How Moquer embraces synthetic data to boost customer service and privacy

An introduction to Moquer

‘Looking good and taking care of yourself is no longer just for women’. Moquer has set the goal to make exclusive hair products, especially for men, more accessible in Europe. On their webshop, they offer exclusive hair products and aim to inspire every men to create a perfect and stylish look.

  • Do you feel like your appearance needs a boost? Visit Moquer’s website.

Moquer’s challenge

Moquer was facing some key challenges, which are expressed in the following two questions:

  • Which products fit with which hair types?
  • Based on the clients hair type, how to target clients with the optimal hair products?

To really understand their customers and answer these questions, Moquer embraces a data-driven decision-making strategy. Consequently, Moquer started collecting data from all contact moments with their customers. For example, when clients request information or purchase products.

To get actionable insights from this data, Moquer aspires to collaborate with third parties that specialize in data analytics. Unfortunately, there are roadblocks. First, protecting the privacy of customers is the highest priority for Moquer. Second, legislation forbids Moquer to share their client data with third parties without the consent of their customers (General Data Protection Regulation, GDPR). Finally, when Moquer applies classic anonymization techniques to mask sensitive parts in datasets, much valuable information gets lost, while privacy risk remain present (read more: why classic anonymization fails). What now?

Illustration 1: Sharing original data with third parties

Syntho in action

The Syntho Engine is applied to convert all the sensitive data Moquer collects from their customers to privacy-preserving synthetic data. Now, Moquer is able to freely share this data in synthetic form with their business partners, because it no longer contains (privacy-sensitive) records from the original dataset. So, Moquer can collaborate with any third party data specialist in order to obtain better customer insights from their data and improve the experience of their customers while privacy is guaranteed. A win-win-win!

Illustration 2: Sharing data in synthetic form with third parties

Result

A third party has developed a recommender system on the synthetic dataset to optimize combinations between hair type and product. As a result, Moquer now (1) knows which products fit with which hair types, and (2) has reliable insights in the optimal product for a given hair type.

In other words, clients can easily filter through Moquer’s product database to find the best suitable product for their hair. This brings Moquer closer to their ultimate goal of making exclusive hair products more accessible for men in Europe and to inspire each man to create a perfect and stylish look.

Moquer menu
Moquer result

Chris Gerrits Jans – Founder & CEO

Synthetic data helped us to improve customer service, while being able to retain our high privacy standards. This would not have been possible in the era of classic anonymization, just a few years ago. I believe every e-commerce company which takes their customer’s privacy serious should consider working with synthetic data.

Explore the added value of synthetic data with Syntho

Getting familiar with the potential added value of synthetic data works best when you actually work with a synthetic version of your own original dataset. To realize this, Syntho offers the opportunity for a pilot. This pilot leads to a full synthetic version of your original dataset, supplied with a quality report and tailor-made dashboard. Consequently, you are able to fully explore the added value of synthetic data with us.

Key pilot deliverables

Fully synthetic and anonymous dataset that preserves the value of your original dataset

Quality report demonstrating the statistical significance of your synthetic dataset

Hands-on experience with synthetic data as a best practice for privacy-by-design

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