Some PR pros can be obsessively analytical (a good thing!). And with AI, the opportunities to analyze data in seconds (albeit with flaws) seem limitless.
Now with AI, the PR and news ecosystem is shifting again under the influence of LLM-powered search and fragmented audience attention. However, some PR measurement KPIs remain foundational while metrics evolve. Keep in mind that core KPIs typically hold steady for two to three years for year-over-year measurement, and the metrics beneath them change much more quickly as technology enables richer, faster insight.
Several foundational KPIs remain non-negotiable in 2026, including:
1. Share of Voice (SoV)
Still the clearest snapshot of standing in a category. New, AI-assisted metrics include:
Share of Search Influence (SoSI): Tracks how earned media shifts brand search volume, category query associations and visibility within AI-driven search and LLM results (e.g., Google’s “AI Overview,” Perplexity). Search trends now show how much a story is shaping the narrative—not just how well-known it is. For example, after a funding announcement lands in TechCrunch and VentureBeat, branded search for “Acme Robotics pricing” might jump 38% in six days while AI Overview would start summarizing Acme’s differentiator (“modular robotics for manufacturing”)—words pulled directly from earned coverage.
Narrative Share/Topic Ownership Score: Uses AI to analyze which themes and topics people associate with the brand versus competitors. Your competitor might’ve dominated the “AI safety” conversation last quarter, but after your founder’s op-ed and two podcast interviews, LLM clustering shows 27% of the category discussion now ties “AI safety frameworks” to your brand.
2. Message Penetration
Core messaging must appear clearly and consistently. Updated metrics include:
AI Semantic Message Match Score: Uses LLMs to check whether media coverage captures the core meaning of key messages—even when the wording changes. What if your key message is “zero-trust data mobility” but only 40% of articles use that phrase? AI analysis can show 78% captured the meaning through phrases like “secure data flow” or “controlled data movement."
Message Density per Article (MDpA): Measures how many times a core message appears within a story and how prominently (headline → intro → body), distinguishing central narratives from throwaway mentions. In a profile piece, if your positioning appears in the headline, first paragraph and twice in quotes, you’ll receive an MDpA score of 5/5 that signals the article strongly reinforces your core story.
3. Sentiment Analysis
Tone is now both a performance metric and a risk indicator. AI-enabled metrics include:
Emotion-Weighted Sentiment Score (EWSS): Goes beyond positive/neutral/negative to classify emotional intensity (confidence, fear, skepticism, excitement) using emotion modeling, which uses AI to identify and measure emotions in content, such as news coverage, social media posts, or customer feedback and differentiates mild criticism from high-risk negativity. If two reviews call a product “solid but early,” while one includes language like “I worry about long-term stability”—this will trigger a high “fear” score. EWSS identifies which article could undermine trust more aggressively.
Influence-Adjusted Sentiment Impact: Accounts for how influential each outlet is, since a negative mention in a major publication has a bigger impact. A mildly negative comment in a Gartner analyst blog will outweigh 10 positive social posts, because analyst authority multiplies the sentiment effect.
4. Quality of Coverage / Prominence
Authority and placement drive impact. Updated metrics include:
LLM-Prominence Scoring (Headline → Lede → Body Index): Uses AI to quantify where and how early a brand appears in coverage, generating a nuanced prominence score instead of a simple “mentioned/not mentioned” flag. A story in Fast Company mentions your brand once and 12 paragraphs below the title, while another story mentions you in the headline and the lede. Prominence scoring quickly shows the headline placement is substantially more impactful than the lower-body mention.
Authority-Weighted Impact Score (AWIS): Combines outlet authority with prominence to highlight the placements responsible for the majority of perception shaping. A single Wall Street Journal quote contributes 42% of a total weekly impact score, more than 15 mid-tier tech blogs combined.
These enhancements transform familiar KPIs into sharper tools that capture visibility, clarity, tone and authority with far greater precision.
A few additional KPIs remain part of the measurement stack, but the way they are scored is changing. Raw counts are becoming less important than context, quality and behavior.
The following KPIs remain in play:
5. Volume of Coverage (Story Count)
Still useful, but interpreted through the lens of diversity and strategic balance. Updated metrics:
Coverage Diversity Index (CDI): Measures how varied your coverage is across formats, verticals, regions and audience segments to ensure you’re not over-relying on a single channel. Say you secure 20 hits in a single week and CDI reveals all came from tech verticals. After securing business and regional coverage, CDI might rise from 0.4 → 0.77, indicating a healthier narrative spread.
