In this webinar, Oshen Davidson (Content Engineer & Researcher at AirOps) joined Josh Spilker (Content & SEO at AirOps) to show how AirOps workflows transform research, reporting, and content distribution.

Top 5 takeaways

1. Use AirOps workflows to research brand mentions in LLM responses. AirOps makes it easy to extract and analyze brand mentions and citations from Language Learning Models (LLMs) at scale.
2. Using workflows and grids allows for easy export, filtering, and deeper research.
3. Copilot simplifies workflow building—even for non-coders. Get help with code, explanations, and step creation, making advanced workflows accessible to all skill levels.
4. Context and visibility of brand mentions can be deeply analyzed. The workflows help distinguish between linked and non-linked mentions, and identify third-party influence in AI search.
5. Research workflows can be customized and repurposed for various content and reporting needs. Extracting key takeaways from reports supports content distribution, campaign planning, and internal sharing.

Check out the research reports Oshen has built using AirOps workflows.

Best practices and key learnings

Oshen and Josh revealed practical techniques to speed up research, improve reporting, and make content operations more efficient. Here are the key strategies that stood out:

Build scalable, repeatable research workflows

AirOps workflows automate the process of querying LLMs, extracting brand mentions, and tying those mentions to citations—making large-scale research possible.

Research becomes simple when you build workflows that can analyze hundreds of queries simultaneously. Teams can gather consistent data on brand visibility and capture both the frequency and context of mentions for deeper competitive insights.

• Use workflows to analyze hundreds of queries and gather consistent data on brand visibility.
• Capture both the frequency and context of brand mentions for deeper competitive insights.
• Export results for further analysis, reporting, or integration with other tools.

"You can get a lot of insights from this, and it saves you a lot of time... You can do it all in AirOps." — Oshen Davidson

Structure and export data for deeper analysis

The "write to grid" feature in AirOps organizes workflow outputs so teams can quickly filter, analyze, and share results.

Every data point collected through your research workflows gets stored as individual rows within the grid. This structured approach makes it easy to sort, filter, and distinguish between owned citations and third-party influence in AI search results.

• Store each mention, citation, and visibility type as a row for easy sorting and filtering.
• Distinguish between owned citations and third-party influence to better understand AI search dynamics.
• Export data as CSV for use in developer environments, machine learning applications, or even Google Sheets.

"Everything that is found and everything is collected as individual rows within the grid." — Oshen Davidson

Make advanced workflows accessible for everyone

Copilot in AirOps empowers non-technical users to build, document, and adapt workflows without needing to write code from scratch.

You don't need coding expertise to create powerful research workflows. Copilot helps you generate and explain code for workflow steps with simple prompts, making advanced functionality accessible to everyone on your team.

• Generate and explain code for workflow steps with simple prompts.
• Use Copilot to document and explain entire workflows for better collaboration and handoff.
• Start quickly with pre-built templates and reusable "power agents."

Repurpose research workflows for content and distribution

Research workflows aren't just for data collection—they can also extract key takeaways for content distribution, internal sharing, and campaign planning.

The same workflows that gather research data can be adapted to create content assets. Teams can summarize findings into digestible insights for emails, social posts, or internal updates, ensuring consistent messaging across channels.

• Summarize research reports into digestible insights for email, social, or internal updates.
• Adapt workflows to extract takeaways, create LinkedIn posts, or inform campaign strategy.
• Share outputs across teams to keep everyone aligned on key findings.

How to put these insights into practice

AI search is rewriting the rules for brand visibility and content measurement. To stay ahead, teams need scalable systems for tracking mentions, analyzing influence, and sharing insights across the organization.

Start by identifying your most pressing research needs—whether that's tracking brand mentions, analyzing competitor visibility, or measuring content performance. Then build or customize AirOps workflows that fit these specific requirements.

Use the grid feature to structure and export your data for deeper analysis, and let Copilot help you overcome technical barriers. Finally, extend your workflows beyond research to power content creation and distribution, maximizing the value of your insights.

Future-proof your content research with AirOps

AirOps transforms how content teams research, analyze, and act on AI search data—without requiring technical expertise. By combining powerful automation with flexible workflows and structured data, you'll gain visibility into brand performance while saving countless hours of manual work.

Book a strategy session to learn how AirOps can transform your content operations.