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Zoomcar Data Intelligence 2026: Rental Market Insights

Introduction

A team tracking only the online catalogue will miss most of the promotional signal in US grocery. The weekly circular is a separate publication, produced by a different team on a different calendar, and the product page frequently does not reflect what the ad is advertising.

That gap is not an edge case. It is the normal state of affairs. If your promotional intelligence comes only from product pages, you are measuring a partial picture and reporting it as complete.

Our promotional price monitoring service and grocery catalogue data collection are built specifically to run both sources together rather than treating the circular as an afterthought.

What a circular is, and why it disagrees with the site

The circular — weekly ad, flyer, insert — is the retailer's planned promotional communication for a defined date range, targeted at a defined group of stores. It is produced weeks in advance, printed or published on a fixed schedule, and it is the authoritative statement of what the retailer intends to promote.

The online catalogue is a different system. Reasons they disagree:

Cause What you observe
Offer requires a clipped digital coupon Ad shows a low price; PDP shows regular price
Offer is in-store only Ad price absent from the online channel entirely
Store group mismatch Ad applies to a store group the online store is not in
Timing offset Ad live before or after the PDP updates
Mechanic not representable on a PDP BOGOF or "buy 4 save $4" shows as a badge with no price change
Ad-only item Promoted item not merchandised online

So the circular and the catalogue are complementary sources answering different questions. The catalogue answers "what does it cost right now, here." The circular answers "what is the retailer promoting, to whom, and until when." Promotional strategy analysis needs the second.

Circular formats and how each is extracted

Circulars appear in three broad forms. Effort and reliability differ sharply.

Format What it is Extraction approach Reliability
Structured data behind the viewer The interactive flipbook is rendered from an offer feed Read the underlying structured offers directly Highest — offers arrive as fields
Interactive flipbook (image-based) Page images with clickable hotspot regions Read hotspot metadata where present; OCR the page image where not Medium — depends on hotspot coverage
PDF or flat image A rendered page with no structure at all Document layout analysis plus OCR, then parse Lowest — needs validation

Always check for the structured source first. A surprising number of interactive viewers are driven by a clean offer feed, and reading it turns a document-understanding problem into a field-mapping problem.

When OCR is required, the hard part is not reading characters. It is deciding which price belongs to which product. A circular page is a dense visual layout where adjacency carries meaning. A price printed large in the middle of a block may govern six surrounding items or only one.

Practical rules for OCR-based extraction:

  • Segment the page into offer blocks before reading text, using layout structure rather than reading order.
  • Treat the largest text in a block as the candidate price and the nearest product description as its subject.
  • Parse fine print separately — limits, conditions, and required quantities live there, and they change the effective price.
  • Route low-confidence blocks to review rather than publishing them.
  • Cross-validate extracted prices against the catalogue price for the same item. An extracted price far outside the plausible range is probably a misread.

OCR extraction accuracy rate by circular format, measured against manual review

Our US retail data services handle all three circular formats, with the extraction route chosen per retailer rather than assumed.

The offer schema

An offer is not a price. It is a conditional statement about a price, and the conditions are most of the value.

Field Notes
retailer, banner Ad ownership
circular_id Retailer's ad identifier
store_group_id Which stores the ad applies to
valid_from, valid_to Ad window as published
page_number, block_position Where on the page — prominence signal
offer_headline_raw Verbatim, e.g. "2 for $5"
product_description_raw Verbatim item text
brand, size_raw Parsed from the description
offer_type price_point / multibuy / bogo / percent_off / dollar_off / digital_coupon / loyalty_required / spend_threshold
offer_price Numeric price where a single price applies
required_qty For multibuys and thresholds
effective_unit_price Derived at required_qty
purchase_limit "Limit 4" parsed
requires_loyalty_card Boolean
requires_coupon_clip Boolean
min_spend For "$5 off $25" style offers
excludes_raw Exclusion fine print
matched_retailer_sku Link to catalogue, null if unmatched
match_confidence Confidence of that link
extraction_confidence Confidence of the extraction itself
collected_at, source_url Provenance

Two confidence scores, not one. extraction_confidence says "did we read this correctly." match_confidence says "did we link it to the right catalogue item." They fail independently, and conflating them makes debugging impossible.

The full offer record is delivered alongside catalogue prices in our pricing and product data service, with both scores preserved per record.

