{"id":41920,"date":"2026-06-09T11:44:00","date_gmt":"2026-06-09T11:44:00","guid":{"rendered":"https:\/\/adspyder.io\/blog\/?p=41920"},"modified":"2026-06-09T12:09:55","modified_gmt":"2026-06-09T12:09:55","slug":"adspyder-shopping-ads-spy-guide","status":"publish","type":"post","link":"https:\/\/adspyder.io\/blog\/adspyder-shopping-ads-spy-guide\/","title":{"rendered":"AdSpyder Shopping Ads Spy | Complete Guide to Researching Competitor Product Listings (June 2026)"},"content":{"rendered":"
\n

Feature Walkthrough<\/p>\n

<\/p>\n

\n

Quick Answer<\/p>\n

AdSpyder Shopping Ads Spy<\/a> 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 \u2014 everything you need to reverse-engineer what works in your category before you spend a rupee on your own campaigns.<\/p>\n<\/div>\n

<\/p>\n

Shopping ads are different from text ads. There is no headline to A\/B test. Your product title, image, and price are<\/em> the ad. Which means competitor research here is about title structure, pricing strategy, market coverage, and ad longevity \u2014 not creative copy. And you cannot get that from a live Google search, which only shows you what is running right now<\/em>, in your location, on your device.<\/p>\n

This guide is a complete walkthrough of every part of AdSpyder’s Shopping Ads Spy \u2014 what each filter does, how to read a result card, and what the archive data actually tells you about the product listings that win.<\/p>\n

<\/p>\n

\n
\n

94M+<\/p>\n

Google Shopping ads indexed<\/p>\n

Across all 184 countries in the archive.<\/p>\n<\/div>\n

\n

184<\/p>\n

Countries covered<\/p>\n

US leads at 22% of total archive volume.<\/p>\n<\/div>\n

\n

63%<\/p>\n

Unique retailer domains<\/p>\n

In a 1,000-ad sample \u2014 633 distinct domains appeared.<\/p>\n<\/div>\n

\n

2018<\/p>\n

Archive start year<\/p>\n

First-seen coverage from January 2018 onward.<\/p>\n<\/div>\n<\/div>\n

Source: AdSpyder platform data, June 2026.<\/p>\n

<\/p>\n

\n

In This Guide<\/p>\n

What it does<\/a>
\nArchive scale<\/a>
\nTwo search modes<\/a>
\nAll six filters<\/a>
\nReading result cards<\/a>
\nWinning title data<\/a>
\nSeasonal research<\/a>
\nStep-by-step workflow<\/a>
\nvs Free tools<\/a>
\nChecklist<\/a>
\nFAQ<\/a><\/div>\n<\/div>\n

<\/p>\n

\n

Feature Guide<\/p>\n

What is AdSpyder Shopping Ads Spy?<\/h2>\n

Shopping Ads Spy<\/a> is AdSpyder’s dedicated module for researching Google Shopping Product Listing Ads. While the Google Ads Spy<\/a> tool covers text-based Search campaigns, Shopping Ads Spy focuses entirely on PLAs \u2014 the image-and-price cards that appear above organic results when someone searches for a product on Google.<\/p>\n

The tool lets you search a product keyword or competitor domain and see exactly what other retailers have run \u2014 their product titles, price points, markets, ad longevity, and SERP positions \u2014 from a 94M+ ad archive spanning 184 countries.<\/p>\n

\n

Who this is for<\/p>\n

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.<\/p>\n<\/div>\n<\/section>\n

<\/p>\n

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The Archive: What You Are Actually Searching<\/h2>\n

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 \u2014 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.<\/p>\n

Top Markets by Shopping Ad Volume<\/h3>\n
\n\n\n\n\n\n\n\n\n\n\n\n\n
Country<\/th>\nAds Indexed<\/th>\nShare of Archive<\/th>\n<\/tr>\n<\/thead>\n
\ud83c\uddfa\ud83c\uddf8 United States<\/td>\n~21 million<\/td>\n22.1%<\/td>\n<\/tr>\n
\ud83c\uddec\ud83c\udde7 United Kingdom<\/td>\n~10 million<\/td>\n10.7%<\/td>\n<\/tr>\n
\ud83c\uddee\ud83c\uddf3 India<\/td>\n~6.1 million<\/td>\n6.4%<\/td>\n<\/tr>\n
\ud83c\uddf2\ud83c\uddfd Mexico<\/td>\n~5.6 million<\/td>\n5.9%<\/td>\n<\/tr>\n
\ud83c\udde6\ud83c\uddfa Australia<\/td>\n~4.7 million<\/td>\n4.9%<\/td>\n<\/tr>\n
\ud83c\udde7\ud83c\uddf7 Brazil<\/td>\n~4.4 million<\/td>\n4.6%<\/td>\n<\/tr>\n
\ud83c\udde8\ud83c\udde6 Canada<\/td>\n~4.2 million<\/td>\n4.4%<\/td>\n<\/tr>\n
\ud83c\uddf5\ud83c\uddf1 Poland<\/td>\n~3.7 million<\/td>\n3.9%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

