Measuring Visibility: Which Figures Show Whether a Business Is Found

Why is counting inquiries not enough?

Many businesses measure their marketing by a single figure: inquiries. That is right, because orders are what count in the end. But it has a drawback. Inquiries are the last link in a long chain, and they react late. When a competitor moves up in search or a channel dries up, it often shows in inquiries only months later, and then it is unclear why.

This guide answers the question: Which figures show whether a business is found by its customers, and how do you measure them with reasonable effort? We first clarify the term visibility and present two models that explain why searches are a good leading indicator. Then the visibility ladder arranges the metrics in four steps. At the end are the limits of measurement and a monthly review.

Inquiries tell you what worked yesterday. Visibility tells you what is coming tomorrow.

What does visibility mean, and how is it linked to inquiries?

Visibility describes how often and where a business is encountered by people who are looking for its offering or might need it. Online, this mainly means search results, the business profile in Google Maps, mentions on third-party sites and answers from AI assistants. Visibility is not reach. Reach measures how many people a piece of content reaches. Visibility measures whether the business shows up where its customers search.

The measurement chain from the article on measuring marketing success has four links: visit, inquiry, conversation, order. Visibility lies before the first link. It answers the question of how many people had the opportunity to visit the business at all. If you measure both, you see whether a decline in inquiries is due to a lack of visibility or to a website that does not convince visitors.

Why are searches a good leading indicator?

The first model comes from Hu, du and Damangir (2014). They examined how advertising affects car sales in the United States. To do so, they combined monthly sales, advertising spend and Google search volume for 21 vehicle models over 103 months, from January 2004 to July 2012. The number of searches for a model served as their measure of prepurchase interest, meaning the people who inform themselves before deciding.

Their result: advertising works through two separate paths. It generates interest, which shows in searches, and it converts interest into purchases. The two effects can differ in strength and develop differently over time. If you look only at sales, you can misjudge the effect of advertising. For a business, this translates into a simple distinction: visibility measures the first path, inquiries and orders the second.

The second model is share of search. It means the share that searches for your own name have of all searches for the names of the suppliers in a market. In 2020, the British advertising researcher Les Binet presented analyses for cars, energy suppliers and mobile phones at the industry association IPA. In all three markets, share of search was related to market share and ran ahead of it, for cars by up to a year. A follow-up study by the IPA with 30 cases from twelve industries in seven countries confirmed the relationship. Binet and the association stress that this is a correlation, not proof of cause and effect.

The visibility ladder: four steps, four metrics

From these models I derive the visibility ladder for small businesses. It has four steps, and each step requires the previous one. It complements the model from the article on visibility in AI answers with its stages found, understood, recommended by assigning a measurable figure to each step.

The ladder has a practical advantage: it shows where a weakness lies. Many impressions and few clicks point to unsuitable page titles or descriptions. Many clicks but hardly any searches for the company name suggest that visitors do not remember the business. Many searches for the name but no mentions by third parties point to a lack of evidence outside your own website.

Where do you get the figures?

Free tools are enough for the first three steps. The most important source is Google Search Console, a Google service that shows for which search queries a website appeared, how often it was clicked and what its average position was. The data goes back 16 months. How the reports are structured is described in the guide on understanding Google Search Console.

1. Separate search terms

   In Search Console, split search queries into two groups: with the company name and without. The first group measures step 3, the second steps 1 and 2.

2. Review the business profile

   In the Google Business Profile, the performance data shows how often the profile was viewed and how many calls, direction requests and website clicks resulted. How to maintain the profile is described in the article on the Google Business Profile.

3. Roughly estimate share of search

   In Google Trends, compare your own name with two to four competitors. The tool shows relative values from 0 to 100. For very small businesses the search volume is often too low; then only your own trend in Search Console remains.

4. Spot-check mentions

   Once a month, put the same five questions customers would ask to two AI assistants and note whether the business is named. Also count new reviews and mentions in trade media.

The fourth step is the hardest to measure. There are tools that automatically track mentions in AI answers. For a small business, a fixed sample is enough as long as it stays the same every month. The article on AI answers cites a finding that shows why this step matters: a large analysis by Kumar (2026), a preprint not yet peer-reviewed, found 11 percent for small and little-known brands compared with 73 percent for global brands.

Where are the limits of measurement? Two views

The first view considers visibility figures a distraction. Impressions and click-through rates are vanity metrics that look good and say nothing about orders. A business should only measure what reaches the till. In favor of this is that many agency reports shine with rising impressions while inquiries stay the same.

The second view considers them indispensable leading indicators. The work of Hu, du and Damangir (2014) and the analyses of share of search show that search interest runs ahead of sales. If you only measure orders, you cannot tell whether a decline is due to interest or to conversion.

I consider the second view correct, with one clear condition: visibility figures are only useful if they are linked to the measurement chain all the way to the order and if you know their weaknesses. A methodological warning comes from Zhang, Miao and Jiao (2026). Using 15,996 observations of search indices for sportswear brands in China, they showed that the same event made one platform or the other appear favored depending on the chosen baseline period and calculation method, in some cases with the opposite sign. Search indices are therefore sensitive to how they are analyzed.

• Same period: always compare months with the same month of the previous year, not with the previous month, because many businesses fluctuate seasonally.
• Same method: do not change search terms, test questions and competitors for a year.
• Read small numbers with caution: with 20 searches a month, 5 more or fewer are chance, not a trend.
• Separate the company name cleanly: if you do not exclude searches with your own name, you mistake awareness for findability.

A figure you cannot link to an order is a clue, not a decision.

The monthly review in 20 minutes

For measurement to stay part of everyday work, it needs a fixed date and a fixed form. I recommend a table with the four steps of the ladder and the inquiries, filled in once a month and compared with the same month of the previous year. It belongs in the metrics dashboard described in the article on a one-page metrics dashboard.

• Impressions for search terms without the company name: up, flat, down?
• Click-through rate for these terms: which three pages have many impressions and few clicks?
• Searches with the company name compared with the same month last year and with competitors.
• Mentions for the five test questions to AI assistants and new reviews.
• Inquiries and their sources from the measurement chain.
• One measure for next month that addresses the weakest step.

If you know which competitors rank ahead of you in search and why, you can act more purposefully. How to find this out from public sources is described in the article on low-effort competitor analysis.

What you can do this week

• Set up Google Search Console for your website if it is missing, or check access.
• Split the search queries of the past twelve months into two groups: with and without the company name.
• Note the views and actions of recent months in the business profile.
• Write down five typical customer questions as fixed test questions for AI assistants and ask them for the first time.
• Create a table with the four steps of the visibility ladder and the inquiries.
• Enter a fixed monthly date for the review in the calendar.

Conclusion: which figures show whether a business is found?

The guiding question was which figures show whether a business is found by its customers and how to measure them. Hu, du and Damangir (2014) show that advertising creates interest that is reflected in searches and that this interest can be measured separately from its conversion into purchases. Les Binet’s analyses of share of search show that search interest can run ahead of market share, without that proving a cause.

For a small business, this results in the visibility ladder with four metrics: impressions for search terms without the company name, click-through rate, searches with the company name and mentions by third parties. Measurement is monthly, compared with the previous year and always together with inquiries. Visibility thus becomes an early warning system that shows what will only reach inquiries later.