Effective ad placement and targeting

Introduction

Cookie-free and tracker-free browsers are coming and that’ll make relevant ad placement and user targeting a lot harder. You’ll be dealing with less information than ever before.

Problem

In the light of data privacy laws (such as GDPR), how can intent-targeting platforms maintain their business and create meaningful results? How can we target the users and justify ad spend if we have limited user information?

It’s time we shifted our focus to AI solutions.

We had to find different parameters to base the ad placement on. The idea was to use ML algorithms to analyze the content on the page and actually rely less on user information and third-party data.

Solution

We created a digital advertising platform that provides contextual analysis. It provides granular insights about the content on a webpage. What this tells you is what type of content it is, its sentiment, keywords and brands, organizations or people related to it. 

That makes deciding whether to place an ad on a specific website easier. It also allows different analysis on various types of content without breaking user privacy.

On top of that, the platform provides performance with the lowest level of cost and memory footprint compared to traditional advertising platforms while supporting analysis in a multilingual environment.

The platform provided essential and functional capabilities for advertisers in our tests.

  • Content categorization

Predict content category based on IAB Tech Lab’s content taxonomy and get information if the page is suitable and safe for ad placement.

  • Sentiment detection

Detect content sentiment and use its score as one factor for choosing where to place an ad.

  • Keyword extraction

Extract keywords and their corresponding contexts for setting up ad targeting campaigns.

  • Entity detection

Detect different entities (persons, brands, organizations etc.) and use it to refine more ad targeting campaigns.

Result

Our AI-powered digital advertising platform has delivered promising results, addressing the challenges of ad placement and targeting in a cookie-less world. Key outcomes include:

Improved Relevance: Ads placed in suitable and safe contexts have led to increased relevancy and engagement, resulting in higher conversions.

Enhanced Targeting: Insights from sentiment analysis, keyword extraction, and entity detection have refined ad targeting campaigns, reaching the right audience segments with precision.

Cost Optimization: Advertisers have optimized their ad spend by leveraging ML algorithms and allocating budgets effectively based on content categories and sentiment.

Privacy Compliance: Our platform respects user privacy by analyzing webpage content instead of relying on user data, ensuring compliance with data privacy laws.

Efficient Performance: The platform demonstrates superior performance with low cost and memory usage, enabling better resource allocation and improved ROI.

Smart Tip

Advertising will have to stop relying on third-party data and make use of first and zero-party data. Adding ML to the mix will help you make sense of it and allocate your budget accordingly.

Smart Fact

“Half my advertising spend is wasted; the trouble is, I don’t know which half.” John Wanamaker

“With this platform, SmartCat prepared us for the future of advertising.”

Product Manager in our client’s company

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