TownNews.com has launched a new program that helps news and media companies harness the power of audience data to present users with content that meets their individual interests—boosting user engagement, and increasing page views, time on site and ad revenue.
"The way a user interacts with your digital product can give insights into what content they find compelling," said Brad Ward, president and CEO of TownNews.com. "For example, if a user frequently clicks on tech-related articles, it's an indication that they might respond to technology business news and tech product reviews."
The new program, called iQ Engage, converts these "signals" from users—answering a poll question, clicking a keyword, saving an article, browsing a specific section, etc.—into actionable audience segments.
This data enables sites that use TownNews.com's BLOX CMS (the news industry's leading content management platform) to serve up content recommendations that are customized to each user based on their individual behavior profile, so they'll browse deeper and see more content—and ad impressions.
A unique profile is created for each visitor, and users can be tracked across multiple devices, including desktops, tablets and phones. Profiles can be created and updated for both anonymous and logged-in users.
"Because iQ Engage is fully integrated with BLOX CMS, we can really take advantage of all of the user interactions that happen on a partner site," Ward said. "When a user fills out a form, 'likes' an article or enters a contest, that information can be used to supplement their profile."
The "Recommended for you" feature marshals browsing data and machine learning to find content that will be of interest to individual users. It then displays a selection of targeted content in a block that can be placed almost anywhere on the site: at the end of each article, on the home page, or the front page of each section.
In customer beta testing, visitors for whom behavioral data has been collected—and who are presented with these behavioral content recommendations—view nearly four more pages and spend eight more minutes on-site in a given browsing session.
Madison.com piloted the iQ Engage recommendation feature for Lee Enterprises, and reports excellent early results. The site has added the behavioral content recommendations block to its home page and most article pages.
"We've seen a significant jump in all key engagement metrics since our launch in February," said Tim Kelley, who serves both as digital director for Madison.com and digital engagement director for Lee Enterprises. "Time spent per session has doubled and we're up to nearly six pages per visit even at this early stage."
TownNews.com clients using iQ Engage are also seeing a massive drop in bounce rate (the number of visits in which a person leaves a website after viewing only one page)—seven percent with recommendations vs. 70 percent without.
"On pages featuring iQ Engage, Madison.com's bounce rate—the number of people who abandon our site after viewing a single page—has plummeted from 38 percent to less than 5 percent," Kelley said.
"It's a great new feature, and we expect even better results as TownNews.com continues to develop and refine the technology underpinning iQ Engage."
iQ Engage can also use behavioral signals to create dynamic experiences for different audiences. Examples include:
- Repeat visitors can be presented with fewer ads, while drive-by traffic from Facebook and Twitter is served a larger number of programmatic advertisements. This gives loyal readers a faster, more streamlined experience, and improves monetization from social media referrals.
- House ads promoting "All-Access" subscriptions to a newspaper's print edition and website can be shown only to users who haven't already subscribed, saving valuable page real estate for other ads or alternate content.
- A "Subscribe to our newsletter" widget can be displayed when a user isn't already a subscriber, but hidden otherwise.
"The trick is to show each visitor content that really matters to them," Ward said. "To do that, we've created a sophisticated predictive algorithm that factors in signal strength (some user behaviors are more predictive than others), content popularity, recency and context—along with many other data points—to present a selection of articles that will be really engaging to that specific user."
"Greater user engagement will impact some of your most critical metrics: bounce rate, session duration and pages per session," Ward said.
"By affecting those, web publishers can boost the most important metric of all—the bottom line."