Channel-Weighted Volume Score (CWVS): Weighs coverage counts based on the strategic importance of each channel, so high-value formats carry more impact than low-tier mentions. Three podcast interviews rank higher than eight small blogs because your audience of engineers engages more deeply with long-form audio.
6. Referral Traffic From Earned Media
Measures what actually drives action, not just what gets clicks. Updated metrics:
Behavioral Quality Score (BQS): Measures the depth of engagement PR-driven visitors show through time on page, scroll depth and multi-page visits. A Forbes story might send 1,100 visits, but visitors bounce quickly. A niche developer forum sends 90 visits, but they might spend four minutes on site and click into your docs. BQS shows the small outlet is the real driver of your pipeline.
Conversion Path Influence (CPI): Identifies how often PR-attributed sessions touch high-value pages and contribute to movement toward a lead or sales opportunity. PR-driven visitors who read your interview might also view your pricing page 22% of the time—and become one of the top contributors to early-stage pipeline activity.
7. Engagement Metrics
Moves past likes and follows to measure the quality of sharing and discussion. Updated metrics:
Influence-Weighted Engagement Score (IWES): Measures engagement quality by weighting interactions based on the authority and reach of the people amplifying your coverage. A technical influencer with 80,000 followers shares your article, but generates only 12 comments. However, because they are high-authority voices in your category, IWES ranks this as your most valuable engagement of the quarter.
Conversation Activation Rate (CAR): Tracks how often coverage sparks meaningful discussions—threads, comments, debates quotes—rather than passive engagement. Imagine your founder interview sparks a 74-comment discussion on LinkedIn about sustainable AI. CAR captures this as a high-value outcome even though impressions were modest.
The next set of KPIs did not meaningfully exist just a few years ago but are becoming essential due to AI, shifting search patterns and the rising importance of trust and momentum.
8. Earned Search Impact (ESI)
Connects PR to search dominance. ESI captures how earned media changes what audiences see when they search for a brand, its competitors, or its category—across both traditional and AI-driven search.
Example metrics:
LLM Snippet Recovery Rate (LSRR): Measures how often your brand or narrative appears in AI-generated search answers following earned media hits. Before a major launch, AI search results rarely feature your brand. But after a series of analyst briefings and earned stories, your product appears in 4 of 10 AI-generated summaries for “best DevOps tools for ML ops."
Query Intent Shift Score (QISS): Monitors how earned media influences the questions and topics people search, revealing changing intent. If searches shift from “What is Acme?” to “Acme integrations” and “Acme pricing”—this reveals increased commercial intent driven by earned coverage.
9. Credibility Signals / Trust Indicators
Trust becomes a primary competitive advantage. This KPI measures the depth and importance of human validation of a brand. Example metrics:
Verified Expert Endorsement Score (VEES): Measures how often recognized experts, analysts or credentialed authorities reference or validate your brand. If two analysts and a university researcher reference your findings in their own work, VEES might reveal a measurable shift in authority.
Fact-Check Accuracy Ratio (FCAR): Tracks the percentage of fact-checks or verification checks that confirm your claims versus inaccuracy flags. If journalists review your claims and find no discrepancies (resulting in a 100% accuracy score), this will reinforce trust for future announcements.
10. Narrative Velocity
Quantifies story momentum. Narrative velocity measures the speed, breadth and directional momentum of a story as it travels across platforms and communities. Example metrics:
Cross-Channel Acceleration Rate (CCAR): Measures how quickly a story jumps from its first appearance into secondary platforms like social, forums, newsletters or community spaces. For example, your founder’s comment in a Bloomberg story jumps to LinkedIn first, then Reddit and then three industry newsletters within 48 hours. This shows rapid spread of a message.
Narrative Reproduction Frequency (NRF): Tracks how often your story is retold, reframed or repackaged by third parties, including journalists, creators and LLMs. For example, a metaphor used in a keynote (“AI is the new seatbelt”) appears in five articles, two podcasts and a YouTube explainer—even though it was said only once. NRF measures that spread.
The PR function is no longer defined by clips, impressions or even sentiment alone. It’s now defined by influence that can be traced, measured and replicated. But the technology is only as powerful as the strategist wielding it. The brands that will rise next year will be the ones whose PR leaders understand which signals matter, how narratives move and how to build reputational equity that algorithms can recognize.
Lindsey Bradshaw is a freelance PR pro who works with B2B and consumer tech startups.