{"id":41677,"date":"2026-05-21T11:58:31","date_gmt":"2026-05-21T11:58:31","guid":{"rendered":"https:\/\/adspyder.io\/blog\/?p=41677"},"modified":"2026-05-21T12:19:09","modified_gmt":"2026-05-21T12:19:09","slug":"how-many-ad-variants-to-run","status":"publish","type":"post","link":"https:\/\/adspyder.io\/blog\/how-many-ad-variants-to-run\/","title":{"rendered":"How Many Ad Variants Do Top Brands Actually Run? (May 2026 Data Study)"},"content":{"rendered":"
\n
Ad Library Intelligence<\/span><\/div>\n
\n

Quick Answer<\/p>\n

Based on AdSpyder’s analysis of 20,000 real campaigns, the typical Amazon Sponsored Ads campaign runs 5 variants (median)<\/strong> and the typical Google Shopping campaign runs 16<\/strong>. Single-variant campaigns are effectively nonexistent among active advertisers on both platforms. Use AdSpyder’s Ad Library<\/a> \u2014 360 million+ ads across 10 platforms \u2014 to benchmark exactly what your competitors are running right now.<\/p>\n<\/div>\n

Most answers to “how many ad variants to run” are based on opinion. Some say test three creatives. Others say generate hundreds with AI. Neither answer comes from actually measuring what active advertisers at scale do. This one does.<\/p>\n

AdSpyder pulled campaign-level data from 10,000 Amazon Sponsored Ad campaigns and 10,000 Google Shopping campaigns \u2014 the two platforms in our archive where campaign IDs map to actual marketer-defined campaigns. We added advertiser-level data from Meta and Google Search. The picture is consistent across all four: single-creative campaigns are not what top advertisers run on any platform.<\/p>\n

This blog shows you the real numbers, explains what they mean per platform, and gives you the exact workflow to benchmark your own variant count against real competitors \u2014 not invented benchmarks.<\/p>\n

\n
\n

5<\/p>\n

Median Amazon variants<\/p>\n

per Sponsored Ads campaign \u2014 51% of campaigns run 4\u201310<\/p>\n<\/div>\n

\n

16<\/p>\n

Median Shopping variants<\/p>\n

per Google Shopping campaign \u2014 87% sit in the 11\u201350 range<\/p>\n<\/div>\n

\n

239<\/p>\n

Median Meta ads per page<\/p>\n

for active Meta advertisers in AdSpyder’s real-time index<\/p>\n<\/div>\n

\n

~0%<\/p>\n

Single-variant campaigns<\/p>\n

on Amazon and Shopping \u2014 effectively nonexistent among active advertisers<\/p>\n<\/div>\n<\/div>\n

AdSpyder platform data, May 2026. Analysis of 20,000 campaigns (Amazon + Google Shopping) and 10,000 advertiser samples (Meta, Google Search).<\/p>\n

\n

In This Article<\/p>\n

Methodology<\/a>
\nAmazon: Median of 5<\/a>
\nGoogle Shopping: Median of 16<\/a>
\nMeta: 239 Per Page<\/a>
\nGoogle Search<\/a>
\nPlatform Summary<\/a>
\nBenchmark Workflow<\/a>
\nMistakes to Avoid<\/a>
\nChecklist<\/a>
\nFAQ<\/a><\/div>\n<\/div>\n
\n

How This Data Was Measured<\/h2>\n

The variant-count question seems straightforward. In practice it requires choosing the right unit of analysis per platform \u2014 because “campaign” means something different in every ad archive.<\/p>\n

