Solution
Where your brand shows up, and where competitors are taking your shelf
Real-time search rank, category rank, sponsored placement, share of voice, and content quality across every retail platform you sell on. Win the digital shelf the way it actually plays out.
The shelf is digital now, and the rules are different.
On Amazon, Flipkart, Blinkit, and every marketplace, position is paid, ranked, and reshuffled by the hour. The brand that wins is the brand that knows where it sits, where the competitor is, and where the customer is actually looking.
Most brands measure digital shelf monthly, in PowerPoint.
By the time a slide says you lost search rank, the competitor has been on top for three weeks, harvested the basket, and trained the recommendation engine to keep them there.
We capture rank, share, sponsored placement, and content quality, by the hour.
Every keyword, every category, every platform. Sponsored vs organic. Banner vs carousel. Buy box vs alternative seller. Delivered structured, deduplicated, in your schema.
Search and category rank, captured hourly
Every keyword you care about, every category, every platform. Watch your rank rise and fall against competitors and against sponsored slots in the same trading hour.
Sponsored, organic, and content quality
Sponsored placements, hero banners, recommended carousels, content-compliance scores. The shelf is more than rank, and we capture every layer.
Share of voice, share of shelf
Roll keyword and category data up to share-of-shelf metrics by brand, sub-brand, and SKU. See where you are dominant, where you are losing, and where the gap is widening.
Position on the digital shelf is the product. A brand that drops three slots in search rank loses 30% of its impressions, regardless of price, packaging, or marketing spend. Whoever measures it hourly wins it. Whoever measures it monthly is reading the eulogy.
How it works
The extraction pipeline
From target spec to your warehouse, every digital shelf record passes through these stages. You see the output. We run everything in between.
Target spec
Keywords, categories, brands, SKUs, platforms, cadence, and schema locked from your pilot scope.
Source orchestration
Web, app, and seller-page extraction across every retail platform in scope, in parallel.
Capture
Rank capture per keyword, category sweeps, sponsored-vs-organic detection, content-compliance scoring per listing.
Validation
Schema, range, deduplication, decoy detection, sponsored-tag verification.
Delivery
CSV, JSON, REST, or direct push to your warehouse, in your spec.
Coverage
Platforms we monitor
Digital shelf analytics runs across the retail platforms where your brand competes for impression and conversion. Each platform has its own rank algorithm, its own sponsored layer, and its own content schema.
Marketplaces
Shopee, Amazon (US, India, EU, JP), Flipkart, Walmart, Lazada, Tokopedia. Search rank, sponsored, buy box, and A+ content across each market's specific layer.
Quick commerce
Blinkit, Zepto, Swiggy Instamart, BigBasket category and search rank
Specialty retailers
Target, Costco, Tesco, Carrefour shelf and sponsored layers
D2C brand storefronts
Direct-to-consumer rank and content quality
Data landscape
The data we extract
Every rank, share, placement, and content-quality record from every monitored platform, normalized into one digital-shelf schema, delivered on your cadence.
Search rank
Keyword, position, page, organic vs sponsored flag
Category rank
Category, sub-category, position, badge
Placement
Banner, hero, recommended carousel, cross-sell slot, deal-of-the-day flag
Sponsored
Sponsored brand, sponsored product, sponsored display tags and positions
Buy box
Winning seller, price, seller type, eligible-seller count where exposed
Content quality
Title length, image count, attribute completeness, A+/EBC presence, video presence
Social proof
Average rating, review count, recent review velocity
This is a representative sample of the data we extract. We customize every extraction to your exact requirements. If you need a data point not listed here, we will add it to your pipeline.
Sample output
What a single record looks like
This is a representative payload from a real digital shelf extraction job. Field names, schema, and delivery format are scoped to your spec at pilot time.
{
"extracted_at": "2026-05-07T16:18:33Z",
"platform": "amazon",
"surface": "app",
"market": "IN",
"keyword": "wireless headphones",
"page": 1,
"position": 4,
"listing": {
"asin": "B0CHX1W1PY",
"title": "Sony WH-1000XM5 Wireless Noise Cancelling Headphones",
"brand": "Sony",
"matched_brand_id": "OUR-BRAND-3"
},
"placement": {
"is_sponsored": true,
"sponsored_type": "sponsored_product",
"is_organic": false,
"badge": "Amazon's Choice",
"is_in_carousel": false
},
"buy_box": {
"winner_seller": "Sony Official",
"winner_seller_type": "first_party",
"buy_box_price": 24990,
"currency": "INR",
"eligible_seller_count": 3
},
"content_quality": {
"title_length": 73,
"image_count": 7,
"attribute_completeness_pct": 92,
"has_a_plus_content": true,
"has_video": true
},
"social_proof": {
"average_rating": 4.6,
"review_count": 8412,
"review_velocity_30d": 94
}
}Schema
Field-level reference
Every record conforms to a stable schema. Your engineering team can integrate against this spec before the pilot starts.
