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The following blog post is a submission for SAP Business One SEED Development Challenge.

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Predicting Fashion Trends using SCP Solution Demo Video:

Submission Details

Solution Name:

Predicting Fashion Trends using SAP Cloud Platform

Solution Description:

The fashion industry has been known for being extremely exclusive to everyone but the insiders. It is difficult for every day consumers to understand what really goes on within the fashion industry. Traditional media further reiterated this exclusivity. Today, focus in the fashion industry has drifted toward digital media, specifically fashion blogs and social media.

Fashion & trend forecasting is the prediction of mood, behavior and buying habits of the consumer at particular time of season. Understanding fashion trends forecast is one of the most arduous and calculative work for all

The solution proposed helps fashion designers, buyers and merchandisers to upload, share and analyze styles for upcoming seasons using latest technology available.

Solution Use Case

Fashion companies face several issues when it comes to predict trends and forecast new products:

  1. Low predictability: because of the volatility of demand it is extremely difficult to forecast (new products with no sales history)
  2. Short selling season: today’s fashion market place is highly competitive and the constant need to ‘refresh’ product ranges
  3. Users need to predict and spot which colors, cuts and shapes are going to hit the streets

These are metrics based on actual surveis in Fashion comapnies

 

Persona Identified:

Pain Points

  1. Low predictability: because of the volatility of demand it is extremely difficult to forecast
  2. Short selling season: today’s fashion market place is highly competitive and the constant need to ‘refresh’ product ranges
  3. High impulse purchasing: many buying decisions by consumers for these products are made at the point of purchase

Solution Detail

  1. – Ideas are instantly upload the SAP Cloud Platform to be shared with the merchandise team
  2. – Styles recognized (SAP Leonardo Visual APIs – Amazon Recognition)and categorized in boards (Pinterest) and moodboards (SCP) for analysis (no manual interventions)
  3. – Images shared in Pinterest and other social networks to gather instant trends.
  4. – SCP predictive services + sales profiles to analyze trend forecasting to rank styles
  5. – Top styles are selected and post in SAP B1 On Premise – Cloud company

Solution Technology

Web IDE, Xamarin forms (Mobile), Fiori Launchpad, Ui5 Controls,  

Picture: Fiori Launchpad with three apps (Moodboards, Style list and model detail). 

Picture: Mater Detail view with styles showing sentiment analysis from social networs (pinterest and facebook) and Forecast using predictive services based on sales profiles – since fashion products have no sales history. 

SAP Cloud Platform , AWS (S3)

Machine Learning – Visual Classification API

Pinterest and facebook APIs , Predictive and sentiment libraries from SCP , Portal (Fiori Launchpad)

Go-to-Market Strategy

Industry focus:

Fashion Companies – Merchandise Planning 

Marketing strategy:

The time it takes for a trend to disseminate into mass market products has dramatically reduced the past several years. With this pressure comes an immense need to reduce cycle time and deliver innovative products to maintain competitiveness.

This solution will be an extension for SAP Business One customers running the AFS solution. As this is decoupled from SAP B1 it can also run as standalone app. 

Road Map

IOT to give identification to garments and integration to fashion services to analyze global trends. Full integration with SAP Leonardo APIs.  

Contact Information

Partner: Argentis Systems

Country: UK , Argentina, US 

Team Name: Lucas Ritondale

Team Members: Dario Salas, Jose Espindola, Lucas Costantini

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