Promotional mechanics that need care

Mechanic Ad text example Effective price logic
Price point "$2.99 ea" Straightforward single price
Multibuy "3 for $10" Unit price only at qty 3; single-unit price unchanged
BOGO free "Buy 1 Get 1 Free" Effective 50% off, only at qty 2. Check whether the free item must be identical
BOGO half "Buy 1 Get 1 50% Off" Effective 25% off at qty 2
Percent off "30% Off" Needs a base price — pull it from the catalogue
Dollar off "$1.50 Off" Needs a base price
Spend threshold "Save $5 when you spend $25" Basket-level, not item-level. Do not allocate to items
Digital coupon "Clip for $1 off" Not realised unless clipped. Flag separately
Loyalty gated "With Card" Only applies to members
Mix and match "Mix or match any 5" Offer spans a set of eligible items, not one item

Percent-off and dollar-off offers cannot be resolved from the circular alone. They need a base price from the catalogue for the same store group, on the same date. This is the strongest argument for aligning the two sources rather than running them as separate reports.

Spend thresholds are basket-level. Allocating a share of a "$5 off $25" offer to individual items produces numbers that look precise and mean nothing.

Aligning circular data to catalogue data

The join has three keys, and all three must be right.

1. Product. Ad copy is abbreviated marketing text, not a catalogue title. "Coke 12pk" must resolve to a specific retailer SKU. Run it through the same matching pipeline as any cross-retailer match: exact identifier where available, then normalised brand plus size plus variant, then attribute similarity, then human review. Store the confidence.

2. Store group. The ad applies to a store group, not all stores. Maintain a mapping from store_group_id to member store IDs and keep it current. Getting this wrong attributes promotions to stores that never ran them.

3. Date. Offers are valid for a window. Joining a Tuesday catalogue observation to a Wednesday ad window produces a mismatch that looks like a data error. Always join on overlapping date ranges, not on a single date.

The product-side join is a specification-matching problem in its own right, covered in our matching ad copy to catalogue SKUs service.

Once aligned, the useful outputs appear:

Metric Definition
Promo depth Offer price against non-promotional catalogue price
Promo frequency Weeks in a period a line appeared in an ad
Promo pressure by category Share of tracked lines on offer in a category, by week
Front-page prominence Share of a brand's offers on early pages
Ad-only rate Offers with no corresponding online price change
Mechanic mix Distribution across BOGO, multibuy, price point, coupon

promo depth distribution by category across tracked chains share of circular offers with no matching online price change

The weekly collection calendar

Most US chains flip their ad midweek, commonly Wednesday, though regional banners vary and some run Sunday or Thursday starts. Build the calendar per banner rather than assuming a single flip day.

A workable weekly rhythm:

Day Action
Day before flip Collect the incoming ad where published in advance
Flip day, early Full collection of new circulars across all banners
Flip day, later Extract, parse, and score confidence
Flip day + 1 Match to catalogue, resolve percent-off base prices
Flip day + 1 Human review queue for low-confidence extractions
Flip day + 2 Publish reconciled offer dataset
Mid-window Spot-check for mid-week changes and corrections

Two operational rules matter. First, keep the previous week's ad available — overlapping windows and late corrections are common. Second, snapshot the source document. When an extracted offer is challenged, the archived page settles it.

Retailers do issue corrections mid-window. Version offer records rather than overwriting them, so history remains reconstructable.

The extraction pipeline that powers this calendar is part of our ecommerce data extraction service.

Conclusion

Actowiz Solutions collects weekly circulars across US grocery banners, extracting structured offers with mechanic type, conditions, store group, and validity window, from structured feeds, interactive viewers, and PDF-only ads alike.

Circular offers are aligned to store-level catalogue prices so promo depth and ad-only offers can be measured rather than inferred.

You can also reach us for all your mobile app scraping, data collection, web scraping, and instant data scraper service requirements!

FAQ

Why does the weekly ad price differ from the price on the website?

The ad and the online catalogue are separate systems. Many ad offers are in-store only, require a clipped digital coupon, or apply to a store group the online store is not part of. Mechanics like BOGO also cannot be expressed as a single PDP price.

What formats do grocery circulars come in?

Three. Some interactive viewers are driven by a structured offer feed, which is the most reliable source. Others are image-based flipbooks with clickable hotspots. Some chains publish only a PDF, which requires layout analysis and OCR plus validation.

How do you link a circular offer to a specific product?

Ad copy is abbreviated, so it runs through a matching pipeline: exact identifier where present, then normalised brand plus size plus variant, then attribute similarity, then human review. Each link carries a confidence score, separate from extraction confidence.

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