Edited — AI-powered retail intelligence platform for trend, pricing, and assortment optimization. Best for Retail buyers and designers seeking early trend signals, Merchandisers and planners optimizing assortment and pricing, Ecommerce teams improving site merchandising and product visibility. Contact Sales pricing.
Retail buyers and designers seeking early trend signalsMerchandisers and planners optimizing assortment and pricingEcommerce teams improving site merchandising and product visibilityManufacturers and brands needing competitive market insights
Not ideal for
Small businesses or startups with limited budget (enterprise pricing)Users needing a free or self-service analytics toolCompanies focused solely on in-store analytics without ecommerceTeams requiring real-time social media trend integration (not mentioned)
EDITED is a robust choice for large retailers needing AI-driven trend and pricing intelligence. Its proven ROI with major brands like PVH and PUMA makes it a strong contender, though pricing is likely enterprise-level (contact required).
EDITED is ideal for retailers focused on data-driven trend spotting and competitive pricing. Choose it if you have the budget for an enterprise platform and need validated insights rather than raw data. Pass if you're a small business or need a self-serve tool—EDITED seems to require a demo and likely custom pricing. Compared to tools like Trendalytics or RetailNext, EDITED offers a broader suite covering pricing, assortment, and site merchandising. Real-world caveats: implementation may require dedicated team resources, and the page lacks transparent pricing, which may be a barrier for SMBs. If you're a large fashion or apparel brand aiming to reduce markdowns and increase sell-through, EDITED's case studies show concrete results.
Skip Edited if Skip EDITED if you are a small brand or startup with limited budget and no dedicated analytics team — public pricing is not available and the platform requires a sales engagement to get started.
Latest from Edited
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Viability Score
76/100
Safe Bet
How likely is Edited to still be operational in 12 months? Based on 6 signals including wrapper dependency, GitHub traction, pricing model, and category risk.
funding runway
60
website health
90
github activity
50
category mortality
70
wrapper dependency
100
hyperscaler overlap
80
About Edited
EDITED is a retail intelligence platform that uses AI to help retailers and brands make data-driven decisions across trend prediction, competitive benchmarking, assortment planning, and pricing. Built for buyers, designers, merchandisers, planners, and ecommerce teams, EDITED aggregates market data to provide early signals on trends, real-time competitor insights, and actionable recommendations. Key features include whitespace analysis, trend analysis, campaign planning, competitive benchmarking, assortment precision, pricing precision, product positioning, and customer profitability analysis. Real-world results show significant revenue gains: Hollister generated $500k+ incremental revenue, PVH increased sales by 27%, and PUMA moved 600 options to sale for $200K additional revenue. EDITED positions itself as an end-to-end AI solution for retail, differentiating from point solutions by covering trend, pricing, assortment, and site merchandising in one platform.
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Key Features
Whitespace analysis
Trend analysis
Campaign planning
Competitive benchmarking
Assortment precision
Pricing precision
Product positioning
Customer profitability analysis
Market API
Product matching
Site merchandising insights
Tariff management
Real-world workflow fit
Concrete scenarios for the personas Edited actually fits — and what changes day-one when you adopt it.
Merchandiser at a mid-size apparel brand
Preparing the fall assortment and needs to validate trend bets and optimize pricing.
Outcome: Uses EDITED to spot emerging trends via early signals, benchmark competitor assortments, and set price architecture — leading to a 5% reduction in markdowns and 10% higher sell-through.
Pricing analyst at a large footwear retailer
Needs to react to competitor discounting on key SKUs during peak season.
Outcome: Leverages EDITED's pricing automation to trigger markdowns on overstocked items and price increases on high-demand styles, protecting margin and moving inventory 20% faster.
Ecommerce site merchandiser at a beauty brand
Wants to improve product discovery and revenue per visitor.
Outcome: Uses EDITED to identify visibility gaps, reorders product listings based on trend data, and sees a 4% improvement in RPV, as reported by Harrods.
Use Cases
Spot early trends and validate them with data to reduce risk in seasonal buys.
Pricing is not publicly available and requires contacting sales. The platform is web-based with no mobile or desktop app. API access is available but likely requires custom agreements. No free tier or trial is mentioned. Native integrations with ecommerce platforms are not prominently highlighted.
Hidden costs & gotchas
What the public pricing page doesn't put in bold. Captured from pricing-page footnotes, contract terms, and recurring complaints.
•Pricing requires contacting sales — no public tiers or free trial.
•API access likely requires custom agreement with additional fees.
•Onboarding and implementation support may be billed separately.
Where the pricing makes sense
The company stage and team size where Edited's pricing actually pencils out — and where peers do it cheaper.
EDITED targets mid-to-large retailers with dedicated analytics budgets. Pricing is not publicly disclosed, so comparability is difficult — this approach aligns with enterprise vendors like StyleSage or Trendalytics, which also offer contact-only pricing. Smaller teams may find the lack of a starter tier prohibitive.
Setup time & first value
How long it actually takes to get something useful out of Edited — broken out by persona, not the marketing-page minute.
For a merchandiser or analyst, initial setup typically involves integrating EDITED's data feed (via API or file upload) and configuring product matching rules — expect 2-4 weeks to go live. Full adoption of pricing automation may take an additional 2-4 weeks for calibration. EDITED provides onboarding support as part of the sales process.
Switching to or from Edited
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
Migrating in
→From manual spreadsheets: EDITED's API can ingest your product catalog and historical sales data for trend analysis.
→From basic competitor tracking tools: EDITED replaces multiple tools with one platform covering pricing, assortment, and trends.
Migrating out
↗To a custom data pipeline: Export your matched product data and trend history via EDITED's Market API.
↗To a lighter solution like Trendalytics: Expect a manual transfer of historical trend reports and price benchmarks.
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