How we helped Plum fix their unintended out-of-stock problem?
About
Plum is one of the leading vegan, cruelty-free, and toxin-free beauty and personal care brands based in India. It is one of the few skincare brands to offer skincare based on skin textures, free from phthalates and parabens, and has a strong growing customer base.
With growing over 35% every quarter, the company serves more than 80,000 customers per month. This direct-to-consumer beauty brand makes about 40% of sales through offline channels. In terms of online, a quarter of sales in done through its own platform, and the rest are from online marketplaces.
Though this brand has anchored its name deep among the noisy space of various giant cosmetics brands, the company was losing out on sales due to small glitches on the different platforms it sells its products.
What was the problem?
Though this brand has anchored its name deep among the noisy space of various giant cosmetics brands, the company was losing out on sales due to small glitches on the different platforms it sells its products.
The brand's products are available on different online platforms. However, if there is any glitch in the platform, they lose out on sales. How? The platform automatically shows that the products are out of stock, even if the inventory is full.
Now the problem is when products are shown as out of stock frequently, it impacts your product shopping search results on the online platform. For instance, Amazon will not list your product if you run out of stock. And if this repeats often, the Amazon product ranking gets knocked down.
Besides, this brand has around 20 pin codes for which we had to check the delivery rate, how many days it would take to deliver their product, and is in stock.
Solution Offered
By Fornax.
Fornax monitored and captured all this data every hour, or twice or thrice a day, to get a clear picture of what's happening on these platforms.
To fetch this data, we developed a unique strategy using parallel and hybrid processing techniques that quickly fetched data within half an hour, whereas the existing code took around 3 hours to do the same.
With around 70% of Plum product sales happening online, these small glitches can greatly impact sales. By sorting big data faster, we bought more accurate data to the table.
We successfully built an infrastructure and mechanism to get their job done faster.
Now, the company is well aware of its products on these websites and has worked on improving the rank of its products. Also, they can track how their products are changing their ranks in real-time.