Source: AdSpyder platform data, June 2026. Top 8 countries shown; 184 total in archive.<\/p>\n<\/section>\n

<\/p>\n

\n

Try Shopping Ads Spy<\/p>\n

Research competitor product listings before your next campaign<\/h2>\n

94M+ Google Shopping ads. 184 countries. Every product title, price, and run duration \u2014 searchable by keyword or competitor domain.<\/p>\n

Try Shopping Ads Spy Free \u2192<\/a><\/p>\n<\/section>\n

<\/p>\n

\n

Two Search Modes: Keyword vs Domain<\/h2>\n

The most important choice in Shopping Ads Spy is the search input mode. You are either searching by what is being advertised<\/strong> (keyword) or who is advertising<\/strong> (domain). These serve different research goals and produce different results.<\/p>\n

\n\n\n\n\n\n\n
Mode<\/th>\nInput Example<\/th>\nBest For<\/th>\n<\/tr>\n<\/thead>\n
Keyword (Broad)<\/td>\nrunning shoes<\/td>\nCategory-level research \u2014 see every brand advertising in a product space, their title structures, price ranges, and positions<\/td>\n<\/tr>\n
Domain<\/td>\netsy.com<\/td>\nCompetitor-level research \u2014 see every product a specific retailer has advertised, their full Shopping catalogue, markets, and pricing history<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
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Recommended starting sequence<\/p>\n

Start with keyword mode to map the competitive landscape \u2014 who is advertising, at what price, how long ads run. Then switch to domain mode for your top 2\u20133 direct competitors to audit their full catalogue. The two modes together give you both the market view and the individual competitor view.<\/p>\n<\/div>\n<\/section>\n

<\/p>\n

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All Six Filter Groups \u2014 What Each One Controls<\/h2>\n

Shopping Ads Spy organises its refinement options into six filter groups. Here is exactly what each controls and when to use it.<\/p>\n

\n
\n
\n
1<\/div>\n
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Major Filters<\/h3>\n

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.<\/p>\n<\/div>\n<\/div>\n<\/div>\n

\n
\n
2<\/div>\n
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Country Filter<\/h3>\n

Supports single-country and multi-country selection across all 184 countries in the archive. Your most important localisation lever \u2014 use it every time.<\/p>\n<\/div>\n<\/div>\n<\/div>\n

\n
\n
3<\/div>\n
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Time Filter (Date Range)<\/h3>\n

Defines the archive window you want to query. Essential for seasonal research \u2014 narrow to Q4 peak windows, Black Friday, or holiday periods to see exactly what competitors ran.<\/p>\n<\/div>\n<\/div>\n<\/div>\n

\n
\n
4<\/div>\n
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Search-In Filter<\/h3>\n

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.<\/p>\n<\/div>\n<\/div>\n<\/div>\n

\n
\n
5<\/div>\n
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Sort Type<\/h3>\n

Controls result ordering. Use sort to surface most-recently-seen ads first for trend research, or most-active for finding consistently-running listings.<\/p>\n<\/div>\n<\/div>\n<\/div>\n

\n
\n
6<\/div>\n
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Advanced Filters<\/h3>\n

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.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n

<\/p>\n

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Reading a Result Card: Every Field Explained<\/h2>\n

Each Shopping ad in your results appears as a card. Here is what every field means and the specific decision each one informs.<\/p>\n

\n\n\n\n\n\n\n\n\n\n\n\n
Field<\/th>\nWhat it shows<\/th>\nHow to use it<\/th>\n<\/tr>\n<\/thead>\n
Product title<\/td>\nExact listing title as it appeared in Google Shopping results<\/td>\nAnalyse title structure \u2014 brand placement, variant inclusion, character length \u2014 and benchmark against your own listings<\/td>\n<\/tr>\n
Price<\/td>\nPrice as displayed in that country’s Google Shopping, in native currency. May show original + discounted (strikethrough) where applicable<\/td>\nMap competitor price positioning per market. Identify who discounts in their feed vs who holds full price<\/td>\n<\/tr>\n
First seen \u2192 Last seen<\/td>\nThe first and last dates this listing was observed by the AdSpyder crawler<\/td>\nA long gap means the listing ran consistently \u2014 enough to keep paying for. This is your strongest signal of a profitable listing<\/td>\n<\/tr>\n
Country<\/td>\nMarket(s) where this ad appeared. Multi-country ads show “Country + N more”<\/td>\nUnderstand which markets a competitor prioritises for a given product SKU<\/td>\n<\/tr>\n
Advertiser domain<\/td>\nThe retailer domain running this listing<\/td>\nIn keyword searches, this identifies which competitors are active in your product category. Combine with domain mode for deeper audits<\/td>\n<\/tr>\n
Average position<\/td>\nMean SERP placement across all observed impressions. Lower = higher placement<\/td>\nCombine 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<\/td>\n<\/tr>\n
Product image<\/td>\nProduct image used in the Shopping listing, where available<\/td>\nBenchmark image style, background choice, and product angle against your own creative<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
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What the archive does not show<\/p>\n

