With the cookieless future looming large, we break down different types of targeting, the power of contextual targeting, and how optimization can supercharge your programmatic cookieless strategy.
What is Contextual or Cookieless Targeting?
What is targeting in programmatic platforms?
In programmatic marketing, targeting refers to the methods used to identify and reach target consumers or audiences most likely to be interested in the product or service an advertiser is selling.
What are the different ways platforms can target?
There are different types of targeting such as first-party data, third-party data, and one of the most common, cookies. First-party data is data that is directly collected from interactions with your consumers and audiences through your companies’ own site. Some examples of first-party data include demographics, purchase history, website activity, interests, behaviors, etc. First-party data has a direct relationship with the consumer (Treasure Data, 2021).
Third-party data is data you acquire from very large databases where it is bought and sold programmatically (Treasure Data, 2021). Cookies fall under the umbrella of third-party data. A cookie is a small piece of data stored on the user’s computer that helps a website keep track of visits and activity.
What is ‘context’ and what information does it use for targeting?
Context refers to a cookieless set of data points that factor into an ad placement’s ability to perform.
Contextual targeting is targeting based on the information available on the page or site of the ad space, rather than user data. Since it is based on what the consumer is currently engaging with, contextual targeting is successful in predicting what the consumer will engage with next.
Contextual targeting is gaining popularity as it is adaptable to an inevitable cookie-less future. With contextual targeting, the look and feel of every single ad placement is unique to the page and can be correlated even more closely with user behavior. It is the answer to the cookie-less future.
- seamlessly integrates your ads into relevant content users are already consuming
- offers precise attribution
- guarantees higher engagement
- offers greater cost efficiencies, especially in combination with Bidtellect’s context-driven optimization engine
- works on all formats: Responsive Native, Display, Video Units, and High Impact Units
What is Contextual or Context-Driven Optimization?
Optimization describes the algorithms that a bidder uses to determine bid prices, whether or not to bid, and how often to bid depending on the performance goals of a campaign. In other words, optimization describes ways to optimize an ad in order to get the best engagement in the most efficient way possible.
Programmatic optimization is the process of improving a programmatic ad campaign’s performance in real time based on data. It’s what makes programmatic advertising the most efficient use of your digital ad budget. With that being said, research shows that programmatic media buying now accounts for 85% of all digital ad spending (Strategus). If you haven’t already made the switch to programmatic, now is the time.
Platforms optimize performance in a variety of ways from cookies to creatives. On the simplest level, optimizing for brand and content works well most of the time; that is what most b2b companies start off with-hire a web3 copywriter and optimize all the creatives, including website content. This strategy often works itself towards the right target audience, but may take time. Context-driven optimization is optimization without using user data or cookies. Contextual optimization is Bidtellect’s key differentiator that uses contextual signals to optimize performance.
How Does Bidtellect Use Context?
Bidtellect has been utilizing context since our founding. We began as a native specialist demand-side platform nearly a decade ago. With native ads, we necessarily had to evaluate the contextual information on the page to create an ad that blended seamlessly into its environment, in addition to reaching performance goals.
Bidtellect’s Contextual Targeting: Bidtellect has consistently pushed our technology forward, and now utilizes a combined contextual approach within our platform: the industry’s best third-party contextual integrations plus our unique proprietary contextual targeting solutions: first-to-market context demographics targeting, categorization and keyword targeting, interest targeting, and inventory quality targeting. Bidtellect also teamed up with Bombora to combine our granular ad placement-level targeting with Bombora’s robust B2B taxonomy for a unique first-to-market B2B contextual targeting tool.
Bidtellect’s Context-Driven Optimization: Bidtellect’s contextual offering goes beyond targeting solutions and into optimization. Optimization maximizes spend, ROI, and performance for advertisers completely using context-driven technology. Contextual optimization is the foundation of Bidtellect’s bidding technology.
AARDvark – Bidtellect’s Automatic Algorithmic Rate Determination tool – factors multiple context data signals simultaneously including: page-level contextual signals, domains, individual publisher ad placements, devices, times of day, and days of week to evaluate auctions and make bidding decisions according to 14 selectable optimization goal types. In other platforms, bid factoring falls entirely onto traders.
Why Choose a Contextual or Cookieless Strategy with Bidtellect?
Context uses the information on the page rather than audience data to deliver the most relevant ads to consumers. Bidtellect consistently outperforms data targeting strategies with our contextual strategies – not only within our own platform, but when testing against other platforms, as well.
Let us help you optimize on your performance goals!