Three modern ways to measure publications impact (and how to use them)

Beyond the usual: Advanced metrics for scientific publications

Traditional metrics like impressions, downloads, and citations are no longer enough to capture the true impact of scientific publications. Today, biopharmaceutical companies need sharper tools to understand how their research is discovered, surfaced, and reused across the digital landscape. Here are three modern measurement techniques that can transform your publications strategy, and how Woven Health Collective can put them into practice for you.

#1 Google Trends: Tracking real-world interest

What it is:

Google Trends lets you track how often specific terms are searched on Google over time and across regions. For publications planners, this provides a window into public and professional interest in a disease state, therapeutic category, or scientific concept.

How to use it:

1. Enter your term of interest at Google Trends.
2. Choose between “Search Term” (for a specific phrase) or “Topic” (for a broader concept).¹
3. Analyze the trend line to see if interest is rising or falling.
4. Compare multiple terms to see which concepts are gaining traction.
5. Use the geographic breakdown to identify where interest is strongest.¹
   
   

Challenges:

Scientific terms may have low overall search volume, and results can be extremely sensitive to the exact wording you use.² That’s why Woven’s Data and Analytics team collaborates with our scientific communications experts to select the right terms and interpret the data in context, ensuring the insights are relevant and actionable.

#2 Measuring content exposure in AI models: Capturing value from generative search engines

What it is:

As large language models (LLMs) like ChatGPT, Gemini, and Perplexity become primary gateways to information, it’s crucial to know if and how your publications are being cited or summarized by these tools. The challenge is that users may get answers directly from the AI, bypassing your original source and reducing the perceived distribution of the content.

How to use it:

1. Track AI-driven traffic: Use Google Analytics 4 (GA4) or similar tools to create custom channel groups or segments for AI referrals. This lets you see which pages are being surfaced by AI tools and how much traffic they generate.^3,4
   
   
   • Analyze “AI traffic” channels: Compare users, sessions, and engagement from AI sources versus other channels to benchmark and track content use by AI models.
   • Review specific landing pages to see which content is most frequently referenced by AI tools. Segmenting AI-driven traffic from paid search or display advertising is a crucial step in calculating ROI.
2. Monitor engagement: Assess session duration, bounce rate, and conversions specifically from AI-driven visitors to measure the impact quality.^3,4
3. Emerging tools: Some analytics platforms now offer LLM observability, letting developers see how often content is surfaced in AI responses.
   
   

Challenges:

Much like the rise of smartphones required web designers to change their approach to user interface, LLMs will change content organization to favor AI ingestion. Generative Engine Optimization (GEO) is an emerging set of techniques to proactively format content for ingestion and use by AI models.

Directly measuring publication citations in LLM outputs can further quantify the reach of content, expose GEO opportunities, and help define user preferences. These practices are still evolving, but tracking referral traffic and engagement from AI tools is a practical first step. Woven’s analytics team can help set up, manage, and interpret these reports, ensuring you understand your content’s reach in the AI era.

#3 Measuring derivative use and content reuse

What it is:

The true influence of a publication is often seen in how it is reused in presentations, third-party reports, educational materials, and derivative works.

How to use it:

1. Backlinks: Use SEO tools to track where your publication is linked or cited online.
2. AI-powered content tracking: Advanced AI tools can now monitor where your content (text, images, data) appears across the web, even if modified.⁵ Techniques include image/video matching, text fingerprinting, and digital watermarking.
3. Custom data science solutions: For more granular tracking, Woven’s data science team offers highly flexible and rapidly configurable monitoring of specific articles for reuse in presentations, lectures, or reports, using automation to scan public repositories, conference proceedings, and even social media for derivative use.^5,6
   
   

Challenges:

There is no universal standard for tracking content reuse, especially for non-traditional formats. So manual and automated methods must be combined. Woven offers solutions to help clients map the full journey of their scientific content, from publication to real-world adoption.

At Woven Health Collective, we integrate these advanced measurement techniques into your publications strategy from the start. Our team combines scientific expertise with data analytics to ensure you not only publish but truly understand and amplify your impact.

If you’d like to learn more, we are always happy to talk and share our experiences. Email me at christy.king@wovenhc.com, and we can find a time to meet.

References

1. https://www.liveplan.com/blog/starting/google-trends-keyword-research
2. https://www.reddit.com/r/bioinformatics/comments/737uy7/something_like_google_trends_for_scientific_papers/
3. https://blog.coupler.io/how-to-track-and-analyze-ai-traffic/
4. https://infotrust.com/articles/analyze-ai-driven-traffic-google-analytics/
5. https://fadel.com/resources/ai-for-marketers-how-to-use-ai-across-the-content-lifecycle/
6. https://hdsr.mitpress.mit.edu/pub/enheggqr