How are you measuring AI share of voice? Our competitors are dominating ChatGPT recommendations and we need to catch up

Your analysis methodology is solid. Here’s how to interpret and act on these results.

On sample size:

40 prompts is a good starting point for directional insights. For statistically robust tracking, I recommend 100+ prompts across different intent types:

• Informational (“What is X?”)
• Comparison (“X vs Y”)
• Recommendation (“Best X for Y”)
• Problem-solving (“How to solve X?”)

What drives AI share of voice:

Based on my analysis across hundreds of brands:

1. Third-party authority (40% of influence) - Wikipedia presence, G2/Capterra reviews, industry publication mentions. AI triangulates from sources that aren’t you talking about you.

2. Content comprehensiveness (25%) - Depth and breadth of your content on relevant topics. AI prefers citing thorough sources.

3. Brand positioning clarity (20%) - How clearly you define what you do and who it’s for. Fuzzy positioning = fuzzy recommendations.

4. Recency signals (10%) - Fresh content indicates relevance. Outdated content gets deprioritized.

5. Technical accessibility (5%) - Content structure, schema markup, crawlability.

The uncomfortable truth:

Competitor A probably isn’t doing anything magical. They likely have better third-party presence and more comprehensive content. The gap is addressable, but not overnight.

We went through this exact exercise 8 months ago. Here’s what actually moved the needle:

What worked:

1. Wikipedia presence - We didn’t have a Wikipedia page. Competitor A did. Getting one (legitimately, with notability) was a 6-month project but massive impact.

2. Review site optimization - Aggressive campaign to get customers on G2 and Capterra. AI systems heavily weight these platforms.

3. Comprehensive pillar content - Created 5 definitive guides on our core topics (5,000+ words each, exhaustive coverage). Became go-to citation sources.

4. Expert quotability - Our CEO started getting quoted in industry publications. Those quotes show up in AI responses.

5. Consistent messaging everywhere - Audit found inconsistent descriptions across web. AI was confused about what we actually do.

What didn’t work:

• Generic blog posts (too thin to be citation-worthy)
• Paid content placements (AI seems to weight earned coverage higher)
• Technical SEO changes alone (necessary but not sufficient)

Our results:

Share of voice went from 28% to 52% over 8 months. Still behind the leader, but competitive.

Analytics perspective on measuring AI share of voice:

The measurement challenge:

Manual prompt testing is valuable but time-intensive. For ongoing tracking, you need automation.

Tools we evaluated:

1. Am I Cited - Best for monitoring brand mentions across AI platforms. Tracks ChatGPT, Perplexity, Google AI Overviews, Claude. We use this for weekly reporting.

2. HubSpot AI Share of Voice Tool - Good for competitive benchmarking, analyzes across GPT-4o, Perplexity, and Gemini

3. Profound - More enterprise-focused, detailed sentiment analysis

4. Manual audits - Still do monthly deep-dives with custom prompts

Our tracking framework:

• Weekly: Am I Cited monitoring for mention frequency
• Monthly: Manual audit of 50 prompts with sentiment analysis
• Quarterly: Full competitive analysis with 150+ prompts

The metric we report to leadership:

“AI Share of Voice Index” - our mention rate divided by top competitor’s mention rate. Goal is to get above 0.8 (within 80% of leader).

PR perspective here - this is becoming a major part of our strategy.

The AI-PR connection:

AI systems heavily weight earned media coverage. The same PR efforts that build traditional brand awareness also build AI share of voice.

What we’ve changed:

1. Targeting AI-cited publications - We analyzed which publications get cited in AI responses and prioritized pitching those

2. Expert positioning - Getting executives quoted in industry articles. AI loves pulling expert quotes.

3. Original research - Publishing original data that others cite. Creates a citation cascade.

4. Wikipedia strategy - Working with a Wikipedia consultant to ensure our company page is accurate and comprehensive

Data that convinced our CEO:

We found that brands mentioned in publications AI frequently cites (Wikipedia, Forbes, TechCrunch) had 2.3x higher AI share of voice than brands with similar revenue and traditional SEO presence.

PR is now directly tied to AI visibility metrics, not just traditional media impressions.

