DemandScience has introduced Content-IQ, a new proprietary platform designed to help B2B companies improve how their content appears in search engines and artificial intelligence (AI) systems.
According to the company, Content-IQ helps organizations move away from producing large volumes of content without clear results and instead build structured content strategies that generate measurable business impact.
The platform combines several DemandScience capabilities into a single system. These include AI Visibility Optimization, Content Architecture and Strategy, and Web Personalization, all aimed at helping companies strengthen their digital presence and connect marketing efforts directly to revenue outcomes.
At the center of Content-IQ is DemandScience’s patented content opportunity scoring technology. The system analyzes how topics are connected across the web and how buyers search for information. Based on this analysis, it recommends structured pillar-based content frameworks that organize related topics into interconnected clusters. This approach is intended to build stronger authority online compared with publishing isolated articles.
DemandScience CEO Derek Schoettle said many organizations are facing a “content effectiveness crisis,” where large volumes of content fail to deliver measurable business results.
“As AI systems increasingly determine what information gets seen and trusted, content that is not structured properly for algorithmic authority can easily disappear,”
Schoettle said.
The company’s recent performance marketing benchmark report highlights the challenge. It found that 25 percent of marketing budgets are wasted on initiatives that fail to produce results.
The report also revealed that 76 percent of organizations create content without verified buyer signals, while 81 percent say half or less of their content contributes to measurable pipeline impact.
Instead of focusing only on individual keywords, Content-IQ maps how real buyers explore topics online. The system then translates those patterns into content clusters and internal linking strategies that help improve both search visibility and AI discoverability.
This approach allows content to appear not only in traditional search results but also in AI-generated answers and AI Overviews produced by large language models.
Content-IQ operates through a three-step process. First, it focuses on visibility, ensuring content is structured so it can be discovered by search engines and AI systems.
Second, it helps organizations understand engagement by tracking how target accounts and customer personas interact with content across a website.
Finally, the system supports real-time activation. When high-value audiences engage with specific content, the platform automatically personalizes website messaging and experiences to match their interests, helping companies respond instantly rather than analyzing results weeks later.
DemandScience has already begun deploying Content-IQ with enterprise clients. In one internal test, the company applied the methodology to its own website using B2B display advertising as a pilot topic.
After identifying the most authoritative topic clusters and publishing a set of 12 related articles, the company reported a significant improvement in search visibility. Within four days, the average keyword ranking for the cluster improved from position 85 to 34, with several keywords reaching Page 1 results and appearing in AI-generated search summaries.
DemandScience says the new platform is designed to help B2B marketers adapt to an environment where AI increasingly influences how online information is discovered and prioritized.