Measure the search demand your brand earns and the retail visibility your products capture. Kvetoiq defines the competitors, keywords, markets, formula, and source context behind every percentage.
Share of Search is the percentage of defined search demand or search visibility attributed to a brand within a selected competitive market.
The percentage changes when the brand set, keyword set, search source, geography, time period, or weighting method changes. Those inputs must be documented.Share of Search helps teams see relative position rather than isolated rank or volume. Used carefully, it can reveal changing consumer interest, visibility gaps, campaign effects, and competitive momentum.
A well-defined Share of Search program gives marketing, ecommerce, brand, and strategy teams one comparable view of who is gaining attention and who is winning discovery.
Kvetoiq separates demand measurement from result-page visibility so teams never mistake one percentage for the other.
What percentage of category-branded search demand belongs to your brand?
What percentage of eligible product-search visibility does your brand capture?
In this example, the selected competitive set generates 100,000 branded searches. Your brand accounts for 28,000.
28,000 ÷ 100,000 × 100. This is an illustrative example, not client or market data.
Five decisions determine what the metric actually means and whether comparisons remain consistent over time.
Define which direct, adjacent, private-label, and emerging brands belong in the denominator.
Select branded, category, product, problem, and use-case queries appropriate to the model.
Separate Google demand data from marketplace and retailer search-result visibility.
Fix the country, region, language, device, retailer, store, or delivery location.
Document equal, volume, rank, opportunity, or business-priority weighting.
Define the market, calculate consistently, diagnose the gap, and deliver the result with its supporting context.
Create a controlled brand set that reflects how buyers and categories actually compete.
Organize the branded, category, product, and use-case searches required by each model.
Keep comparisons tied to the correct market, language, platform, and observation context.
Calculate relative brand interest across the approved competitive category.
Measure how often and where products appear for selected marketplace and retailer searches.
Apply a documented weighting model that reflects search demand and result importance.
Identify the brands, queries, markets, and retailers driving the largest visibility differences.
Keep earned visibility separate from paid placement while preserving a combined reference view.
Track momentum, seasonality, volatility, and persistent competitive movement.
Notify responsible teams when important searches cross an agreed movement threshold.
Compare search demand and visibility before, during, and after important brand activity.
Send percentages, inputs, trends, and supporting records into the tools teams already use.
A share can rise while total category demand falls. Preserve both views.
Determine whether your brand improved or another tracked brand declined.
Compare against relevant baselines before assigning a cause.
See which queries created the largest gain or loss.
Search data can reveal meaningful movement, but it does not automatically prove sales impact, causation, or future market share.
Demand, visibility, conversion, distribution, price, and availability affect different outcomes.
Adding or removing brands and keywords changes the measured share.
Google Trends, keyword tools, retailers, and marketplaces do not produce identical values.
Ambiguous queries, misspellings, and unrelated intent require careful filtering.
Compare relevant historical periods before interpreting a temporary spike.
Location, device, personalization, stock, and sponsorship can change visible results.
Do not present Share of Search as a universal predictor of future market share.
Always retain the underlying volume or visibility counts beside the percentage.
A controlled process keeps the metric comparable and gives every change a traceable source.
Brands, keywords, source, market, period, and weighting.
Gather eligible demand or result visibility signals.
Apply the documented numerator and denominator.
Identify the competitors and queries driving change.
Compare movement across time, market, and source.
Route priorities to brand, SEO, ecommerce, and retail teams.
Compare relative branded search interest across selected competitors, periods, and markets.
Track eligible product and brand presence for priority Amazon search terms.
Explore Amazon data →Measure product discovery and competitive placement across selected Walmart searches.
Explore Walmart data →Build a defined keyword and result-monitoring scope for relevant retail websites.
Preserve geographic, language, device, retailer, store, or delivery context where supported.
Compare recent movement with seasonal, campaign, and longer-term reference periods.
