Feature Walkthrough
Quick Answer
AdSpyder Shopping Ads Spy lets you search 94 million+ Google Shopping product ads across 184 countries by product keyword or competitor domain. Each result card shows product title, price in native currency, first-seen to last-seen date range, advertiser domain, and average SERP position — everything you need to reverse-engineer what works in your category before you spend a rupee on your own campaigns.
Shopping ads are different from text ads. There is no headline to A/B test. Your product title, image, and price are the ad. Which means competitor research here is about title structure, pricing strategy, market coverage, and ad longevity — not creative copy. And you cannot get that from a live Google search, which only shows you what is running right now, in your location, on your device.
This guide is a complete walkthrough of every part of AdSpyder’s Shopping Ads Spy — what each filter does, how to read a result card, and what the archive data actually tells you about the product listings that win.
94M+
Google Shopping ads indexed
Across all 184 countries in the archive.
184
Countries covered
US leads at 22% of total archive volume.
63%
Unique retailer domains
In a 1,000-ad sample — 633 distinct domains appeared.
2018
Archive start year
First-seen coverage from January 2018 onward.
Source: AdSpyder platform data, June 2026.
In This Guide
Feature Guide
What is AdSpyder Shopping Ads Spy?
Shopping Ads Spy is AdSpyder’s dedicated module for researching Google Shopping Product Listing Ads. While the Google Ads Spy tool covers text-based Search campaigns, Shopping Ads Spy focuses entirely on PLAs — the image-and-price cards that appear above organic results when someone searches for a product on Google.
The tool lets you search a product keyword or competitor domain and see exactly what other retailers have run — their product titles, price points, markets, ad longevity, and SERP positions — from a 94M+ ad archive spanning 184 countries.
Who this is for
E-commerce brand managers, Shopify and WooCommerce store owners, Google Shopping campaign managers, and performance marketers who want to know what competitor product listings look like before building or improving their own campaigns.
The Archive: What You Are Actually Searching
That 63% unique-domain figure from the headline stat matters. Google Shopping is not a marketplace dominated by three giants. In a 1,000-ad sample from the archive, 633 distinct retailer domains appeared. Your competition is a long tail of specialists — category-specific stores, regional retailers, and niche direct-to-consumer brands you have probably never heard of. The Spy tool is built for that scale.
Top Markets by Shopping Ad Volume
| Country | Ads Indexed | Share of Archive |
|---|---|---|
| 🇺🇸 United States | ~21 million | 22.1% |
| 🇬🇧 United Kingdom | ~10 million | 10.7% |
| 🇮🇳 India | ~6.1 million | 6.4% |
| 🇲🇽 Mexico | ~5.6 million | 5.9% |
| 🇦🇺 Australia | ~4.7 million | 4.9% |
| 🇧🇷 Brazil | ~4.4 million | 4.6% |
| 🇨🇦 Canada | ~4.2 million | 4.4% |
| 🇵🇱 Poland | ~3.7 million | 3.9% |
Source: AdSpyder platform data, June 2026. Top 8 countries shown; 184 total in archive.
Try Shopping Ads Spy
Research competitor product listings before your next campaign
94M+ Google Shopping ads. 184 countries. Every product title, price, and run duration — searchable by keyword or competitor domain.
Two Search Modes: Keyword vs Domain
The most important choice in Shopping Ads Spy is the search input mode. You are either searching by what is being advertised (keyword) or who is advertising (domain). These serve different research goals and produce different results.
| Mode | Input Example | Best For |
|---|---|---|
| Keyword (Broad) | running shoes | Category-level research — see every brand advertising in a product space, their title structures, price ranges, and positions |
| Domain | etsy.com | Competitor-level research — see every product a specific retailer has advertised, their full Shopping catalogue, markets, and pricing history |
Recommended starting sequence
Start with keyword mode to map the competitive landscape — who is advertising, at what price, how long ads run. Then switch to domain mode for your top 2–3 direct competitors to audit their full catalogue. The two modes together give you both the market view and the individual competitor view.
All Six Filter Groups — What Each One Controls
Shopping Ads Spy organises its refinement options into six filter groups. Here is exactly what each controls and when to use it.
Major Filters
Primary search refinements that control the broad parameters of your query. These are set first and define the scope before country and time narrow results further.
Country Filter
Supports single-country and multi-country selection across all 184 countries in the archive. Your most important localisation lever — use it every time.
Time Filter (Date Range)
Defines the archive window you want to query. Essential for seasonal research — narrow to Q4 peak windows, Black Friday, or holiday periods to see exactly what competitors ran.