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 \u2014 not as a substitute for your own campaign performance data.<\/p>\n<\/div>\n<\/section>\n

<\/p>\n

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What the Archive Tells You About Winning Product Titles<\/h2>\n

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 \u2014 which is the closest proxy for profitability the data gives you.<\/p>\n

Across a 2,000-ad sample from the archive (AdSpyder platform data, June 2026):<\/p>\n

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65.4<\/p>\n

Average title characters<\/p>\n

Median is 58 characters.<\/p>\n<\/div>\n

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50.6%<\/p>\n

50\u2013100 char titles<\/p>\n

Most common title length bucket.<\/p>\n<\/div>\n

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44.8%<\/p>\n

Include a variant term<\/p>\n

Size, color, capacity, or material.<\/p>\n<\/div>\n

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0.1%<\/p>\n

Use offer\/promo language<\/p>\n

Virtually absent from all titles.<\/p>\n<\/div>\n<\/div>\n

Source: AdSpyder platform data, June 2026. Sample n=2,000.<\/p>\n

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.<\/p>\n

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Winning title formula (from archive data)<\/p>\n

[Brand] + [Product \/ Model] + [Variant: size \/ color \/ capacity \/ material]<\/p>\n

50\u2013100 characters. Product-first. No discount mentions. No leading with the retailer name. Source: AdSpyder platform data, June 2026.<\/p>\n<\/div>\n<\/section>\n

<\/p>\n

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Using the Time Filter for Seasonal Research<\/h2>\n

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.<\/p>\n

\n
\n

63%<\/p>\n

Halloween Shopping ads appear in October<\/p>\n

Strong single-month concentration.<\/p>\n<\/div>\n

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65%<\/p>\n

Black Friday Shopping ads appear in November<\/p>\n

Most launch in the month itself.<\/p>\n<\/div>\n

\n

Oct\u2192Dec<\/p>\n

Christmas Shopping ad ramp<\/p>\n

54k Oct \u2192 69k Nov \u2192 137k Dec. Slow build, then a spike.<\/p>\n<\/div>\n<\/div>\n

Source: AdSpyder platform data, June 2026.<\/p>\n

To use this: set the Time filter to the relevant seasonal window (e.g. October\u2013November 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 \u2014 giving you a concrete brief for your own seasonal campaign structure.<\/p>\n

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December to January: worth knowing<\/p>\n

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 \u2014 useful timing to understand before setting budget expectations.<\/p>\n<\/div>\n<\/section>\n

<\/p>\n

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Step-by-Step: Research a Competitor in 10 Minutes<\/h2>\n

Use this workflow when entering a new product category, refreshing existing campaigns, or planning a seasonal push.<\/p>\n

\n
\n
1<\/div>\n
\n

Open Shopping Ads Spy<\/h3>\n

Go to adspyder.io\/shopping-ads-spy<\/a> and log in. New users can start a free trial \u2014 no credit card required.<\/p>\n<\/div>\n<\/div>\n

\n
2<\/div>\n
\n

Start with keyword mode<\/h3>\n

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 \u2014 who is advertising, at what price, and for how long.<\/p>\n<\/div>\n<\/div>\n

\n
3<\/div>\n
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Set Country and Time filters<\/h3>\n

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.<\/p>\n<\/div>\n<\/div>\n

\n
4<\/div>\n
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Scan the top result cards<\/h3>\n

Review the top 15\u201320 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.<\/p>\n<\/div>\n<\/div>\n

\n
5<\/div>\n
\n

Switch to domain mode for top competitors<\/h3>\n

Take the 2\u20133 advertiser domains from your keyword scan and run each through domain mode. You now see their full advertised catalogue \u2014 every product, every market, every price point in the archive.<\/p>\n<\/div>\n<\/div>\n

\n
6<\/div>\n
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Apply findings to your campaigns<\/h3>\n

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<\/a> to cross-reference competitor landing page strategy.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n