\n\n\n\n\n\n\n\n\n
Platform<\/th>\nUnit Used<\/th>\nWhy<\/th>\n<\/tr>\n<\/thead>\n
Amazon Sponsored Ads<\/td>\nVariants per campaign<\/td>\nCampaign ID maps to a real marketer-defined Amazon Ads campaign<\/td>\n<\/tr>\n
Google Shopping<\/td>\nProducts per campaign<\/td>\nCampaign ID maps to a real Shopping campaign feed<\/td>\n<\/tr>\n
Meta (Facebook + Instagram)<\/td>\nAds per advertiser page<\/td>\nMeta campaign ID equals Facebook post ID \u2014 ads per page is the honest substitute<\/td>\n<\/tr>\n
Google Search<\/td>\nAds per advertiser domain<\/td>\nCampaign ID is a scraper batch grouping, not a marketer-defined campaign<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
\n

Important caveat<\/p>\n

Amazon and Google Shopping numbers are true campaign-level variant counts. Meta and Google Search numbers are advertiser-level and represent cumulative creative output \u2014 not what is live in a single campaign at one moment. Both are useful; they measure different things. Do not mix them in the same comparison.<\/p>\n<\/div>\n

\n

See what your competitors are actually running \u2014 right now<\/p>\n

360M+ ads across 10 platforms. Search by competitor domain, filter by date, get their real variant count in minutes.<\/p>\n

Explore the Ad Library<\/a><\/p>\n<\/div>\n

\n

Amazon Sponsored Ads: The Median Is 5, the Mainstream Is 4\u201310<\/h2>\n

Amazon is the cleanest dataset for this analysis because the campaign ID field in the Sponsored Ads archive actually maps to an Amazon Ads campaign the way a PPC manager understands the term. We sampled the 10,000 most-active campaigns by ad count.<\/p>\n

\n\n\n\n\n\n\n\n\n\n
Variant Bucket<\/th>\n% of Campaigns<\/th>\nWhat This Signals<\/th>\n<\/tr>\n<\/thead>\n
1 variant<\/td>\n~0%<\/td>\nEffectively nonexistent among active advertisers<\/td>\n<\/tr>\n
2\u20133 variants<\/td>\n26.9%<\/td>\nMinimal testing \u2014 usually small brands or tightly controlled SKUs<\/td>\n<\/tr>\n
4\u201310 variants (majority)<\/td>\n50.8%<\/td>\nThe mainstream: multiple images, copy angles, or product listings tested<\/td>\n<\/tr>\n
11\u201350 variants<\/td>\n20.8%<\/td>\nScaled advertisers \u2014 multiple SKUs or seasonal stacks<\/td>\n<\/tr>\n
50+ variants<\/td>\n1.5%<\/td>\nHeavy catalog advertisers \u2014 outlier max was 473 variants<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
\n
\n

Median<\/p>\n

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

\n

Average<\/p>\n

9<\/p>\n<\/div>\n

\n

90th Pct.<\/p>\n

19<\/p>\n<\/div>\n

\n

99th Pct.<\/p>\n

61<\/p>\n<\/div>\n<\/div>\n

Source: AdSpyder Amazon Sponsored Ads archive, top 10,000 campaigns by ad count \u2014 AdSpyder platform data, May 2026.<\/p>\n

The practical takeaway: if you’re running Amazon Sponsored Ads with one or two creatives, you’re below the floor of what active advertisers are already doing. The mainstream band is 4 to 10 \u2014 where 51% of campaigns sit. Getting to that range is the minimum bar, not the aspirational target.<\/p>\n

The 473-variant outlier is a large catalog advertiser, not a signal to run hundreds of versions of your hero SKU. Use AdSpyder’s Amazon Ad Library<\/a> to see how many variants your category competitors are actually running before setting your own target.<\/p>\n

\"Amazon<\/p>\n

\n

Google Shopping: Median of 16, and 87% of Campaigns Run 11\u201350<\/h2>\n

Google Shopping is structurally different from search text ads \u2014 each “variant” is a product feed item, so volume naturally reflects catalog depth as much as creative testing. The numbers are still striking: running under 10 products puts you in the bottom 8% of active Shopping campaigns.<\/p>\n