Deliver percentages, source observations, keyword contributions, competitor comparisons, and trend records in the format required by your operating environment.
Connect search visibility with content, availability, sellers, ratings, reviews, and offer execution.
Explore Digital Shelf Analytics →Map equivalent retailer listings before comparing product-level discovery and performance.
Explore Product Matching →Understand whether price, promotion, and availability context affects product visibility and demand.
Explore Price Monitoring →Investigate listings, sellers, and marketplace behavior that may affect trusted brand discovery.
Explore Brand Protection →Build specialized search and category datasets for markets with unique measurement requirements.
Explore Custom Extraction →Coordinate larger keyword, market, source, and observation programs with managed infrastructure.
Explore Enterprise Crawling →Kvetoiq documents the source, competitor set, keyword set, geography, period, weighting method, and known limitations behind the calculated metric. Share of Search supports decisions but does not replace sales, market-share, or causal analysis.
Share of Search is the percentage of defined search demand or search visibility attributed to a brand within a selected competitive market, source, geography, and period.
For brand demand, divide your branded search volume by the total branded search volume of all tracked category brands and multiply by 100. Retail search visibility requires a separately defined appearance and weighting methodology.
If your brand generates 28,000 searches and the selected category brand set generates 100,000 total searches, your brand-demand Share of Search is 28%.
Brand-demand Share of Search measures relative interest in brand queries. Retail-discovery Share of Search measures relative product or brand visibility for selected marketplace and retailer searches.
Share of Search measures relative search demand or defined search visibility. Share of Voice usually measures relative advertising, media, social, or communications presence.
No. Market share measures a portion of sales, units, customers, or revenue. Share of Search measures a portion of search demand or visibility. The two can move together in some categories, but they are not interchangeable.
It can be a useful directional indicator, but the relationship varies by category, time period, brand maturity, distribution, price, availability, and other commercial factors. It should not be presented as a universal prediction.
Google Trends can support relative interest analysis, but it uses sampled and normalized data. The method, query definitions, geography, category filters, and time period should be documented.
Use a stable set reflecting direct category competitors, meaningful private labels, emerging brands, and relevant substitutes. Changes to the competitor universe should be versioned because they change the denominator.
The appropriate set depends on the model. Brand demand generally uses branded terms and validated variants. Retail discovery may use category, product, problem, feature, and use-case keywords organized by intent and priority.
Frequency depends on the source, category volatility, campaign cadence, market size, retailer behavior, and decision window. Weekly or monthly reporting is often sufficient for demand trends, while retail visibility may require more frequent observations.
Yes, when the underlying source supports the required geography. Country, region, language, device, retailer, store, or delivery context should be preserved with the measurement.
Eligible marketplace and retailer search results can be monitored for selected keywords, products, categories, locations, and result types. The exact scope depends on source availability and technical feasibility.
They should be labeled and reported separately, with a combined view only when the methodology clearly states how each result type is weighted.
Changes can result from campaigns, news, seasonality, distribution, product launches, competitor activity, search visibility, category demand, reputation events, or changes to the tracked market definition.
The response depends on the model. Brand demand may require stronger products, campaigns, PR, distribution, and brand salience. Retail discovery may require better content, keyword relevance, availability, category placement, advertising, reviews, and digital shelf execution.
Limitations include source estimation, sampling, generic brand names, incomplete competitor sets, changing denominators, seasonality, geographic variation, personalization, and the fact that search behavior is not identical to sales.
Share your brand, priority competitors, category, keywords, search sources, target markets, reporting period, intended decisions, and preferred delivery method. Kvetoiq will define the methodology before production monitoring begins.
Share your brand, competitors, category, keywords, sources, and target markets. Kvetoiq will define the measurement model, calculate a sample view, and map the ongoing monitoring workflow.
Share the platforms, categories, competitors, SKUs, regions, or business questions you care about. KVETOiQ will help define the right data strategy, output format, and operating cadence.