<\/p>\n

\n

Shopping Ads Spy vs Free Research Methods<\/h2>\n

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.<\/p>\n

\n\n\n\n\n\n\n\n\n\n\n
Capability<\/th>\nAdSpyder Shopping Ads Spy<\/th>\nGoogle Ads Transparency Center<\/th>\nManual Google Search<\/th>\n<\/tr>\n<\/thead>\n
Historical archive (from 2018)<\/td>\n\u2705<\/td>\n\u274c<\/td>\n\u274c<\/td>\n<\/tr>\n
Search by competitor domain<\/td>\n\u2705<\/td>\n\u2705 (limited)<\/td>\n\u274c<\/td>\n<\/tr>\n
Price visibility per market<\/td>\n\u2705 Native currency<\/td>\n\u274c<\/td>\n\u2705 (live only)<\/td>\n<\/tr>\n
First-seen \/ last-seen dates<\/td>\n\u2705<\/td>\n\u274c<\/td>\n\u274c<\/td>\n<\/tr>\n
Average SERP position<\/td>\n\u2705<\/td>\n\u274c<\/td>\n\u274c<\/td>\n<\/tr>\n
Multi-country coverage<\/td>\n\u2705 184 countries<\/td>\nLimited<\/td>\nOne at a time<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
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One honest note on the archive<\/p>\n

AdSpyder’s archive clusters around 2018\u20132022 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.<\/p>\n<\/div>\n<\/section>\n

<\/p>\n

\n

Where Shopping Ads Spy fits in your ecommerce workflow<\/h2>\n

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<\/a>, the Google Ads Spy<\/a> tool for Search campaign research, and Facebook Ads Spy<\/a> for what e-commerce brands run on Meta alongside their Shopping campaigns.<\/p>\n<\/section>\n

<\/p>\n

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Pre-Campaign Research Checklist<\/h2>\n
\n

\u2705 \u00a0Run keyword mode search for your primary product term in your target country<\/p>\n

\u2705 \u00a0Identify the top 3\u20135 advertiser domains active in your category<\/p>\n

\u2705 \u00a0Note title structure of listings with longest first-seen to last-seen gap<\/p>\n

\u2705 \u00a0Map price positioning per market in native currency<\/p>\n

\u2705 \u00a0Switch to domain mode and audit your top 2\u20133 competitors’ full catalogues<\/p>\n

\u2705 \u00a0Check which product variants competitors advertise that you have not yet listed<\/p>\n

\u2705 \u00a0For seasonal campaigns, apply Time filter to the relevant window and repeat<\/p>\n

\u2705 \u00a0Rewrite product titles using [Brand] + [Product\/Model] + [Variant] formula<\/p>\n<\/div>\n<\/section>\n

<\/p>\n

\n

FAQs<\/h2>\n
\nHow many Google Shopping ads does AdSpyder index?<\/summary>\n

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.<\/p>\n<\/details>\n

\nCan I search Shopping ads by competitor domain?<\/summary>\n

Yes. Shopping Ads Spy has two search modes \u2014 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.<\/p>\n<\/details>\n

\nDoes AdSpyder show competitor pricing in Shopping ads?<\/summary>\n

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.<\/p>\n<\/details>\n

\nWhat does average position mean in Shopping Ads Spy results?<\/summary>\n

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 \u2014 your strongest performance signal.<\/p>\n<\/details>\n

\nIs the Shopping Ads Spy data a live feed or historical?<\/summary>\n

Historical. The archive clusters around 2018\u20132022 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.<\/p>\n<\/details>\n

\nIs AdSpyder Shopping Ads Spy free to try?<\/summary>\n

Yes. AdSpyder offers a free trial at adspyder.io\/shopping-ads-spy<\/a>. You can start exploring the 94M+ Shopping ad archive without a credit card.<\/p>\n<\/details>\n<\/section>\n

<\/p>\n

\n

Stop guessing. See exactly what your competitors are advertising.<\/h2>\n

94 million+ Shopping ads. 184 countries. Every product title, price, and run duration \u2014 searchable by keyword or competitor domain. Start for free today.<\/p>\n

Try AdSpyder Shopping Ads Spy Free \u2192<\/a><\/p>\n<\/section>\n<\/article>\n","protected":false},"excerpt":{"rendered":"

Feature Walkthrough Quick Answer AdSpyder Shopping Ads Spy lets you […]<\/p>\n","protected":false},"author":27,"featured_media":41924,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[163],"tags":[],"class_list":["post-41920","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-shopping-ads-spy"],"acf":[],"yoast_head":"\nAdSpyder Shopping Ads Spy Guide June 2026 | Competitor Ads<\/title>\n<meta name=\"description\" content=\"Research competitor Google Shopping ads with - 94M+ product listings, 184 countries, pricing, run duration & title patterns. Try free.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/adspyder.io\/blog\/wp-json\/wp\/v2\/posts\/41920\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AdSpyder Shopping Ads Spy Guide June 2026 | Competitor Ads\" \/>\n<meta property=\"og:description\" content=\"Research competitor Google Shopping ads with - 94M+ product listings, 184 countries, pricing, run duration & title patterns. 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