In this post, we look at some of the feature solutions that contextual data companies make available to advertisers.
All of these features are derived from crawling web pages to understand what they are about.
These companies provide a variety of services including video player size targeting.
This is important because it allows advertisers to serve ads on the larges video player size available for the targeting parameters.
Weather triggers create opportunities to target or exclude targeting based on the current weather conditions.
For example, if it’s raining outside it may be a great time to serve an ad for hot cocoa.
If it’s snowing, serve an ad for snowchains. If it’s over 85 degrees serve up an ad for sunscreen.
Predicted or viral content allows the advertiser to be on unforeseen, but very important content that is currently viral.
This happens by looking at social shares, publish data, and algorithmic analysis.
Finally, sentiment analysis helps advertisers target ads where the content is positive, or exclude ads where sentiment is negative.
This is particularly useful for product and brand targeting. If you’re Toyota, you want to run ads on pages that are positive towards your brand, and exclude targeting to pages that are slamming your cars.
These tools create a very nuanced approach to advertising that makes it viable for brands to precision target ads to ultimately drive more sales and leads.