Search-In Filter
This is what switches you between keyword mode and domain mode. Select keyword to search by product term; select domain to pull all Shopping ads from a specific advertiser URL.
Sort Type
Controls result ordering. Use sort to surface most-recently-seen ads first for trend research, or most-active for finding consistently-running listings.
Advanced Filters
Additional refinements for narrowing a large result set. Use when a broad keyword like “shoes” or “phone” returns thousands of results and you need to drill down further.
Reading a Result Card: Every Field Explained
Each Shopping ad in your results appears as a card. Here is what every field means and the specific decision each one informs.
| Field | What it shows | How to use it |
|---|---|---|
| Product title | Exact listing title as it appeared in Google Shopping results | Analyse title structure — brand placement, variant inclusion, character length — and benchmark against your own listings |
| Price | Price as displayed in that country’s Google Shopping, in native currency. May show original + discounted (strikethrough) where applicable | Map competitor price positioning per market. Identify who discounts in their feed vs who holds full price |
| First seen → Last seen | The first and last dates this listing was observed by the AdSpyder crawler | A long gap means the listing ran consistently — enough to keep paying for. This is your strongest signal of a profitable listing |
| Country | Market(s) where this ad appeared. Multi-country ads show “Country + N more” | Understand which markets a competitor prioritises for a given product SKU |
| Advertiser domain | The retailer domain running this listing | In keyword searches, this identifies which competitors are active in your product category. Combine with domain mode for deeper audits |
| Average position | Mean SERP placement across all observed impressions. Lower = higher placement | Combine with run duration: long date gap + low average position = a listing that ranked well and kept running. That combination is the clearest performance signal in the archive |
| Product image | Product image used in the Shopping listing, where available | Benchmark image style, background choice, and product angle against your own creative |
What the archive does not show
Shopping Ads Spy shows observed competitor ads and listing patterns. It does not reveal private ROAS, exact ad spend, conversion rates, or bidding data. Use it for market research and testing direction — not as a substitute for your own campaign performance data.
What the Archive Tells You About Winning Product Titles
This is where Shopping Ads Spy goes beyond a search interface. The 94M+ ad archive is large enough to identify patterns in what makes a Shopping listing run long — which is the closest proxy for profitability the data gives you.
Across a 2,000-ad sample from the archive (AdSpyder platform data, June 2026):
65.4
Average title characters
Median is 58 characters.
50.6%
50–100 char titles
Most common title length bucket.
44.8%
Include a variant term
Size, color, capacity, or material.
0.1%
Use offer/promo language
Virtually absent from all titles.
Source: AdSpyder platform data, June 2026. Sample n=2,000.
The longevity data is the most actionable finding. Listings that ran 30 or more days carry more size or variant terms (46.9% vs 44.2%) and are significantly less likely to lead with the retailer name (9.4% vs 15.8%). The pattern is consistent: long-running Shopping ads lead with the product, not the store. And they never use discount language in the title.
Winning title formula (from archive data)
[Brand] + [Product / Model] + [Variant: size / color / capacity / material]
50–100 characters. Product-first. No discount mentions. No leading with the retailer name. Source: AdSpyder platform data, June 2026.
Using the Time Filter for Seasonal Research
The Time filter unlocks one of the most underused capabilities in Shopping Ads Spy: researching exactly what competitors ran during peak seasonal windows. The archive data shows clear seasonal clustering that makes this valuable for Q4 planning.
63%
Halloween Shopping ads appear in October
Strong single-month concentration.
65%
Black Friday Shopping ads appear in November
Most launch in the month itself.
Oct→Dec
Christmas Shopping ad ramp
54k Oct → 69k Nov → 137k Dec. Slow build, then a spike.
Source: AdSpyder platform data, June 2026.
To use this: set the Time filter to the relevant seasonal window (e.g. October–November for Black Friday), apply your Country filter, and run a keyword search for your product category. You will see exactly what titles, prices, and domains your competitors ran in that window — giving you a concrete brief for your own seasonal campaign structure.
December to January: worth knowing
The archive data shows an 89% drop in Christmas Shopping ads from December to January. If you are planning post-holiday campaigns, the competitive landscape clears dramatically — useful timing to understand before setting budget expectations.
Step-by-Step: Research a Competitor in 10 Minutes
Use this workflow when entering a new product category, refreshing existing campaigns, or planning a seasonal push.
Open Shopping Ads Spy
Go to adspyder.io/shopping-ads-spy and log in. New users can start a free trial — no credit card required.
