Data doesn't create meaning,
There are many factors that come into play when making sense out of a dataset. Its accuracy is dependent on the quality of the data-points, the frequency at which they're captured and the subjective perception of the data scientist.
That said, when the accuracy of your prediction is represented by an excitingly narrow standard-deviation verified against hard data, a warm fuzzy feeling takes over. Feeling that can also be represented with the iconic 'cha-ching' sound.
Using less than 10 data-points to do our sales prediction analysis, we choose a road of quality over quantity. We'll be integrating a few more to refine this process by incorporating sentiment analysis and fluctuations in social trends.
Our goals extend far beyond sales prediction. Surpassing them fuels us.
Our initial product proposition will most likely leverage our sales prediction technology. Yet the data roadmap we've devised will bring lots of exciting destinations yet to be explored and we expect for them to influence the data goals in return.
Determine the probability of sales for top vendors of a SKU using multiple data-points and high-frequency signals.
brand offering Maximization
Assist vendors to maximize the power of their brand offering.
next-gen repricing tech
Devise a new framework to product repricing technology by using our advanced data signals and predictive workflow.
HOT ITEM DISCOVERY
Many marketplace selling tools offer their users suggestions of other items to sell, yet this is done based on the same users' inventory data. In our process we don't reference the users' stock or sales data at all.
When we say discovery, we mean it.
PRODUCT SPECTRUM analysis
Help vendors understand the complete spectrum of their inventory offerings and advise them of missed opportunities.
new-product market analaysisHelp inventors and innovators understand more in detail their target market and competition landscape.