\n\n\n\n\n\n\n\n\n
Variant Bucket<\/th>\n% of Campaigns<\/th>\nImplication<\/th>\n<\/tr>\n<\/thead>\n
1\u20133 variants<\/td>\n~0%<\/td>\nPractically nonexistent among active Shopping advertisers<\/td>\n<\/tr>\n
4\u201310 variants<\/td>\n8.0%<\/td>\nSmall niche catalogs \u2014 the exception, not the rule<\/td>\n<\/tr>\n
11\u201350 variants (dominant)<\/td>\n86.6%<\/td>\nThe norm \u2014 brands advertising category depth, not just hero SKUs<\/td>\n<\/tr>\n
50+ variants<\/td>\n5.5%<\/td>\nLarge retailers \u2014 outlier max was 2,255 variants in one campaign<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
\n
\n

Median<\/p>\n

16<\/p>\n<\/div>\n

\n

Average<\/p>\n

23<\/p>\n<\/div>\n

\n

90th Pct.<\/p>\n

40<\/p>\n<\/div>\n

\n

99th Pct.<\/p>\n

99<\/p>\n<\/div>\n<\/div>\n

Source: AdSpyder Google Shopping ads archive, top 10,000 campaigns by ad count \u2014 AdSpyder platform data, May 2026.<\/p>\n

\n

Shopping vs. text ad variants<\/p>\n

A Shopping campaign with 16 variants is advertising 16 different product listings \u2014 not 16 headline rewrites. If you’re comparing to text ad creative testing, Amazon’s numbers (median: 5) are the more direct parallel. Use AdSpyder’s Shopping Ads Spy<\/a> to see how competitors structure their product feeds.<\/p>\n<\/div>\n

\n

Meta (Facebook + Instagram): 239 Ads Per Active Page, and 88% Are Images<\/h2>\n

Meta’s campaign ID structure doesn’t support true campaign-level variant analysis the way Amazon does. What we measure instead is ads per advertiser page \u2014 and the numbers reveal the real scale of creative production at the top of the market.<\/p>\n

\n\n\n\n\n\n\n
Data Source<\/th>\nMedian Ads\/Page<\/th>\n99th Percentile<\/th>\nWhat It Represents<\/th>\n<\/tr>\n<\/thead>\n
Meta Real-time Feed<\/td>\n239<\/td>\n3,253<\/td>\nAds currently live or recently active (rolling ~90 days)<\/td>\n<\/tr>\n
Meta Historical Archive<\/td>\n712<\/td>\n23,989<\/td>\nAll ads ever captured per page since 2018<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

Source: AdSpyder Meta real-time and historical archives, top 10,000 advertiser pages \u2014 AdSpyder platform data, May 2026.<\/p>\n

The real-time number is the operationally useful one: the median active Meta advertiser in AdSpyder’s feed has 239 ads on record. That’s their recent active creative stack \u2014 not lifetime production.<\/p>\n

There’s a second finding here that challenges a widespread assumption. Across AdSpyder’s Meta historical archive of 44 million+ ads, 88% are static images and 12% are video<\/strong> (AdSpyder platform data, May 2026). The “video-first Meta strategy” narrative doesn’t match what most advertisers are actually running. The dominant format is static imagery by a wide margin. Build your Meta variant testing to match that reality: mostly image-led, with a separate video section.<\/p>\n

\n

What this means for your Meta strategy<\/p>\n

If a competitor has 239 ads on their page and you’re running 15, the gap is not strategy \u2014 it’s creative production volume. Use Facebook Ads Spy<\/a> and Instagram Ads Spy<\/a> to measure the gap precisely, then build the production system that can close it.<\/p>\n<\/div>\n

\n

Google Search: 3,147 Ads Per Advertiser \u2014 Volume Compounds Over Time<\/h2>\n

For Google Search, the total ad volume per advertiser domain across AdSpyder’s full archive (164M+ Google Search ads) is the best available measure. This is a lifetime view \u2014 the cumulative output of years of PPC testing \u2014 not a snapshot of what is live at any one moment.<\/p>\n

