Tracking How Bad The Situation At Farfetch Really Is
Tracking How Bad The Situation At Farfetch Really Is
A case study for web data
About Data Boutique
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Tracking How Bad The Situation At Farfetch Really Is
We’ll walk through a highly relevant case study for web data in to consumer goods
The 4Bn USD problem
4.4bn USD worth of fashion items were sold through Farfetch in 2023, but many in the industry fear 2024 for the fashion marketplace might mean the end.
Over the past six months, Farfetch faced significant challenges, including financial difficulties and strategic missteps that led to its delisting from the NYSE. Following these events, Neiman Marcus has decided against pursuing technological integration with Farfetch, and Kering announced its intention to remove its brands, including Saint Laurent, Gucci, Bottega Veneta, and Balenciaga, from the platform, which historically has been significant for Farfetch.
If Farfetch’s situation were to worsen, several groups of stakeholders would face significant risks: Brands with direct concessions on the platform could lose a vital sales channel, while boutiques might suffer due to their increasing dependency on the online retailer. Investors, including the most recent Coupang, employees, and consumers, also stand to be affected.
The speed of information
Given the significant interests at stake (4.4Bn USD in sales), it is crucial to understand not only where this is going to end but also how fast this is happening. So that those impacted the most can have the best chance to make business-saving decisions.
Why use web data
Short answer: Because it’s the best, sometimes the only, source of information many have.
Long answer: Financial results are slow to be reported (Farfetch delayed announcing quarterly results before the crisis), insider information is not granted and may be partial, biased, or misleading.
Credit card transactional data and email receipts are also a great way to track this.. if you work in a hedge fund with deep pockets for data, data scientists, and data infrastructure - but this is not the case for the rest of the class.
What stands out in the open, for everyone to see, is how the website behaves towards its customers. This is the ultimate touchpoint between the platform and the source of their revenue: customers.
What data
Traffic data
This is not strictly web data (at Data Boutique, we are often asked if they can be scraped… no, they can’t), so I’ll put it in. It is extremely relevant and also accessible. Similarweb is a great place to start.
Website traffic gives a timely measurement of the footfall of the website, which is critical to have a pulse on how the demand side of the business is responding.
Web scraped data
Web scraped data tells us how the supply side of the business is acting. Let’s see what web data can tell us and where to find it:
Brand presence
How fast is Kering pulling out from Farfetch? In which geographies do they start first? Where will they leave next? What other fashion groups or brands are and will be next?
The basic e-commerce data on Farfetch (schema E0001) for the UK, USA, Europe, China, and Japan are the perfect (and affordable) place to get this info.
Discounts
When things go south, in the wild e-commerce world, discounting and promotion are often the easiest levers to pull, so being on the watch for when and where this lever will be pulled is key. The problem with discounts also affects Farfetch's competitors since once someone starts, the others are forced to follow, in a domino effect.
Get the same data mentioned above; it will also cover this.
Price discipline
Discounting is not the only price hack common in fashion. Going rogue with arbitrages, especially in countries far away and difficult to track, can be challenging. To track this, we will need, in addition to the E0001 datasets mentioned above, the E-ADD-CODE-0001 dataset, which provides the original SKU numbers (on Farfetch called Brand ID) that allow cross-platform product matching.
Concessions
Who are Farfetch merchants? Will they stay, or will they go? When will they jump ship? Although Farfetch does not disclose merchants’ names as clearly as other players like Yoox or Zalando do, it is still visible and accessible from the same E0001 datasets mentioned for discounts and brand presence (if you have any trouble making it work, feel free to reach out).
The same datasets will serve this as well.
Inventory
Inventory depth is also very relevant in retail analysis. The newly released dataset E-INVENTORY for Farfetch covers this topic. Although Farfetch does not own inventory, it shows the depth of stock brands in concession, and merchants are letting Farfetch see. Super hot dataset, used for GMV estimates as well.
Conclusions
Whether you work in a large corp with great data analysis capabilities or a small venture, access to web data can offer valuable, timely insights on how this farfetched crisis is evolving.
About the Project
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