Case Study: Marchon - Impression #1

Case Study: Predicting Products Potential

Marchon Eyewear is one of the top three eyewear companies in the world. Each year, they sell more than 20 million pairs of glasses and have more than 2 700 employees in over 20 countries.

One of the most important processes at a fashion and accessory company before starting production is determining the commercial viability of new product collections developed by the style department. In response to Covid constraints, the company decided to enlist the help of a global evaluation team to conduct an online rating of the new collections.

Logo: Marchon
Logo: Jakala (fka. H-Farm)
Pimcore Gold Partner
Customer
  • Marchon
Solution Partner
Industry
Products Used
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Customer Key Facts

1 000
Mio. Euro Turnover
2 700
Employees
26
Exclusive Brands
100
Countries
Challenge

Overtaking Covid

The evaluation team is made up of several different experts from all over the world, and they usually meet together in Italy twice a year for a rating contest about the new collections before Covid. Marchon relies on this process because they direct production plans. The challenge was to allow the company to vote even while under lockdown due to COVID-19.

Solution

Voting platform

Jakala created a digital crowdsourcing application for Marchon in which raters (Regional Sales Directors, Sales reps, and key dealers) can view new products and their key features online and rate them based on various evaluation criteria. Thanks to the feedback gathered from raters all over the world, it was possible to create a dashboard with accurate production and sales projections using this application.

Results

Engaging many for better results

Since Marchon began using this custom web application to reduce business travel costs, the evaluation process has expanded to include more people involved in the business. Even more reviewers save time during the review process because they can do so whenever and wherever they want. Overall, the 80% accuracy is higher than before.

Key Results

€ 300 000
Cost Savings
70%
Increase in Accurate Forecasts

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