Quick read
How to read magicpin.in quickly
magicpin.in looks like shopping. Traffic estimates are limited, so use the trust and structure modules first. Current AI trust scoring is 15/100.
What to do next
- The stack appears to include React.
- Open the Traffic tab if you need audience scale and geography before outreach.
- Open the Business tab if trust, monetization, or positioning is your first decision filter.
Provider Completeness
34/56 fields populated (61%)
Providers with missing fields
ads: 0/5publisher: 3/5files: 2/3traffic: 0/10radar: 0/4
View field-level status
visual: 4/4
All expected fields present
meta: 3/3
All expected fields present
seo: 5/5
All expected fields present
dns: 4/4
All expected fields present
ads: 0/5
Missing: isAdvertiser, advertiserIds, advertiserNames, resultCount, transparencySignals
publisher: 3/5
Missing: directCount, resellerCount
files: 2/3
Missing: robotsSitemapUrls
traffic: 0/10
Missing: monthlyVisits, globalRank, countryRank, bounceRate, avgVisitDuration, pagesPerVisit, topCountry, topRegions, topKeywords, trafficSources
whois: 6/6
All expected fields present
radar: 0/4
Missing: globalRank, rankBucket, categories, sourceTimestamp
ai: 7/7
All expected fields present
Why this module matters
Business signals help answer “is this a real opportunity?”
Use the business tab to understand trust, monetization, audience fit, and brand posture before you spend time on outreach, partnerships, or competitive teardown work.
- Trust score and sentiment are your first risk screen.
- Business summary and audience notes speed up qualification.
- Ads and monetization patterns reveal how the site captures value.
Business Intelligence
Business Profile
magicpin is a hyperlocal savings and discovery platform that connects users with restaurants, shops, and services nearby, offering exclusive deals, cashback, and rewards for offline and online purchases.
Business ModelMarketplace / Aggregator with affiliate and commission-based revenue from partner merchants
Target AudiencePrice-conscious consumers in Indian urban areas seeking discounts on dining, shopping, and local services; primarily millennials and Gen Z in metro cities
Classification
CategoryShopping
Sub-CategoryCoupons & Offers
local discoverydealscashbackrestaurantssavingsrewardshyperlocalvouchersfintech
Trust & Risk
Trust Assessment
Trust Score15/100
SentimentProfessional
Spam DetectionClean
Publisher Monetization
ads.txtFound
Ad Systems
google.com
Monetization Signals
has_ads_txthas_ad_systems
AI Visual Analysis
Design StyleModern Consumer App
VibeTrustworthy, Savings-focused, Approachable
UI Score8/100
Detected Logo Textmagicpin
IAB Taxonomy
IAB CategoryShopping
IAB Sub-CategoryCoupons & Offers
Confidence92%
local discoverydealscashbackrestaurantssavingsrewardshyperlocalvouchersfintech
Business Insights
Business Model
Marketplace / Aggregator with affiliate and commission-based revenue from partner merchants model detected
Trust Level
Low trust with 15/100 score
Audience
Price-conscious consumers in Indian urban areas seeking discounts on dining, shopping, and local services; primarily millennials and Gen Z in metro cities
Keep exploring
Keep exploring from this report
Good pSEO pages should not strand the visitor. These links keep the journey moving through adjacent directories and comparable live reports.
Browse Shopping sites
Move from this single report into the broader market cluster.
Browse Coupons & Offers sites
Use the topic route when audience and editorial intent matter more than category.
Browse React websites
Pivot from one domain into a stack-based discovery path.
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