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Organic Search Traffic Metrics Updated for AI and LLMs
AI and large language models (LLMs) are increasingly driving search now. Changes in how organic search results are generated mean that marketers need to rethink the metrics they use to measure search results.
AI and large language models (LLMs) are increasingly driving search now. Changes in how organic search results are generated mean that marketers need to rethink the metrics they use to measure search results.

These are metrics that marketers will want to focus on:
- Engagement metrics. Search results now provide more direct responses, so it’s even more important to measure user engagement – time spent on page, scroll depth and rates of interaction with content are pertinent items to look at.
- Key events. It’s important to consider key events such as newsletter signups and product reviews. This will aid in the alignment of reporting and business objectives.
- Attribution metrics. Conversions can happen over various channels, and LLMs can alter how the traffic is distributed to different channels. Using attribution models to better understand the impact on organic search, social media and other channels is helpful.
- Customer lifetime value (CLV). Shifting landscapes mean that it’s more important to understand the lifetime value of customers acquired over various channels to better understand the effectiveness of your strategies.
- Brand awareness metrics. How customers discover brands is changing due to LLMs, so assessing brand awareness is important. Insights can be gained through surveys, mentions on social media and search volume.
- Conversion rate optimization (CRO) metrics. There may be reduced search traffic from traditional organic search, so you’ll need to look at conversion rates for key actions, such as purchases and signups. Improved performance may be gained with A/B testing and landing page optimization.
- Referral traffic analysis. Traffic that is hard to attribute can result from LLMs, so it’s important to delve more closely into referral sources for traffic.
- Content performance metrics. Prioritize high-quality content by assessing content performance – looking at shares, backlinks and mentions.
- Search query insights. How users interact with LLMs and the types of queries they use an provide insight into your content strategy and SEO efforts.
- User feedback and satisfaction. Feedback from users, surveys and Net Promoter Scores can be used to assess user satisfaction with your content and the overall experience.