For years, PR professionals and brand leaders have relied on Share of Voice (SOV) as the ultimate yardstick for competitive PR success. The logic was simple: whoever owns the loudest megaphone and the biggest slice of media coverage wins.
But the megaphone is changing shape.
In the era of AI search, B2B buyer and investor audiences are less likely to click through standard links on Google and far more likely to ask ChatGPT, Perplexity, or Google AI Overviews to summarize complex queries for them. In this new landscape, relying solely on traditional media share of voice is like bringing a paper map to a GPS fight. It’s only one piece of the PR measurement puzzle, and it only measures coverage volume, not real influence.
If your PR strategy is still measuring success by counting raw article clips while ignoring how AI models and humans alike perceive your brand, you’re missing the bigger picture.
So, how do we fix it? Let’s break down what Share of Voice actually means today, why the old way of measuring it is failing us, and how brands must adapt to track true visibility in an AI-driven world.
What is Share of Voice?
Share of Voice is the percentage of all media hits about your company or brand relative to your competitors. If you were to round up every article mentioning either your brand or your competitors and create a pie graph, how big a slice would your brand get? That number is your traditional SOV.
When asked why they’re devoting time and effort to PR, many companies say “brand awareness.” However, brand awareness is notoriously hard to quantify. Traditional SOV provides a way to examine media coverage at a deeper level and evaluate whether your brand is referenced enough in material directly related to your industry. Analyzing a brand’s share of voice also provides tangible data to support ROI evaluations and strategic planning.
How do I calculate media share of voice?
To calculate share of voice, first determine your competitive set and time range. From there, count every piece of coverage across that competitive set, including the company you’re evaluating, during that time range. The coverage secured by your company, divided by the group’s total coverage, is your share of voice.
You can always measure share of voice manually. However, there are several tools that help with the process. Software suites like Cision and MuckRack make it easy to track these numbers automatically across thousands of digital publications.
How should I use share of voice for PR strategy?
Share of voice can do more than just illustrate how you stack up against your biggest competitors. Digging into the data that makes up your SOV can help with planning and goal-setting, adjusting outreach mid-campaign, and communicating success overall.
- Setting Benchmarks: Gaining a better understanding of where your brand sits today is essential before considering any change in strategy or tactics.
- Spying on Competitor Strengths: If you find competitors gaining coverage for certain types of announcements or activities that you haven’t communicated externally before, it can help guide your own content strategy.
- Refining Media Targets: If a competitor has a larger SOV, digging into their coverage can provide direction for new media outlets. If your competitors are seeing more earned media success than you are, it might also indicate that your message or outreach strategy needs an adjustment.
- Communicating PR Success: Tracking and sharing results is essential if you want clients or executives to continue investing money into PR efforts. Business leaders, especially those in the B2B and SaaS space, make decisions based on hard data and numbers, so the more data-driven context you can provide, the better.
What is missing from media share of voice?
Calculating share of voice can be very helpful in measuring the baseline output of PR efforts; however, the results can be very one-dimensional. After all, it’s only one metric.
One major issue with traditional SOV is that it only measures the volume of coverage, not the quality or context. It doesn’t automatically take into account sentiment, where the brand name appears, how many other companies were mentioned in the piece, or a variety of other qualifying factors.
For example, there could be a negative, crisis-driven story in a major publication for your brand that syndicates to dozens of other media outlets and earns millions of potential impressions. Consequently, you’ll own a massive part of the conversation among your competitors. In reality, owning the share of voice in that instance was more detrimental to your brand than helpful.
There could also be moments when your brand’s share of voice is lower than desired, but the media placements you did secure are incredibly strong. Depending on your overall business goals, a hundred brief mentions in a laundry list of competitors means significantly less to your brand than a deep, dedicated feature story or a highly targeted piece of coverage in a niche trade publication specific to your industry.
PANBlast uses our proprietary Story Score metric to help communicate the value of each piece of coverage.
Shifting to Quality: Measuring Key Message Pull-Through
Because raw volume numbers can be so misleading, modern PR teams must look beneath the surface of an article count. This is where key message pull-through comes in.
It’s no longer just about if your brand was mentioned, but how it was framed. When you secure a piece of media coverage, are your core value propositions actually reflected in the final text? If your company is a cybersecurity firm focusing heavily on “zero-trust architecture,” but your media hits only refer to you as a generic “IT software company,” your traditional SOV might look healthy, but your narrative strategy is failing.
Measuring message pull-through means evaluating your earned media clips for specific, pre-determined messaging points. This calculation tells you what percentage of your total coverage actually drives your core narrative home. Measuring this is crucial for two reasons:
- For Humans: It ensures that prospective buyers walk away from an article actually understanding your unique value proposition.
- For AI: LLMs learn from the context around your brand name. If your key messages are repeatedly pulled through in high-quality articles, AI models learn to associate your brand with those specific topics and solutions.
Share of Voice in the AI Search Era: Visibility & Penetration
As the media landscape evolves, the way we think about share of voice has to evolve with it. The rise of AI-driven search engines has fundamentally changed how audiences find information, giving rise to a new metric: AI visibility.
AI models ingest massive amounts of authoritative media coverage to generate answers for users. Brands need to start measuring their visibility within specified prompts that matter to their business. When a B2B buyer asks Perplexity, “What are the top enterprise SaaS tools for data compliance?” or when an investor or potential employee queries an AI about your industry’s outlook, does your brand appear in the generated summary?
However, you can’t just cross your fingers and hope an AI cites you. Building AI visibility requires a targeted approach:
- Targeting high-impact data sources: AI engines place a higher weight on crawlable, topical content. PR teams must identify which sites are driving the AI’s visibility for their specific target prompts, then heavily prioritize engaging those sites.
- Measuring AI visibility: Instead of just tracking a static pie chart of media clips, brands should measure their visibility inside AI responses. If you test your core buyer prompts across ChatGPT, Copilot, Perplexity, and Google AI Overviews, what percentage of those generated answers cite or recommend your brand versus your competitors? That is your share of AI visibility.
Solving the Modern PR Measurement Puzzle
Navigating this new era means moving past vanity metrics and tracking what actually impacts your bottom line. At PANBlast, we build bespoke, outcomes-focused PR programs specifically designed for emerging and high-growth B2B SaaS and tech brands. From uncovering deep data insights to securing media real estate to auditing and optimizing your visibility in critical AI search models, our team acts as a true extension of yours.