Using Perplexity to Map Your Competitors' AI Share of Voice

Your marketing team tracks competitors in Google. You monitor their ad spend, their blog output, their ranking positions. But if you are not tracking their presence in AI-generated answers, you are missing the channel where the next generation of buyers is forming opinions. Perplexity makes this research fast and surprisingly deep.

Why AI Share of Voice Is Different from Traditional SOV

AI share of voice measures how often your brand appears in AI-generated answers compared to your competitors. It is not the same as search volume share, social mentions, or display impression share.

The key difference is intent depth. When someone asks Perplexity a question, they are usually further along in their research than when they type keywords into Google. They want a synthesized answer they can act on. The brand that appears in that answer has a direct line to a high-intent buyer.

Traditional share of voice spreads across dozens of result pages and ad placements. In AI search, you either appear in the answer or you do not. This makes the competitive dynamics easier to measure and the stakes higher for every query you miss.

How Perplexity Constructs Competitive Answers

Perplexity pulls from live web sources and synthesizes them into a narrative answer. It tends to favor content from industry publications, review platforms, and authoritative blogs. When you run a query like "best marketing automation platforms for mid-sized US companies," the brands that appear are the ones with the strongest coverage in the sources Perplexity trusts.

This matters because it means you can reverse-engineer why a competitor appears. You look at Perplexity's cited sources, find where your competitor is covered, and identify the specific placements driving their AI presence.

Building Your Competitive Query Set

Before you start, build a list of queries that map to your market category. These should be the questions your buyers actually ask when they are researching solutions.

A good query set for competitive SOV research has four types of queries. Category comparison queries are the backbone: "best [category] tools for [use case]." Recommendation queries add specificity: "which [category] platform do US marketing teams prefer." Problem-solution queries capture earlier-stage research: "how do I solve [specific marketing challenge]." And budget or tier queries capture segment level: "enterprise marketing automation platforms" or "affordable email marketing for startups."

Aim for 20 to 40 queries. You want enough to see patterns, not so many that the research becomes unwieldy on the first pass.

Running the Competitive Research in Perplexity

1. 1
   Create a Tracking Spreadsheet

   Set up a spreadsheet with columns for: query, brands mentioned (all of them), your brand position, competitor brand positions, and sources cited. You will fill this in as you run each query.

2. 2
   Run Each Query and Record All Brands

   Paste each query into Perplexity and record every brand that appears in the answer, not just the top result. Note the order they appear in, since first mention typically signals the strongest association.

3. 3
   Capture the Source Citations

   For every query where a competitor appears and you do not, open the source citations. Record which publications, review platforms, or blogs Perplexity is pulling from. This is your gap analysis in action.

4. 4
   Run Variations for Key Queries

   For your highest-priority queries, test at least two phrasings. "Best email marketing tools" and "top email marketing platforms for US companies" may return different brands. Variations reveal where your positioning is narrow.

5. 5
   Calculate Share of Voice by Category

   Once you have run all queries, count how many times each competitor appears across the full query set. Divide by total possible appearances to get a rough SOV percentage per brand per category.

Here are examples of the types of queries you should run in Perplexity:

Interpreting Your Competitive Data

After running your queries, you should see clear patterns. Some competitors will appear across almost every query. Others will show up only in specific niches. Some will not appear at all.

The gap between Competitor A and your brand in a chart like this is not mysterious. It reflects third-party coverage volume, the depth of content on their owned properties, and how consistently they appear in the review platforms and publications that AI models trust. Each of these is something you can build.

Turning Competitive Insights into Your AEO Strategy

• ✓Identify the 3 to 5 queries where competitors appear and you do not, these are your highest-priority content gaps
• ✓List every source citation that consistently drives competitor mentions and build a presence there
• ✓Look for queries where no competitor owns the answer, these are fast-win opportunities
• ✓Note how competitors are described in AI answers and compare it to how your brand is described
• ✓Build a 90-day plan that targets the most impactful gaps first, not the easiest ones
• ✓Re-run your competitive audit quarterly to catch shifts before they compound

Frequently Asked Questions

How is AI share of voice different from Google share of voice?

Google SOV measures how often your brand appears in search results pages relative to competitors. AI SOV measures how often your brand is mentioned in synthesized answers. AI SOV is currently harder to track systematically but tends to correlate more directly with high-intent consideration, since buyers reading an AI answer are usually evaluating options, not just browsing.

How accurate is Perplexity's output for competitive research?

Perplexity is excellent for this research because it pulls from live sources and shows citations. You should treat each session as a sample, not a census. Run queries in multiple sessions and across different times of day to get a more representative picture. It will not give you statistically perfect data, but it will reveal the competitive dynamics clearly enough to act on.

How often should I run competitive AEO research?

A full competitive audit every quarter is a solid cadence for most marketing teams. If you are in a fast-moving category or launching a new product, run a focused competitive check before and after major moves. The competitive landscape in AI search can shift faster than in Google because new coverage and new content gets picked up more quickly.

What if a competitor is dominating every query?

That is a data-rich situation. You now know exactly which third-party sources are driving their dominance. Prioritize building presence on those same platforms, but also look for query categories where they are weaker. Most dominant brands are strong in core category queries but thin in niche use-case queries. That is your entry point.

Should I compare Perplexity results with ChatGPT and Claude?

Yes. Each model has different training data and citation tendencies. A competitor might dominate in Perplexity but be weaker in ChatGPT. Running your competitive query set across at least two AI tools gives you a more complete picture and helps you prioritize which platforms matter most for your specific buyer audience.

Aeotics tracks AI brand visibility across 12 AI models, updated weekly. See how your brand compares →