the burden that your team is responsible for by virtually eliminating the manual work involved with segmenting audiences by identifying patterns and learning from past tasks.

 

Better weather targeting can drive sales

The weather is another important, but sometimes overlooked, component of contextual advertising. While the weather may seem trivial, you can gain a lot of insight into how a consumer will behave based on one’s location and weather. For example, a forecast of 50 degrees will drive a different behavior in MA than in Florida. IBM Watson Advertising Weather Targeting turns the relationship between weather location, consumer behavior and complex data sets into actionable, proven solutions for advertisers that don’t rely on third-party cookies.

 

Example of contextual advertising

 

           CVS uses contextual ads to reach 42 million consumers in moments

 

CVS came to IBM Watson Advertising looking to engage with consumers in high-risk flu areas through contextual ads. The goal of the campaign was to drive flu-shot vaccinations to help prevent people from getting sick.

With millions of Americans at risk of contracting the flu, CVS’s sponsorship of the AI-enabled Flu Insights with Watson tool on The Weather Channel app was an optimal method for CVS to drive contextual relevance. Furthermore, the solution effectively connected with consumers when and where it mattered.

Through the Flu Insights with Watson sponsorship on The Weather Channel app, CVS reached millions of consumers in critical planning moments. Results included 42 million unique visitors, 644 million total ad impressions and over 77% of module clicks via “Find Your Local CVS” messaging.

Final thoughts

IBM Watson Advertising offers a suite of contextual advertising solutions that are designed to automate complex processes, predict future behavior and optimize employees’ time—without the use of third-party cookies. Learn more about AI in advertising and request a demo.

 

 

The performance data discussed herein is presented as derived under specific operating conditions. Actual results may vary.

All client examples cited or described are presented as illustrations of the manner in which some clients have used IBM products and the results they may have achieved. Actual environmental costs and performance characteristics will vary depending on individual client configurations and conditions. Contact IBM to see what we can do for you.