B2B context since the OP seems to be in that space:

AI share of voice matters differently in B2B:

Our buyers aren’t asking “best CRM” - they’re asking specific questions like:

• “What CRM integrates with SAP and has SOC 2 compliance?”
• “CRM for financial services with custom workflow automation”
• “Enterprise CRM with European data residency”

The niche advantage:

For specific queries, you can dominate even against larger competitors. Competitor A might win “best CRM” but we can win “[specific use case] CRM.”

Our strategy:

1. Identify the specific queries our ideal customers ask
2. Create definitive content for those narrow topics
3. Build authority specifically for our niche

Results:

Overall share of voice: 25% (behind leaders) Share of voice for our ideal customer queries: 65% (leading)

Don’t try to win everything. Win where it matters for your business.

Product marketing angle:

The positioning clarity problem:

I audit AI responses about brands professionally. The #1 issue I see: AI can’t clearly articulate what companies do.

Prompts like “What does [Company] do?” return vague or inaccurate responses because:

• Website messaging is unclear
• Different sources describe the company differently
• No consistent value proposition across platforms

The fix:

1. Craft a single positioning statement that can be quoted directly
2. Ensure it appears verbatim on your website, LinkedIn, Crunchbase, G2, everywhere
3. Train AI by repetition - the more consistently you’re described, the more consistently AI describes you

Test it yourself:

Ask ChatGPT “What does [your company] do?” Compare the response to how you want to be described. The gap is your positioning clarity problem.

Companies with clear, consistent positioning have 40-60% higher share of voice than companies with muddled messaging, even with similar content volume.

Sharing our systematic approach to improving share of voice:

The 90-day playbook we used:

Days 1-30: Audit & Foundation

• Complete AI visibility audit (100+ prompts)
• Identify top-cited competitors and analyze why
• Audit brand consistency across platforms
• Set up Am I Cited for ongoing monitoring

Days 31-60: Content & Authority

• Restructure top 20 pages for AI citability
• Launch 3 comprehensive pillar content pieces
• Begin G2/Capterra review push
• Pitch 5 industry publications for coverage

Days 61-90: Scale & Optimize

• Monitor early results in Perplexity (fastest feedback)
• Iterate content structure based on what gets cited
• Expand review site presence
• Launch expert quote campaign

Our results:

• Starting share of voice: 22%
• After 90 days: 38%
• After 6 months: 51%

It’s not rocket science - it’s systematic execution of known best practices.

Running an agency focused on this, I’ll share common mistakes:

Why brands fail to improve share of voice:

1. One-time project mentality - They audit, make changes, then stop. Competitors keep pushing. Share of voice is a continuous race.

2. Ignoring third-party presence - They optimize their website and wonder why nothing changes. 40% of influence is off-site.

3. Generic content - Creating content AI won’t cite because it’s not comprehensive or authoritative enough.

4. Inconsistent monitoring - They check quarterly instead of weekly. Miss trends and competitor moves.

5. Impatience - Expect results in weeks when it takes months. Give up before momentum builds.

The brands that win:

• Treat AI share of voice as an ongoing program, not a project
• Balance on-site and off-site investment
• Monitor weekly, report monthly, strategize quarterly
• Commit to 6-12 month timelines

The difference between 35% and 65% share of voice isn’t luck - it’s sustained focus.

This thread has been incredibly valuable. My action plan is now clear.

Key insights I’m taking away:

1. Third-party authority is 40% of the battle - Our under-investment in PR and review sites is the biggest gap

2. Positioning clarity matters - Testing “What does [company] do?” revealed our messaging is inconsistent

3. Systematic approach beats one-time efforts - The 90-day playbook format resonates

4. Niche focus can win - We can dominate our specific use case queries even if we can’t win broad terms

5. Ongoing monitoring is essential - Weekly tracking, not quarterly audits

What I’m proposing to leadership:

Immediate (this month):

• Set up Am I Cited for continuous monitoring
• Audit brand consistency across all platforms
• Test positioning clarity via AI prompts

90-day sprint:

• G2/Capterra review campaign launch
• 5 comprehensive pillar content pieces
• PR push targeting AI-cited publications
• Weekly share of voice tracking

6-month goal:

• Move from 35% to 55% share of voice
• Reach 70%+ on our niche use-case queries
• Close gap with Competitor A from 2x to 1.3x

The framework for addressing this is much clearer now. Time to execute.