Reviewing SEMrush for generative AI monitoring: an off-site marketer’s perspective

Generative AI is changing how consumers discover and engage with brands. For off-site marketers, understanding how your brand, and your competitors, appear in AI-driven answers is becoming as important as tracking search rankings. While a handful of new tools are emerging to help with this, SEMrush has already introduced features that offer useful visibility into generative AI performance.

Here’s our review of SEMrush for generative AI monitoring, specifically from the lens of off-site content and perception management.

Strengths

• Visibility and perception insights:

  SEMrush makes it possible to see how brands are being surfaced in AI responses and, importantly, which cited pages are driving that visibility. This is valuable for identifying the role of press mentions, affiliate content, and third-party reviews.

• Regular refresh:

  The platform resets data every seven days. This means you get fresh visibility snapshots regularly, though you need to be mindful when building reporting — insights can change between the start and end of your analysis.

• Clean layout:

  The interface is clear, making it easy to interpret data without a steep learning curve.

• Price point:

  Compared to alternatives such as Similarweb, SEMrush is extremely affordable, which makes it attractive for teams testing generative AI visibility for the first time.

Limitations

• No export functionality:

  At present, data can’t be exported to Excel, which makes it harder to slice and dice results for deeper analysis.

• No API access:

  Without an API, the platform can’t yet connect to BI tools such as Looker, meaning you can’t automatically cross-examine SEMrush data with other off-site content inputs.

• No search function:

  Within the dataset, there’s no simple way to search for specific queries, which limits flexibility when analysing large volumes of information.

• Geographic filters not live:

  Country-level filtering is not yet available, though SEMrush has indicated this feature is coming.

Practical recommendations

• Manual reporting is a must:

  We recommend copying your key queries into your own manual reporting template to preserve a historical record, given the 7-day reset.

• Cross-check with AI directly:

  Always run a parallel test using incognito queries in ChatGPT or other AI platforms. This helps validate whether SEMrush’s tracking matches the real user experience.

• Use as a directional tool:

  At this stage, SEMrush is best used for directional insights rather than as a standalone measurement system. It can highlight where your off-site content is influencing AI, but more advanced workflows will need additional tools and manual checks.

Verdict

SEMrush’s generative AI monitoring is a useful, affordable entry point for off-site marketers who want to track brand visibility in AI outputs. While the limitations mean it can’t yet serve as a complete reporting solution, it offers meaningful insights into cited pages and brand perception. With future updates like country filtering and (hopefully) export and API access, it could become a more powerful cornerstone of generative AI monitoring.

This review is part of our ongoing exploration into tools and strategies for managing off-site visibility in the age of generative AI. To receive our full whitepaper on this topic, get in touch with the Planit team.