How to Make More Strategic Decisions With Contextual Data
In its essence, contextual data helps you understand more about your users so you can deliver more personalized experiences to them. For media brands and publishers, contextual data provides deeper insight into onsite behaviors and is described by Gartner as “any relevant facts from the environment,” incorporating any behavioral data collected using:
- Website engagement
- Form fills
- Survey responses
- Paywall submissions
- Social media interactions
- IoT devices
- Localized markets
- User preferences
Put another way, contextual data helps you go beyond just a lead’s name to understand what industry they work in, if they are using another solution like the one you offer and what type of content they prefer. It differs from behavioral data often collected via cookies, such as websites visited and time spent on page. Publishers use the broader market to delve into the deeper meaning behind the initial information they have collected about their customers, and they use those findings to create big picture strategies that improve site experiences and advertising opportunities and that open more doors for revenue-generating tactics.
Contextual targeting: built with zero- and first-party data
Contextual data is very similar to both zero- and first-party data.
Zero-party data is intentionally submitted user data provided by consumers when they fill out forms, respond to surveys and select unique preferences when interacting with your website. First-party data is behavioral data that publishers collect as users browse through content and different web pages across your site. Both types of data are very popular in the publishing space, particularly with the looming elimination of third-party cookies in 2023.
Publishers pool zero- and first-party data together to build their audience profiles and segments. These profiles improve how sites are optimized and personalized, increasing the chances that users will spend more time on the site. Additionally, you can use contextual data to create contextual advertising campaigns and increase advertising revenue for the business.
Publishers can use progressive profiling to collect more contextual data about their users. Progressive profiling targets users based on their history with your website. If a user has provided details like their name and email address in an earlier visit, they won’t be asked those questions on future visits. Instead, the forms will ask for more details about things like their favorite topics to read about, so you are collecting more rich context every time a user returns to your site.
Build rich audience segments to create powerful lookalike parameters
More brands are following the lead of publishers to build detailed audience profiles. They then deploy more targeted and more meaningful interactions with users by using the audience profiles to personalize the overall site experience for those users. Digital publishers have spent the past decade optimizing paid content experiences, and there’s growing demand to replicate that formula to personalize ads.
By pairing together contextual data with zero- and first-party data identifiers, publishers can produce lookalike segments to find unknown users whose interests best align with their own audience profiles. They then use these lookalike segments for themselves to deploy personalized ads designed to resonate with the intended audience. Success is measured by analyzing the impressions and clickthrough rates to identify how many people engaged with those ads and followed through to the publisher’s site.
Use current events and localized issues to optimize featured ads
Localized events and trending issues can influence the content you publish and the types of ads you deploy. This is an especially helpful tactic if your publication focuses on local news and activities. Any upcoming events on the calendar should factor into your pricing and promotion strategy. Offer special deals and discounts that best align to the context of that particular event.
Weather is also an important piece of contextual data. Audiences are looking for information about these incoming weather events; by targeting those prospective users with relevant ads and messaging, you can use these types of events to acquire more engaged users.