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Market ResearchTop 7 Best Fashion Trend Forecasting Services of 2026
A roundup comparing fashion trend forecasting services for fashion teams, including Teneo, Kreab, and Oliver Wyman, with key tradeoffs.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
AI search agents find sources, extract figures with provenance, and aggregate written reviews. They also transcribe video reviews and podcasts.
Framework: Features 40% · Ease 30% · Value 30%
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Teneo is the best pick for brands that need multi-season direction because it connects cultural shifts to consumer behavior with synthesis across sources, turning trends into actionable narratives that guide merchandising and creative choices, while Kreab fits teams that want trend insights packaged into communications-ready storylines for launch and planning alignment.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Teneo
Connected trend narratives that link cultural shifts to consumer behavior implications
Best for: Brands needing multi-season trend direction tied to consumer and cultural signals
Kreab
Editor pickTrend insights packaged as brand communications narratives for launch and planning alignment
Best for: Fashion teams needing trend insights plus communications-ready recommendations
Oliver Wyman
Editor pickTrend insights mapped to assortments and operating implications through decision-support consulting work
Best for: Enterprises needing analytics-led fashion trend forecasting tied to merchandising decisions
Comparison Table
Teneo
enterprise_vendorDelivers market and reputational intelligence that can be used for fashion trend impact analysis across consumer segments and cultural drivers.
Connected trend narratives that link cultural shifts to consumer behavior implications
Teneo stands out with fashion trend intelligence delivered through connected cultural, consumer, and runway signals rather than category-only styling summaries. The core offering blends qualitative storytelling with structured insights to support merchandising, buying, and creative direction.
Research outputs are designed to connect trend themes to audience behaviors and brand implications. Engagement typically supports brands that need actionable direction across multiple seasons and product lines.
- +Cross-source trend synthesis connects culture, consumer demand, and runway indicators
- +Actionable thematic outputs support merchandising and creative direction decisions
- +Structured insight framing helps translate trends into product planning
- +Strong fit for multi-season work across category and audience segments
- –Outputs may feel broader than purely technical fabric or pattern guidance
- –Less suited for teams seeking single-sku, short-cycle styling micro-recommendations
- –Requires internal team context to map insights to exact assortment strategies
Private equity and portfolio leaders
Assess fashion brand reputation and risk
Advisory support for value priorities
Corporate communications teams
Coordinate messaging around fashion downturn
Faster stakeholder alignment
Show 2 more scenarios
Transformation leaders and restructuring
Guide rebrand messaging during turnaround
Coordinated external messaging
Supports transformation communications to connect trend direction with investor and employee updates during restructuring.
Corporate development diligence teams
Validate fashion trend thesis for deals
Documented diligence findings
Conducts diligence-grade research that documents findings for strategic decisions tied to fashion trend themes.
Best for: Brands needing multi-season trend direction tied to consumer and cultural signals
Kreab
agencyProvides brand and communications advisory services that include trend-driven insight work for fashion and consumer brands seeking directional market narratives.
Trend insights packaged as brand communications narratives for launch and planning alignment
Kreab stands out for translating market signals into brand-ready recommendations across communications, insights, and trend narratives. Its trend forecasting combines editorial intelligence with stakeholder and brand input to support category direction.
The offering fits teams that need both foresight and practical messaging guidance for launch planning and executive alignment. Delivery emphasizes cross-functional synthesis from research inputs into actionable trend themes.
- +Structured trend-to-narrative synthesis for fashion brand and campaign teams
- +Combines research insights with communications strategy for clearer adoption
- +Cross-functional delivery supports product, marketing, and leadership alignment
- –Trend outputs can require internal translation for merchandising calendars
- –Less suited for teams needing only raw data files without narrative work
- –Forecast specificity depends on the brand brief and internal inputs
Brand marketing and communications
Translate trend signals into launch narratives
Launch messaging alignment
Product and category leadership
Set assortment direction using stakeholder input
Actionable trend themes
Show 1 more scenario
Executive teams and brand stewards
Get foresight for multi-brand decisions
Clear executive direction
Uses cross-functional synthesis to convert market signals into consistent trend narratives for decision-making.
Best for: Fashion teams needing trend insights plus communications-ready recommendations
Oliver Wyman
enterprise_vendorProvides analytics and consulting services that support fashion executives with market sizing, scenario planning, and consumer trend strategy.
Trend insights mapped to assortments and operating implications through decision-support consulting work
Oliver Wyman is distinct because it pairs fashion trend work with management consulting methods like market structuring and decision support. The firm delivers trend sensing that translates style signals into actionable categories, assortments, and go-to-market implications.
It supports clients with analytics-driven recommendations that connect consumer behavior, demand drivers, and operational readiness for fashion teams. The engagement style suits organizations that want trend outputs tied to measurable business decisions.
