Shopping the perfect outfit thanks to cross-recommendation systems

Imagine a holding who owns multiple fashion companies. Each company has its own website and mobile app, its own customer database, inventory management, etc. As a customer, I’m browsing through the website of company A, looking for a new outfit. I see this really cool shirt, but can’t find matching jeans. Luckily, the web shop of company A recommends me the jeans I’m looking for (of company B) and even offers me some cool accessories (of company C). I’m completing my outfit and buy the items. I don’t really care my outfit consist of items of 3 different companies, to me it’s the perfect look for a night out. I’m just glad I didn’t have to go through several web shops or mobile apps, make 3 different payments and expect 3 different packages at my door (let’s hope they don’t arrive at 3 different days…).

In the background, the above scenario has been made possible by combining data (both structured and unstructured) and making recommendations based on my personal profile of many different sources into 1 big data platform. In this way, the holding can optimize the shopping experience of the customer, making ‘cross-recommendations’ between the different companies the holding owns.

Currently we are working on such a recommendation system at a big company with several websites and fashion brands. Although we just started with connecting the first clickstream data to the big data platform, the first results are in! Next steps are to include data of more sources to the platform and combining all this to get valuable insights into customer behaviour and preferences.

Consumer360 graph
                                                                                                                            

This one example shows that big data is a huge asset to retail companies. As an expert in data excellence, Anchormen has proven itself several times by building platforms that combine all relevant data to enable companies to take the most effective action and act at precisely the right moment, which leads to a more fun and more relevant shopping experience for the customer. Our unique approach enables us to process data in ways that reveal connections and provide intelligent answers so companies can respond more rapidly and effectively.

We strongly believe in big data, and we believe we can make the promise of big data come true.

Want to have a more technical insight into the high level architecture of such a Consumer 360 platform? Read this blog post!

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