ВОЛНА

Fashion Intelligence — Data Driven

Track the Wave.
Know What's Next.

Volna combines Google Trends and Pinterest data to forecast the rise and fall of luxury fashion brands — giving buyers, brands, and researchers a data-driven edge.

21

Brands Tracked

5yr

Data History

2

Signal Sources

6mo

Forecast Window

Scroll

Fashion moves in waves.

Some brands are rising. Others are peaking. Some are fading. Knowing the difference before it happens is what separates reactive buying from strategic buying.

Volna tracks search interest and consumer intent signals across 21 luxury fashion brands, applies time series forecasting, and generates clear investment signals so you can make confident, data-backed decisions.

Live signal preview — current brand momentum

Prada
BUY ↑
Miu Miu
BUY ↑
Valentino
BUY ↑
Louis Vuitton
HOLD →
Balenciaga
HOLD →
Sacai
WIND ↓

Methodology

How Volna Works

01

Data Collection

Weekly trend data pulled from Google Trends and Pinterest, capturing both search intent and aspirational consumer behavior across the US market.

02

Forecasting

Holt-Winters exponential smoothing projects each brand's interest trajectory 6 months forward, accounting for momentum and seasonal patterns.

03

Lifecycle Classification

Each brand is classified into one of four stages — Rising, Peaking, Stable, or Declining — based on recent momentum and historical performance.

04

Investment Signals

Google and Pinterest signals are cross-validated to produce a combined Buy, Hold, or Wind Down signal with upgraded conviction when both platforms agree.

05

AI Interpretation

Plain-language brand interpretations grounded in consumer psychology research and cultural context, generated fresh from live data each run.

Coverage

21 Luxury Brands Tracked

Gucci
Prada
Balenciaga
Saint Laurent
Versace
Bottega Veneta
Alexander McQueen
Burberry
Dior
Louis Vuitton
Givenchy
Valentino
Fendi
Dsquared2
Rick Owens
Sacai
Vivienne Westwood
Miu Miu
ERD
Jean Paul Gaultier
Comme des Garcons

Data Sources

Built on Real Signal Data

Google Trends

Weekly aggregate search interest for fashion brand keywords in the US market via pytrends. Captures active consumer research and purchase intent.

Pinterest Trends API

Weekly aggregate pin and save counts per brand keyword. Captures aspirational consumer behavior and forward-looking purchase planning intent.

Groq AI

AI-generated brand interpretations using Llama 3.3 70B, grounded in consumer psychology research, cultural theory, and cited academic sources.

Who It's For

Built for the Industry

01 — Retail Buyers

Make data-backed purchasing decisions.

Know which brands are gaining momentum before the market catches up. Replace intuition with quantified trend signals and 6-month forecasts.

02 — Fashion Brands

Monitor your market positioning.

Track your own search trajectory alongside competitors. Understand where you sit in your lifecycle and what the data says about the months ahead.

03 — Investors

Track consumer interest as a leading indicator.

Identify rising brands early and spot declining ones before they peak. Cross-platform signal validation adds conviction to investment decisions.

04 — Researchers & Students

Explore fashion at the intersection of data science.

A working platform demonstrating applied machine learning, time series forecasting, and AI-powered analysis in the context of luxury fashion.

21

Brands Tracked

5yr

Data History

2

Data Platforms

6mo

Forecast Horizon

An independent data science project.

Volna is developed independently to demonstrate applied machine learning and trend forecasting in the luxury fashion industry. The platform uses Google Trends, the Pinterest Trends API, and the Groq AI API to collect, analyze, and interpret brand interest data.

No personal user data is collected or stored at any point. All analysis is performed on aggregate, anonymized trend signals only.