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Less than a decade ago, contextual was poised to dominate online advertising—delivering on the promise of providing relevant ad content to the consumer at exactly the right time. Over the past several years, the industry has taken a long and costly detour down the audience/behavioral path, only to hit what is increasingly looking like a dead-end due to regulatory, privacy, technical, and other issues. Now, the pendulum is rapidly swinging back to contextual.
Contextual: The Once and Future King
As a recap: contextual targeting is the practice of advertising to individuals based on content they’re currently choosing to engage with. Contextual itself isn’t a new form of advertising, it has long been used in magazine and newspaper advertising, placing relevant ads next to articles on related topics. Today, contextual enables marketers to target specific types of web content on which to display their advertisements. And this, all without user consent or reliance on personal information gathered from demographic, geolocation, or behavioral data.
Rather than tracking cookies and personal data, this can all be accomplished via highly accurate categorization and understanding of the content on a specific URL (or specific ad placement on a page). When a web user visits a given page, information about the URL (or specific ad placement IDs) is passed along to an ad server or supply-side platform (SSP) which will match that URL/ID to advertisements from campaigns targeting related content topics, categories, or keywords to available ad inventory. This is all handled programmatically—allowing for high throughput real-time bidding (RTB).
GDPR, updates to the ePrivacy Directive, the “creepy” factor of retargeting, consumer concerns about hacking of their online profiles, and cookie blocking are all having an impact on audience-based marketing trends. Limitations and risks associated with personalized advertising continue to mount, and additional regulations threaten to further undermine the effectiveness of audience-based tactics.
There are a number of reasons why advertisers are shifting efforts and budgets away from audience targeting and towards contextual. They include:
- Contextual targeting doesn’t require consent. There are no barriers of entry and advertisers don’t rely on a user action–that may not occur. There are no additional overhead costs for maintaining records for user consent or any risk of accidentally contacting or misusing data.
- Contextual targeting doesn’t rely on third-party data. New and existing regulation will make it increasingly difficult to use third-party data in 2019 and beyond. Reduced reliance on third-party data can save advertisers money and may actually glean better results.
- Contextual doesn’t have the creepiness factor associated with audience-based methods. Users are not bombarded with advertisements targeting some other personal data point such as a one-off web search, geolocation data gathered on them, or a like/mention/conversation on social media that was believed to be “private”.
- Contextual delivers the right ad content at the right time to the right audience. Always. Advertisers find that contextual targeting can be more engaging as advertisements closely match the web users current intent—and even intent that may not yet exist from historical personalized data or a customer persona (i.e. new interests, shopping for car, etc.).
- Contextual targeting reduces risk associated with data misuse or non-compliance compared to audience-based methods. Additionally, concerns over massive fines for non-compliance or misuse of data under new regulations has contributed to the shift back to contextual targeting. As GDPR outlines, fines can be up to €20 million or 4% of the total worldwide annual revenue for the prior financial year, whichever is higher. And regulatory bodies have made a point early on in showing they’re serious about compliance. Just this January, Google was fined €50 million by CNIL, France’s data protection regulator, for failing to comply with GDPR.
Transitioning From Audience-Based Methods to Contextual Targeting.
How do you overcome the contextual challenges to take advantage of potential benefits to ad relevance, engagement, and lift—while reducing reliance and risk associated with trackers in this post GDPR world?
Before investing time and money, Ad Tech platforms and advertisers should outline content taxonomies and begin performing A/B tests and pilot programs to measure results. Achieve a proof of concept on a small budget—then scale. Starting early is key, as it will take time to map taxonomies to specific interests and user segments.
Requirements for Contextual
In order to maximize ROI on ad spend and meet advertiser’s expectations, effective contextual targeting will require the following:
- Artificial intelligence, machine learning, and natural language processing. In recent years, we’ve seen giant leaps forward in AI and machine learning. These advances have resulted in major improvements—delivering highly accurate categorization and understanding of web content across a growing number of languages. Machines can now achieve a high level of understanding and better identify content topics, sentiment analysis, and even nuances such as homonyms. For advertisers and Ad Tech platforms to deliver on contextual targeting, they must invest in—OR identify/partner with companies who can deploy and continue to develop these AI-based technologies.
- Highly accurate and highly reliable content categorization. Content on the web is changing continuously. In order to be successful, both platforms and advertisers will require that ads are served (and budgets spent) only on the most accurate webpages and relevant content. Systems must not only maintain exceedingly high accuracy, but high reliability as well—as outages are missed opportunities, equating to budget wasted and revenue lost.
- Brand safety guarantees. The content where ads are served must be consistent with the brand’s image and brand safety requirements.
- Measurements and transparency. As mentioned earlier, testing and measurements will play a critical role in achieving contextual adoption rates. Platforms must be able to provide measurable performance and accuracy to sell advertisement space to prospective marketers. Advertisers, meanwhile, will need to justify their ad spend and be able to project ROI for contextual campaigns.
Next Steps For Successful Contextual Targeting Strategies
zvelo partners with Ad Tech platforms on the buy and sell side, as well as agencies and brands to help enrich data and augment contextual targeting efforts. Delivering the market’s leading AI-based web content categorization and brand safety services, zvelo offers unmatched granularity with nearly 500 unique content categories, full IAB taxonomy support, as well as flexible deployment options. Additionally, thanks to ongoing advancements in natural language processing and lemmatization techniques, we support over 200 languages with over 99.9% classification coverage of the ActiveWeb.
If you’re a brand, agency, or DSP transitioning away from audience-based targeting—now is definitely a good time to be evaluating how contextual can improve lift and efficiency, while reducing cost. If you’re looking for steps to take and guide for how to substitute contextual targeting for your audience-based methods—stay tuned for our next blog.