- +Structured trend-to-decision frameworks for merchandising and planning teams
- +Analytics grounding links consumer signals to demand and category implications
- +Consulting rigor supports stakeholder alignment across marketing, buying, and operations
- –Trend outputs may feel less creative than boutique fashion agencies
- –Engagements rely on internal data inputs for strongest forecasting accuracy
- –Deliverables can skew toward strategy over hands-on merchandising execution
Fashion operations leaders
Build decision support for assortment shifts
Traceable decision rationale
Enterprise transformation teams
Redesign operating model for trend adoption
Coordinated implementation roadmap
Show 2 more scenarios
Continuous improvement teams
Turn trend planning into measurable workflow KPIs
Improvement backlog with owners
Diagnoses process performance, quantifies gaps, and sequences governance changes for trend intake and planning.
Commercial strategy leaders
Prioritize growth initiatives from demand drivers
Measurable growth targets
Analyzes markets, customers, and constraints to translate trend implications into a prioritized growth plan.
Best for: Enterprises needing analytics-led fashion trend forecasting tied to merchandising decisions
Groenewold
specialistProvides fashion and textile insight services that support trend direction through market research, consumer signals, and material and color perspectives for brands.
Seasonal visual trend narratives that convert research into color and theme direction
Groenewold stands out through fashion trend forecasting that connects cultural signals to practical creative direction. Core deliverables include seasonal trend reports, mood and color guidance, and theme frameworks designed for design teams.
- +Seasonal forecasting links cultural drivers to concrete design directions
- +Clear mood, color, and theme frameworks help teams translate signals quickly
- +Visual trend storytelling supports alignment across design and merchandising
- +Useful for planning collections and assortments around named concepts
- –Best fit for teams wanting guidance rather than custom data pipelines
- –Requires internal creative resources to fully implement recommendations
- –Outputs can feel broad for brands needing hyper-niche, micro-trend detail
Design teams and creative directors
Apply seasonal themes to new collections
Shared collection narrative
Retail merchandisers
Translate runway research into buying concepts
More consistent assortment decisions
Show 1 more scenario
Color and material planners
Plan palettes using trend-informed guidance
Color direction for seasons
Provides mood and color direction so teams can translate trend themes into practical palette selections.
Best for: Fashion brands and retailers translating trend research into collection planning
The Futurist Group
specialistOffers trend forecasting and fashion-relevant insights that translate macro signals into product themes and directional guidance for fashion and retail planning.
Category-specific seasonal forecasting delivered as design-ready mood and direction assets
The Futurist Group stands out by pairing runway and consumer signals into actionable seasonal fashion direction. Core offerings include trend forecasting research, visual mood development, and category-specific guidance for apparel, accessories, and retail assortments.
- +Seasonal trend research tied to apparel and retail decision-making
- +Visual mood outputs support faster design and merchandising alignment
- +Category-level insights help target assortments more accurately
- –Value depends on internal ability to convert trends into products
- –Forecast outputs may require tailoring for niche markets
- –Project timelines must fit design cycles for usable impact
Apparel product developers
Turn trend research into development briefs
Clear brief for execution
Merchandising and assortment planners
Reduce guesswork in seasonal product decisions
Better-informed selections
Show 2 more scenarios
Retail planners for accessories
Align accessories themes to season planning
Aligned category direction
Creates visual mood development and accessory guidance that teams use for assortment and campaign planning.
Design team alignment leads
Unify teams behind visual trend direction
Fewer conflicting interpretations
Delivers visual mood assets and category guidance that support shared design team alignment.
Best for: Fashion brands and retailers needing seasonal trend guidance for merchandising planning
Worn Again Technologies
specialistSupports fashion trend strategy by combining circularity-driven market research with sustainability trend mapping to help brands align product direction with consumer expectations.
Garment-centric sustainability signal mapping used to drive forecast recommendations
Worn Again Technologies stands out for trend forecasting delivered through garment-centric sustainability insights tied to real material and product signals. The service focuses on turning observed fashion behavior into actionable direction for merchandising, product planning, and brand storytelling.
- +Garment-focused forecasting ties trends to real product and materials signals
- +Actionable merchandising guidance supports product planning decisions
- +Sustainability-informed trend narratives improve brand positioning consistency
- +Category-level direction helps teams align collections and styling
- –Best suited to teams that act on merchandising direction
- –Less useful for highly niche microtrend research needs
- –Forecast outputs require internal execution ownership
Sustainability and merchandising teams
Translate garment signals into category plans
Practical plan for teams
Product planning teams
Prepare faster seasonal decisions using narratives
Faster seasonal alignment
Show 1 more scenario
Brand storytelling owners
Build sustainability-linked trend narratives
Cohesive sustainability story
Uses real material and product signals to support brand storytelling tied to forecasted trend narratives.