extracted_atISO 8601UTC capture timestamp2026-05-07T16:18:33Zextracted_atISO 8601UTC capture timestamp
2026-05-07T16:18:33ZplatformstringSource platform nameamazonplatformstringSource platform name
amazonsurfaceenumweb, appappsurfaceenumweb, app
appmarketISO-3166Market codeINmarketISO-3166Market code
INkeywordstringSearch query capturedwireless headphoneskeywordstringSearch query captured
wireless headphonespagenumberSearch results page number1pagenumberSearch results page number
1positionnumberSlot position on the page4positionnumberSlot position on the page
4listing.asinstringSource-platform listing identifierB0CHX1W1PYlisting.asinstringSource-platform listing identifier
B0CHX1W1PYlisting.brandstringBrand label as listedSonylisting.brandstringBrand label as listed
Sonylisting.matched_brand_idstringYour brand mapped to this listingOUR-BRAND-3listing.matched_brand_idstringYour brand mapped to this listing
OUR-BRAND-3placement.is_sponsoredbooleanSlot is paid placementtrueplacement.is_sponsoredbooleanSlot is paid placement
trueplacement.sponsored_typeenumsponsored_brand, sponsored_product, sponsored_display, nullsponsored_productplacement.sponsored_typeenumsponsored_brand, sponsored_product, sponsored_display, null
sponsored_productplacement.badgestring / nullPlatform badge if anyAmazon's Choiceplacement.badgestring / nullPlatform badge if any
Amazon's Choicebuy_box.winner_sellerstringSeller currently winning the buy boxSony Officialbuy_box.winner_sellerstringSeller currently winning the buy box
Sony Officialbuy_box.winner_seller_typeenumfirst_party, fba, fbm, mall, preferred, regularfirst_partybuy_box.winner_seller_typeenumfirst_party, fba, fbm, mall, preferred, regular
first_partybuy_box.buy_box_pricenumberActive buy-box price24990buy_box.buy_box_pricenumberActive buy-box price
24990buy_box.eligible_seller_countnumberSellers eligible for the buy box3buy_box.eligible_seller_countnumberSellers eligible for the buy box
3content_quality.title_lengthnumberCharacter count of listing title73content_quality.title_lengthnumberCharacter count of listing title
73content_quality.image_countnumberNumber of images on the listing7content_quality.image_countnumberNumber of images on the listing
7content_quality.attribute_completeness_pctnumberPercent of required attributes filled92content_quality.attribute_completeness_pctnumberPercent of required attributes filled
92content_quality.has_a_plus_contentbooleanA+ / EBC content presenttruecontent_quality.has_a_plus_contentbooleanA+ / EBC content present
truecontent_quality.has_videobooleanVideo asset presenttruecontent_quality.has_videobooleanVideo asset present
truesocial_proof.average_ratingnumberAverage customer rating4.6social_proof.average_ratingnumberAverage customer rating
4.6social_proof.review_countnumberTotal review count8412social_proof.review_countnumberTotal review count
8412social_proof.review_velocity_30dnumberReviews added in last 30 days94social_proof.review_velocity_30dnumberReviews added in last 30 days
94Delivery formats
How you receive the data
You define the format. We handle the rest.
Use cases
How teams put digital shelf data to work
From pricing teams to category managers to operations leads, here are the most common ways digital shelf data drives decisions.
E-commerce managers, rank defense and recovery
Monitor search and category rank for every keyword that drives your basket. Catch rank drops the same day, identify what changed, recover before it costs you a week of impressions.
Brand managers, share of shelf
Track your brand's share of shelf against competitors per category and per platform. Defend share with content, rank, and sponsored investment based on real position data.
Trade marketing, sponsored placement ROI
Measure sponsored impression share, organic-vs-paid mix, and sponsored placement cost per impression across competitors. Negotiate sponsored spend on real market data.
Content teams, content compliance scoring
Score listing quality across title, image, attribute, A+/EBC, and video coverage. Spot listings that need content investment to recover rank.
Category leadership, cross-platform performance
Compare digital shelf performance across Amazon, Flipkart, Blinkit, and others side by side. Identify platforms where you over-index and under-index, and reallocate effort.
Leadership, digital shelf scorecard
Weekly board-ready rank, share, and sponsored reports across categories, brands, and platforms. Trends, deltas, recovery times, sponsored ROI.