\n
\n

Median Ads \/ Domain<\/p>\n

3,147<\/p>\n<\/div>\n

\n

Average<\/p>\n

9,866<\/p>\n<\/div>\n

\n

99th Percentile<\/p>\n

89,279<\/p>\n<\/div>\n<\/div>\n

Source: AdSpyder Google Search archive, top 10,000 advertiser domains by ad count \u2014 AdSpyder platform data, May 2026.<\/p>\n

The mean is much higher (9,866) because outlier advertisers pull it up \u2014 the single highest-volume domain in the sample had 11.8 million ads captured. That is the output of years of consistent creative testing, not one aggressive launch cycle. The advertisers with the largest ad libraries got there by running, testing, and refreshing systematically \u2014 volume compounds.<\/p>\n

Use Google Ads Spy<\/a> to see what competitors are currently running in search and how their current count compares to their historical volume. The gap between those two numbers tells you how aggressively they refresh creative.<\/p>\n

\n

Platform Benchmark Summary: What Your Minimum Target Should Be<\/h2>\n
\n\n\n\n\n\n\n\n\n
Platform<\/th>\nUnit<\/th>\nMedian<\/th>\nDominant Bucket<\/th>\nMinimum Target<\/th>\n<\/tr>\n<\/thead>\n
Amazon Sponsored<\/td>\nVariants \/ campaign<\/td>\n5<\/td>\n4\u201310 (51% of campaigns)<\/td>\n4 variants to enter the mainstream<\/td>\n<\/tr>\n
Google Shopping<\/td>\nProducts \/ campaign<\/td>\n16<\/td>\n11\u201350 (87% of campaigns)<\/td>\n11 products to leave the thin-catalog tier<\/td>\n<\/tr>\n
Meta (recent)<\/td>\nAds \/ page (active)<\/td>\n239<\/td>\nTop 10k advertiser pages<\/td>\nBuild a creative system, not just a test batch<\/td>\n<\/tr>\n
Google Search<\/td>\nAds \/ advertiser (lifetime)<\/td>\n3,147<\/td>\nTop 10k domains<\/td>\nVolume is cumulative \u2014 test consistently over time<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

Source: AdSpyder Ad Library \u2014 20,000 campaign sample (Amazon + Google Shopping) and 10,000 advertiser sample (Meta, Google Search), May 2026.<\/p>\n

\"How<\/p>\n

\n

How to Benchmark Your Competitors’ Variant Count Using AdSpyder<\/h2>\n

The numbers above tell you what top advertisers do across the market. What you need is what your specific competitors are doing. Here is the exact workflow:<\/p>\n

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

Open Ad Library and select your platform<\/h3>\n

Go to AdSpyder’s Ad Library<\/a>. Choose the platform your competitor advertises on. Results are platform-specific \u2014 each archive is indexed separately.<\/p>\n<\/div>\n<\/div>\n

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

Search by competitor domain, not keyword<\/h3>\n

Enter the competitor’s domain. Domain search surfaces every ad that specific advertiser has run on the chosen platform \u2014 their full creative strategy, not just ads that match a search term. Use Domain Analysis<\/a> for a cross-platform view.<\/p>\n<\/div>\n<\/div>\n

\n
3<\/div>\n
\n

Filter to the last 30\u201390 days<\/h3>\n

Set the date filter to isolate currently running creatives. The total result count is the competitor’s current active variant stack on that platform. This removes historical noise and gives you a live benchmark.<\/p>\n<\/div>\n<\/div>\n

\n
4<\/div>\n
\n

Categorise variants by type \u2014 not just count them<\/h3>\n

As you scroll results, categorise by what is actually being tested: different hooks, price angles, image vs. video, different CTAs. What kind of variants they run matters more than the raw number. Ten near-identical ads are not ten meaningful variants.<\/p>\n<\/div>\n<\/div>\n