Best for: Brands and retailers needing sustainability-aware, action-ready fashion trend direction
TrendzBuy
specialistDelivers fashion trend forecasting research for apparel brands through curated trend reports and consumer and runway trend analysis for merchandising and product development.
Trend concept briefs that translate forecasts into concrete styling and merchandising direction
TrendzBuy stands out by packaging fashion trend intelligence into actionable merchandising and styling directions for faster decision-making. It supports ongoing trend discovery for product planning and campaign themes across apparel categories.
- +Actionable forecast outputs link trends to merchandising and styling decisions.
- +Consistent trend concept delivery supports repeatable planning cycles.
- +Category-focused inputs help align assortment themes with target audiences.
- –Trend outputs require internal team effort to execute across channels.
- –Deeper brand-specific research needs may not be fully covered.
- –Creative teams may still need additional concept development beyond forecasts.
Apparel category planners
Build repeatable trend-led assortments
More consistent collections
Campaign and marketing teams
Shape campaign themes from forecasted concepts
Theme alignment across teams
Show 2 more scenarios
Design and styling coordinators
Translate forecast visuals into styling execution
Faster styling decisions
Provides styling guidance and visual cues that design teams convert into collection-ready outputs.
Merchandising ops teams
Reduce time for collection iteration
Quicker collection iteration
Supports ongoing trend discovery and repeatable use for product planning across apparel categories.
Best for: Retail and brand teams building trend-led collections and campaigns
Conclusion
After evaluating 7 fashion trend forecasting, Teneo stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
Frequently Asked Questions About Fashion Trend Forecasting Services
How do TrendzBuy and The Futurist Group differ in what they deliver for fashion merchandising?
Which providers are best suited for brands that need sustainability-linked trend forecasting?
What’s the practical difference between category styling summaries and connected cultural or consumer insight?
Which service works well for cross-functional alignment across design, merchandising, and executive stakeholders?
Which providers are strongest when the organization needs research-grade forecasting rooted in broader market context?
How do Groenewold and Worn Again Technologies support visual storytelling for collections?
What delivery model or workflow fits teams that reuse trend outputs throughout the assortment planning cycle?
What technical inputs or outputs are typically required to get value from these services?
How should a team choose between Oliver Wyman and Kreab when the main goal is to connect trend insights to decisions?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
How to Choose the Right Fashion Trend Forecasting
We separate options most often by how well they turn fashion trend data into usable forecasts—especially across Update frequency and sourcing transparency. Those two choices affect whether your outputs stay current when you run collections or buying cycles.
Update frequency for new signals
Why it matters
Update frequency matters in fashion trend forecasting because signals shift quickly and stale inputs lead to late direction changes. When updates are regular, teams can align launches to what’s actually emerging.
How to check
Ask for the last few update dates and what changed between them. In a demo, view a sample forecast page and show how often new themes, colors, or styles appear.
Sourcing transparency and coverage
Why it matters
Sourcing transparency and coverage matter because you need confidence in where signals come from and which segments are represented. Without it, forecasts can feel like a black box.
How to check
Request a breakdown of the source types shown in the UI (for example, visual, retail, or community inputs) and what regions or categories they cover. Then check whether each forecast item references its underlying source set.
Forecast granularity by category
Why it matters
Forecast granularity by category helps you use the output for real merchandising decisions instead of one-size summaries. Finer breakdowns let you match trend direction to product types and assortments.
How to check
Pick a category you plan to work on and filter a forecast to see whether results change meaningfully. Confirm the depth is sufficient by comparing outputs for two distinct product types.
Past performance and lag visibility
Why it matters
Past performance and lag visibility matter because you need to know how forecasts behave over time. In fashion trend forecasting, even good signals can arrive late, so you need timing context.
How to check
In the demo, look for historical views that show what was forecast earlier and what happened later. Ask how the tool indicates time lag and whether archived versions are preserved.
Export-ready outputs for teams
Why it matters
Export-ready outputs matter because forecasts must become decisions, briefs, and visuals your team can reuse. If outputs don’t travel well into planning, the forecast loses value.
How to check
Try generating a sample brief or report from a forecast page and review the file contents. Check whether you can export in a format that preserves the key fields you’ll use in internal reviews.
Controls to calibrate to your market
Why it matters
Controls to calibrate to your market matter because “one forecast for everyone” rarely fits. Calibration lets you adapt direction to the audience, channels, and regions you actually buy for.
How to check
Ask to adjust market filters and see whether the forecast changes in a traceable way. Verify that the tool records what filters were applied to each output.
Red flags
- Updates are infrequent or dates are unclear
- Forecast items show no usable sourcing trail
- Exports omit the details your buying and design teams need
Fit by situation
- If your buying cycle runs weekly, prioritize Update frequency for new signals.
- If stakeholders demand evidence for direction, prioritize Sourcing transparency and coverage.
- If you plan across multiple product types, prioritize Forecast granularity by category.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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