Tech specs
What we run at scale
Every digital shelf engagement runs against these baseline specs. Your scope can move freshness, throughput, or geo coverage to whatever you need.
Hourly
Default search-rank refresh
1M+
Keyword-platform combinations daily
99.9%
Pipeline uptime
20+
Retail platforms covered
15 min
Minimum cycle on flagged keywords
99%+
Records passing validation
Challenges
Why digital shelf data extraction is hard
If extraction were easy, you would do it yourself. Here is why it is not.
Search rank changes by user, by session, by location
The same query returns different rankings to different users. Capturing your competitive rank means capturing it from a clean session, in the right geo, at the right cadence. Most providers run logged-in sessions and capture personalized results, then sell them as competitive intelligence.
Sponsored placements blur with organic
Platforms intentionally make sponsored hard to distinguish. Sponsored brands, sponsored products, sponsored display, native ads, badged listings. Detecting which slots are paid is a per-platform engineering problem that has to be re-solved every time the platform updates its UI.
Content quality has no standard schema
What counts as a complete listing varies by platform. Amazon A+ content is different from Flipkart Plus is different from Blinkit's listing schema. Scoring content compliance across platforms means building a normalization layer most teams skip.
Buy box is its own data problem
On Amazon and similar marketplaces, the winner of the buy box at a given moment is who actually gets the order. Tracking buy-box winners over time, seller types involved, and price thresholds requires its own capture logic.
Hourly cadence at scale is expensive
Hourly rank capture on 100,000 keywords across 10 platforms is 24 million rank records per day. At that volume, anti-bot, validation, and storage are all infrastructure problems, not features.
Building it in-house costs more than the data
Engineers, geo-routing, login automation, schema normalization, monitoring, on-call. Internal projects spend 6 to 12 months and end up with daily rank data that misses every same-day rank shift.
Why us
Why Clymin for digital shelf
We are not a tool. We are the team you call when the data matters too much to get wrong.
We solve what others can't
Hourly rank capture across 20+ retail platforms simultaneously, with sponsored-vs-organic detection, buy-box tracking, and content-compliance scoring. Per-platform engineering, not per-vendor compromise.
We prove it before you pay
Free pilot on your keywords, your brands, your categories, your platforms. Sample data within 1 to 3 days. You evaluate against your own rank tracking before any commitment.
You pay only for data delivered
Per record, no setup fees, no per-keyword charges, no per-platform charges. One metric: cost per record. If we don't deliver, you don't pay.
Your identity stays protected
We do not display client logos or name-drop. Digital shelf intelligence is sensitive. Your competitors should never know you are watching.
100B+
Data points extracted
24/7
Pipeline uptime
Real-time
Data delivery
100K+
Points of interest covered
Proven at enterprise scale. We operate continuous competitive intelligence infrastructure for one of the world's largest quick commerce platforms.
Industries served
Who buys digital shelf data
The verticals where digital shelf extraction creates the most leverage.
See where your brand shows up before the rank report tells you
Tell us your keywords, your categories, your platforms. Pilot data in 1 to 3 days. No commitment.
FAQ
Digital Shelf Analytics data extraction FAQ
Amazon (US, India, EU, JP), Flipkart, Walmart, Lazada, Shopee, Tokopedia, Blinkit, Zepto, Swiggy Instamart, BigBasket, Target, Costco, Tesco, Carrefour, and any retail platform we are scoped to add during pilot.
Hourly default for search-rank capture. 15 minutes on flagged high-priority keywords. Daily for category sweeps.
Yes. Per platform we maintain detection logic for sponsored brands, sponsored products, sponsored display, native ads, and badged listings. Classification is captured per record and updated when platforms change tagging.
Yes. Buy-box winner seller, seller type (first-party, FBA, FBM, mall), winning price, and eligible-seller count where exposed.
Per platform we maintain a content schema covering title, image count, attribute completeness, A+ / EBC presence, video presence, and bullet richness. Each listing gets a per-platform score, and an aggregated score where comparison is meaningful.
Yes. Brand-level share by category, by keyword, by impression slot. Sponsored-inclusive and organic-only views delivered separately.
De-personalized. We run clean, geo-correct sessions specifically to capture the rank a typical first-time customer would see. Personalized rank is a separate, opt-in delivery if you provide test accounts.
CSV, JSON, REST API, or direct push to your data warehouse: BigQuery, Snowflake, Redshift, S3. You define the schema.
We extract publicly available data. We do not extract authenticated user-level data without explicit account ownership. Use of extracted data is the customer's responsibility under their jurisdiction.