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The Data Behind 11.11 Sales

What was once marketed as a treat-yourself single’s day has now evolved into what many are calling the ‘retail olympics’.

In November 2018, Alibaba raked in an astounding $30.8 billion in sales during the 24-hour shopping event. The billion-dollar mark was surpassed in the first 1 minute and 25 seconds; and 2017’s bar of $25.3 billion.

Momentum

Since its inception in 2009, an increasing range of global brands has been hopping on board to take part in the 11.11 sale festivities. Now, partner merchants span over 200 countries. Aside from Alibaba, large players such as Lazada, Shopee, and Sephora also offer 11.11 deals.

The scale and focus of the fiesta are unprecedented, but 11.11 is not just about sales. The exceptional peak in viewership and active users across the online platforms present brands with a unique opportunity to launch new products and gather valuable data on consumer behavior, price sensitivity, and insights.

According to Forbes, the event has become so significant that most brands start the strategic planning cycle at least 9 months in advance. Some companies are even incorporating 11.11 sales planning as part of their 3-year plans. Ergo, it is safe to conclude that 11.11 is not about offering last-ditch attempts to clear stocks or last-minute deals but rather, being about long-term planning.

Data

The value of the sheer magnitude of data generated by 11.11 is unquestionable. Having access to it would enable a more informed decision with regards to product and price intelligence.

Before being able to formulate the right strategies, one must first be able to capture the data. You could definitely do it yourself manually and end up with an unfortunate folder of screenshots upon screenshots, or simply use a web scraper.

It’s a fool’s errand to attempt to capture all the necessary data manually during the short 24-hour window. This is like attempting to draw a portrait of an F1 car speeding past. Using a web scraper, on the other hand, is akin to using a high-speed camera. The key here is to conduct data extraction with speed.

Uses

Some examples are pricing and revenue optimization, competitor monitoring, and investment decision making.

It’s important to have a targeted data set to enable business intelligence teams to create better-informed strategies. For instance, using a web-scraper to observe and aggregate publically available data from competitors. This could include product price and sentiment data. On certain websites such a Taobao, even sales volume can be scraped.  An effective data set and analysis could reveal insights into competitors’ product positioning, sales and promo strategies, and even consumer sentiments.

Conclusion

All in all, the 11.11 sale has evolved into being about so much more than just sales. It’s about data too. Use cases are aplenty, and these valuable insights could be leveraged to create long and short term strategic plans. To meet the scale and scope of gathering such data at the necessary speed, web scrapping tools are the obvious choice.

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