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

Set up ongoing tracking so changes do not surprise you<\/h3>\n

Add competitors to an AdSpyder project to monitor their creative volume over time. Across AdSpyder’s user base, 1,104 projects actively track 3,687 competitors for exactly this reason \u2014 catching creative pivots before they show up in your own performance metrics. (AdSpyder platform data, May 2026)<\/p>\n<\/div>\n<\/div>\n

\n

Three Mistakes That Undermine Ad Variant Strategy<\/h2>\n
\n

Mistake 1: Treating the “3 to 5 creatives” rule as an ongoing steady-state<\/h3>\n

Three to five is a reasonable floor for a single test cycle. It is not what top advertisers run at scale. 51% of Amazon campaigns run 4\u201310 variants and 87% of Shopping campaigns run 11\u201350. Staying at “3 creatives” permanently is an execution bottleneck masquerading as a strategy.<\/p>\n<\/div>\n

\n

Mistake 2: Conflating volume with meaningful variation<\/h3>\n

Ten ads with the same hook, same offer, and slightly different background colours are not ten ad variants \u2014 they are one concept with ten executions. Meaningful variants test different hypotheses: a different emotional angle, a different offer structure, a different format. Volume without structure creates noise, not learning.<\/p>\n<\/div>\n

\n

Mistake 3: Benchmarking against industry averages instead of direct competitors<\/h3>\n

The numbers in this blog are market-wide benchmarks. What matters is what the 3\u20135 brands competing for the same customers are running. Benchmark against those specific competitors \u2014 not the median of 44 million archived ads. AdSpyder lets you do that in minutes.<\/p>\n<\/div>\n

\n

Ad Variant Strategy Checklist<\/h2>\n
\n
\n

\u2713<\/span><\/p>\n

Look up your top 3 competitors in AdSpyder’s Ad Library<\/a> and record their active variant count per platform \u2014 not from a benchmark table.<\/p>\n<\/div>\n

\n

\u2713<\/span><\/p>\n

On Amazon: confirm at least 4 variants per campaign. Below 4 puts you in the bottom quartile of active advertisers in our 10,000-campaign sample.<\/p>\n<\/div>\n

\n

\u2713<\/span><\/p>\n

On Google Shopping: confirm your campaign covers at least 11 products. Under 10 puts you in the 8% thin-catalog tier.<\/p>\n<\/div>\n

\n

\u2713<\/span><\/p>\n

On Meta: track your Facebook page’s total ad count. The median active advertiser has 239 ads on record. Measure the gap and set a quarterly production target.<\/p>\n<\/div>\n

\n

\u2713<\/span><\/p>\n

Categorise your variants by type: hook angle, visual format, offer, and CTA. Ten executions of the same concept do not count as ten variants.<\/p>\n<\/div>\n

\n

\u2713<\/span><\/p>\n

Set up ongoing competitor monitoring in AdSpyder so creative volume changes trigger a review before they show up in your performance data.<\/p>\n<\/div>\n

\n

\u2713<\/span><\/p>\n

Use Text Ad Generation<\/a> and Image Ad Generation<\/a> to accelerate variant production once you know which angles competitors are testing.<\/p>\n<\/div>\n<\/div>\n

\n

AdSpyder Ad Library<\/p>\n

Stop guessing. Start benchmarking against what competitors actually run.<\/p>\n

360M+ ads indexed across 10 platforms. Search any competitor, see their full creative stack, and set your variant target based on real campaign data. Used by 23,000+ marketers and agencies.<\/p>\n

Try AdSpyder Free<\/a>
\nExplore Google Ads Spy<\/a><\/div>\n

23,000+ users \u00b7 10 platforms \u00b7 360M+ ads indexed<\/p>\n<\/div>\n

\n

Frequently Asked Questions<\/h2>\n
\nHow many ad variants should I run at once? +<\/span><\/summary>\n

On Amazon Sponsored Ads, 51% of active campaigns run 4\u201310 variants with a median of 5. On Google Shopping, 87% run 11\u201350 with a median of 16. On Meta, the median active advertiser has 239 ads on record. Benchmark your specific competitors using AdSpyder’s Ad Library rather than relying on any single market-wide number.<\/p>\n<\/details>\n