Start with keyword mode
Use the Search-in filter to select keyword mode. Enter your primary product term (e.g. “wireless earbuds” or “office chair”). This gives you the category-level view — who is advertising, at what price, and for how long.
Set Country and Time filters
Select your target market. If doing seasonal research, narrow the date range to the relevant window. Skip the date filter if you want the full archive view.
Scan the top result cards
Review the top 15–20 cards. Note advertiser domains, title structures, price ranges, and date gaps. A long first-seen to last-seen gap with a low average position is your signal: this listing worked.
Switch to domain mode for top competitors
Take the 2–3 advertiser domains from your keyword scan and run each through domain mode. You now see their full advertised catalogue — every product, every market, every price point in the archive.
Apply findings to your campaigns
Rewrite your product titles using the winning formula. Adjust price positioning based on what competitors charge per market. Identify product variants your competitors advertise that you have not listed yet. Use URL and Domain Analysis to cross-reference competitor landing page strategy.
Shopping Ads Spy vs Free Research Methods
Free methods can show you what is running right now in your location. That is about all they give you. Here is what each approach actually covers.
| Capability | AdSpyder Shopping Ads Spy | Google Ads Transparency Center | Manual Google Search |
|---|---|---|---|
| Historical archive (from 2018) | ✅ | ❌ | ❌ |
| Search by competitor domain | ✅ | ✅ (limited) | ❌ |
| Price visibility per market | ✅ Native currency | ❌ | ✅ (live only) |
| First-seen / last-seen dates | ✅ | ❌ | ❌ |
| Average SERP position | ✅ | ❌ | ❌ |
| Multi-country coverage | ✅ 184 countries | Limited | One at a time |
One honest note on the archive
AdSpyder’s archive clusters around 2018–2022 first-seen dates. It is not a live feed. For researching title patterns, pricing strategy, market coverage, and long-run ad behaviour, the archive is exactly what you need. For checking what a competitor is running today, supplement with a direct Google Shopping search in your target market.
Where Shopping Ads Spy fits in your ecommerce workflow
Use Shopping Ads Spy before campaign launches, before seasonal promotions, and during monthly competitor reviews. For broader paid-ad intelligence, combine it with the AdSpyder Ad Library, the Google Ads Spy tool for Search campaign research, and Facebook Ads Spy for what e-commerce brands run on Meta alongside their Shopping campaigns.
Pre-Campaign Research Checklist
✅ Run keyword mode search for your primary product term in your target country
✅ Identify the top 3–5 advertiser domains active in your category
✅ Note title structure of listings with longest first-seen to last-seen gap
✅ Map price positioning per market in native currency
✅ Switch to domain mode and audit your top 2–3 competitors’ full catalogues
✅ Check which product variants competitors advertise that you have not yet listed
✅ For seasonal campaigns, apply Time filter to the relevant window and repeat
✅ Rewrite product titles using [Brand] + [Product/Model] + [Variant] formula
FAQs
How many Google Shopping ads does AdSpyder index?
AdSpyder Shopping Ads Spy indexes 94 million+ Google Shopping product ads across 184 countries, with archive coverage starting from January 2018. Source: AdSpyder platform data, June 2026.
Can I search Shopping ads by competitor domain?
Yes. Shopping Ads Spy has two search modes — keyword and domain. In domain mode, enter a competitor’s URL (e.g. etsy.com) and you will see every Shopping ad they have run in the archive, across all markets they advertised in.
Does AdSpyder show competitor pricing in Shopping ads?
Yes. Each result card shows the price as it appeared in that country’s Google Shopping results, in native currency. Some cards also show original vs discounted price where a strikethrough was visible in the original listing.
What does average position mean in Shopping Ads Spy results?
Average position is the mean SERP placement of that Shopping ad across all observed impressions in the archive. A lower number means the ad appeared higher in Shopping results more consistently. Combine with the first-seen to last-seen date gap to identify listings that ranked well and kept running — your strongest performance signal.
Is the Shopping Ads Spy data a live feed or historical?
Historical. The archive clusters around 2018–2022 first-seen dates. It is excellent for researching title patterns, pricing strategy, market coverage, and long-run ad behaviour. For checking what a competitor is running today, supplement with a direct Google Shopping search in your target market.
Is AdSpyder Shopping Ads Spy free to try?
Yes. AdSpyder offers a free trial at adspyder.io/shopping-ads-spy. You can start exploring the 94M+ Shopping ad archive without a credit card.
Stop guessing. See exactly what your competitors are advertising.
94 million+ Shopping ads. 184 countries. Every product title, price, and run duration — searchable by keyword or competitor domain. Start for free today.
