Based on your analysis of customer behaviour, you may also employ dynamic pricing for the highly demanded products. All your eCommerce merchandising woes may be covered by qualified third party software solution providers who could use high-end techniques like machine learning and SaaS for an added benefit.
4. About us
Tagalys was built on the learnings of building & scaling an online store. We
were not very successful as retailers, but we learnt a lot about online retail –
the challenges, costs & pain points.
In 2011, Antony resigned from his management consulting job at Deloitte in
New York to embark on his entrepreneurial journey as an online retailer. Due
to his management consulting background, he sought technology services
from Palani (PC), who had his own firm serving hundreds of customers across
verticals.
During this venture, both Antony & PC realized that the e-commerce
platforms had no clue what products to display to visitors. Antony worked
with PC & team, writing the code to start collecting analytics and building
prediction models to determine what products to show visitors.
Fortunate or not, this venture hit the graveyard of startups, for Tagalys to be
born. Palani joined Antony and they worked to build an intelligent engine that
learns visitor interest to merchandise online stores effectively.
“To become the worlds best Merchandising Engine for online retail”
Today, we process over half a billion retail data points a month giving us
insights across verticals. We do not want to be a product, but your extended
partner that collaborates with you.