\nWhat percentage of campaigns run only one ad creative? +<\/span><\/summary>\n

Effectively zero, based on AdSpyder’s analysis of 10,000 Amazon campaigns and 10,000 Google Shopping campaigns. Single-variant campaigns are nonexistent among the top active advertisers on both platforms. (AdSpyder platform data, May 2026)<\/p>\n<\/details>\n

\nIs the “3 to 5 creatives” rule accurate? +<\/span><\/summary>\n

It is a reasonable floor for a single test cycle \u2014 but not what top advertisers run at scale. 50% of Amazon campaigns run 4\u201310 variants and 87% of Google Shopping campaigns run 11\u201350. Three to five is where you start testing. Treating it as the ongoing steady-state is an execution bottleneck.<\/p>\n<\/details>\n

\nHow can I see how many ads my competitors are running right now? +<\/span><\/summary>\n

Use AdSpyder’s Ad Library<\/a>. Search by competitor domain on your target platform, set the date filter to the last 30\u201390 days, and the result count is their current active variant stack. For a cross-platform view, use the Domain Analysis<\/a> tool.<\/p>\n<\/details>\n

\nWhy do Google Shopping campaigns have more variants than Amazon? +<\/span><\/summary>\n

In Google Shopping, each variant is a product feed item \u2014 so campaign volume reflects catalog depth. A retailer with 30 SKUs naturally runs 30+ variants. Amazon Sponsored Ads more closely mirrors traditional creative testing: distinct ads with different images or copy angles. This is why the medians differ (5 vs. 16). Do not use one benchmark to judge performance on both platforms.<\/p>\n<\/details>\n

\nDoes running more ad variants always improve performance? +<\/span><\/summary>\n

Not automatically. Volume without intentional variation creates noise, not learning. The advertisers running 239 Meta ads are not running 239 versions of the same idea \u2014 they are systematically testing different hooks, offers, formats, and audiences. Volume and structure need to go together for variant testing to produce useful signal.<\/p>\n<\/details>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Ad Library Intelligence Quick Answer Based on AdSpyder’s analysis of […]<\/p>\n","protected":false},"author":27,"featured_media":41680,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-41677","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"acf":[],"yoast_head":"\nHow Many Ad Variants to Run in 2026? 20,000+ Campaigns Data<\/title>\n<meta name=\"description\" content=\"Real data from 20,000 Amazon & Google Shopping campaigns reveals how many ad variants top brands actually run - why 1 is never the answer.\" \/>\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\/41677\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How Many Ad Variants to Run in 2026? 20,000+ Campaigns Data\" \/>\n<meta property=\"og:description\" content=\"Real data from 20,000 Amazon & Google Shopping campaigns reveals how many ad variants top brands actually run - why 1 is never the answer.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/adspyder.io\/blog\/how-many-ad-variants-to-run\/\" \/>\n<meta property=\"og:site_name\" content=\"AdSpyder\" \/>\n<meta property=\"article:published_time\" content=\"2026-05-21T11:58:31+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-05-21T12:19:09+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/adspyder.io\/blog\/wp-content\/uploads\/2026\/05\/How-Many-Ad-Variants-to-Run.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"1774\" \/>\n\t<meta property=\"og:image:height\" content=\"887\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/webp\" \/>\n<meta name=\"author\" content=\"Abhishek Singh\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Abhishek Singh\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"12 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/adspyder.io\/blog\/how-many-ad-variants-to-run\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/adspyder.io\/blog\/how-many-ad-variants-to-run\/\"},\"author\":{\"name\":\"Abhishek Singh\",\"@id\":\"https:\/\/adspyder.io\/blog\/#\/schema\/person\/019f20ac9229517cfc2d66b908b656f0\"},\"headline\":\"How Many Ad Variants Do Top Brands Actually Run? 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