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Article3 min read

Yandex Metrica Introduces Industry Benchmarks: How to Tell If Your Site Slipped or the Whole Market Did

The new Metrica report lets you compare your metrics against industry standards. I explain how to select a comparable group and avoid mistaking an average value for a mandatory sales target.

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Traffic has dropped. Did ads perform worse, did an error appear on the site, or are shoppers simply searching for such products less frequently? Without an external reference point, it is easy to confuse these causes and waste budget fixing the wrong problem.

On September 18, 2026, Yandex announced the Metrica report "Average Industry Indicators." It allows you to compare your own data with anonymized industry metrics, including traffic and stages of the commercial funnel. The report is available at no extra cost; you must enable access to market reports in the settings.

First, choose who to compare against

The report allows you to filter by site type, country, niche, and size. Selecting the group requires care. A small store selling specialized components and a mass-market universal catalog may exhibit different buyer behavior even within a broad retail category.

It is useful to record the comparison conditions you selected. If you change them every month to achieve a more favorable result, the report will no longer show accurate trends. An unsuitable group can also create unnecessary alarm where the business is actually performing normally.

The average value does not explain the cause

If conversion is below the industry benchmark, it is a reason to investigate the situation, not proof of poor design. A site may have a different share of new visitors, a more complex product, or a longer decision cycle.

Split the data at least by device and traffic source. A problem only on smartphones points to one set of hypotheses, while a decline across all segments points to another. Only then should you check specific actions and technical errors.

The funnel helps narrow the search

Suppose visitors frequently add items to the cart but rarely complete the order. Checking ad headlines is unlikely to be the first step. It is more useful to go through the checkout process: delivery options, available payment methods, mandatory fields, and unexpected changes in the total amount.

If few people proceed to product selection, investigate the landing page and whether it matches audience expectations. These are working hypotheses to test, not a ready-made diagnosis based on a single chart.

Verify your own data before comparing

A purchase event may be sent twice, while some orders may not reach analytics. In such cases, even an accurate external benchmark cannot fix an internal counter. First, it is useful to cross-check several real orders with site events and the accounting system.

Define which actions are measured and at what stage. 'Form submitted' and 'qualified lead received' yield different results. Blurring these distinctions particularly hinders service websites with long sales cycles.

How to use the report in conversations with contractors

Instead of demanding an immediate catch-up to the industry average, ask the contractor to explain the significant discrepancy and propose a testable hypothesis. Then agree on a single change and a success metric. This is more substantive than debating whether the conversion rate is good in general.

The new report provides context for decisions, not a ready-made plan. Comparing market data, your own metrics, and visitor behavior helps identify the work that the site actually needs right now.

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