Search terms · Trends
Who is gaining ground, when did it change, and which searches drove it?
Executive HQ
Market condition, lost opportunity, channel coverage, and the competitive gap.
Scorecard space readyOverall market visibility and material movement.
Waterfall space readyPrice-weighted visibility opportunity by cause.
Coverage space readyWhere paid and organic participation reinforce or leave gaps.
Comparison space readySelected company against a competitor across approved metrics.
Executive HQ
Charts chosen for this role.
Products
Observed products from the selected company, rolled up by group or category.
Validate Query Matches. Blacklist Mismatches.
Matrix space readyEquivalent SKU visibility across observed retailers.
Frequency space readyAppearance frequency with the median in the same view.
Value space readyPrice-weighted recoverable visibility opportunity.
Matrix space readyHow often each SKU appears versus how strongly it ranks.
Matrix space readyParticipation breadth versus resulting visibility.
Search terms
Start with search-term groups, then expose the terms driving opportunity and cost.
Ranked term viewTerm and term-group visibility leaders, laggards, and contribution.
Distribution space readyRaw position distribution and weighted visibility.
Frequency space readySelected-company appearance frequency with the median in the same view.
Rate space readyShare of eligible searches where the selected company appears in the top three.
Matrix space readyAppearance frequency versus position strength.
Matrix space readySKU or channel coverage breadth versus resulting visibility.
Pricing
Compare the same product across stores. Review and adjust every match.
Illustrative annual business case · Your example, not measured results or published pricing.
| Source | Annual value |
|---|---|
| Replaced software | $120,000 |
| Redirected FTE capacity | $420,000 |
| Reduced advertising waste | $420,000 |
| Incremental gross profit | $500,000 |
| Total | $1,460,000 |
| Value / $240,000 fee | 6.1× |
6.1× is value divided by fee—not net ROI. Capacity freed is not automatically cash saved.
Competitive products → relevant searches → profitable orders
Find opportunities →Measure: added gross profitMatched offers → better price steps → stronger margins
Review price ladders →Measure: family profit + units soldClear evidence → faster decisions → less rework
Review search fit →Measure: hours freed + verified spend savedUse actual retired software costs, hours freed × loaded hourly cost, verified ad savings, and incremental gross profit. Count each benefit once; exclude ad savings already counted in profit. Subtract implementation costs for a net-value calculation.
Check comparable periods and unchanged products where possible. Confirm sales and spend outcomes in your own systems; visibility alone does not prove profit.
Reference
Short definitions first, with explanations and a worked share of shelf example below.
| Term | Short definition |
|---|---|
| Share of shelf | Your paid Shopping offers divided by all retailers’ paid Shopping offers in a search. |
| Weighted share of shelf | Your paid Shopping position points divided by all retailers’ position points. |
| Position weight | The credit a SKU earns from its recorded position. |
| Relevant searches | Recorded searches for terms included as relevant to a product. Terms default to Relevant; users can add them to or remove them from the blacklist. |
| Zero-ad search | A successful search that returned no paid ads. |
| Appearance rate | How often a SKU appears on its relevant terms, regardless of position. |
| Visibility | Appearance rate with less credit for lower positions. |
| Exposure / 100 searches | Presence per 100 searches across the full selected term set. |
| When ads show / ad SERP freq. | Appearance rate restricted to relevant searches that returned ads. |
| Ads returned / ad availability | How often relevant searches returned any paid ads. |
| Average / median position | The average or middle rank among recorded appearances. |
| Modeled click share | A company’s share of modeled attention across paid ad cards. |
| eCTR | Estimated click-through rate: the predicted chance of a click. |
| Visibility movers | Changes in appearance rate between two date ranges. |
Our scale gives positions 1–8 one point each, then lowers the credit in bands. These are position points, not measured click probabilities. Weighted share is higher than plain share when your SKUs’ average point value exceeds the whole shelf’s average; it is lower when their average point value is lower. Average position alone cannot tell you which, because several positions share the same weight.
Each slot below holds one distinct retailer/SKU offer. Read each position-and-weight pair from top to bottom.
| Position | Weight | Position | Weight | Position | Weight | Position | Weight |
|---|---|---|---|---|---|---|---|
| Total weighted score for all 40 SKUs | |||||||
Wayne occupies positions 3, 11, 14, and 22. Stark occupies 16, 21, 27, and 35. Other companies occupy the remaining 32 slots, and all 40 slots stay in both denominators.
| Company | SKU positions | Position weights added | Total points | Share of shelf | Weighted share of shelf |
|---|
Plain share: 4 ÷ 40 × 100 = 10% each.
Weighted share: company points ÷ full-shelf points × 100.
Wayne’s positions earn more points than an average set of four slots, so its weighted share is higher than 10%. Stark’s earn fewer, so its weighted share is lower. Both occupy the same number of slots; placement changes their share of the points.
Each product and search-term combination defaults to Relevant. Users can add a combination to the blacklist or remove it to mark it Relevant again. A term can be relevant to one SKU and blacklisted for another. Relevant-mode product metrics use the included terms, while Blacklist mode lets you inspect excluded combinations. Changing relevance does not delete the observed evidence.
A zero-ad search is an observed absence of paid ads, not a failed collection. Appearance rate and Visibility include these checks as absence. Share of shelf excludes them because there is no paid shelf to divide. Visibility movers lets you include or exclude them with “Include 0 ad searches.”
Appearance rate measures presence on relevant terms, including successful checks with no ads. Each relevant term has equal weight, with recorded locations, days, hours, and repeated checks balanced. This product metric tells you how consistently a SKU shows up; it does not measure how much of the shelf it occupies.
Product visibility applies our position weights to a SKU’s appearances on relevant terms; absence earns zero credit. For a term containing several of your SKUs, term visibility averages their position credits within each search before averaging across searches. Multiple SKUs share that search’s credit. These scores use balanced sampling and include recorded zero-ad checks as absence.
Product Exposure measures a SKU’s presence across the full selected term set, with collection frequency balanced. A product relevant to a small part of that set can have strong Visibility but modest Exposure. On a term row, Exposure counts searches showing at least one included SKU. Visibility movers uses its own relevant-search rate, described below.
When ads show measures how often your SKU appeared when relevant terms returned any paid ads. Zero-ad checks are excluded from this denominator. On a term row, the measure checks whether at least one included SKU appeared. Recorded sampling is balanced so more frequent collection does not add ranking credit.
Ads returned measures whether a relevant search produced a paid shelf at all, regardless of which company appeared. A low value can help explain why a product’s overall appearance rate is lower than its when ads show rate. Failed collections are not treated as successful zero-ad searches.
A smaller position number means a higher place in the paid results. Average position is the mean rank when products appeared; median position is the middle rank. Live metrics balance the recorded sampling. Missing appearances are not assigned a rank, and neither an average nor a median replaces the individual position weights used in weighted scores.
An eCTR curve would estimate click probability by position using click and impression evidence. We do not currently have a calibrated eCTR curve. Share of shelf uses our fixed position-credit bands, and Trends uses illustrative attention curves. Their weighted shares are modeled scores, not measured clicks or validated click probabilities.
Movers compares distinct appearances divided by successful searches for each product’s relevant terms, multiplied by 100. It balances terms, locations, days and hours and compares shared term/location/hour coverage by default. The default comparison is the immediately preceding range of equal length; a custom comparison is also available. The zero-ad toggle controls whether successful searches with no ads enter the denominator. Changes are reported in percentage points; these are balanced visibility rates, not demand estimates.