How closely are you seeing an intersection between big data and the need for analytics in eCommerce?
Understanding customers and their preferences is key to any successful business and data is vital for that understanding. And unlike traditional businesses, in eCommerce it is easier to capture a wide range of data and volume of data. So, there is more scope to serve our customers well. And we intend to do that.
How are you using these analytical solutions and what all are you analyzing using these solutions. Please share some references of the areas where the analytical solutions are being used and how.
We have been using MySQL to store our data but now we are migrating to Mongodb. We use R for our analytics. We use data in every aspect of our business – analyzing consumer trends, designing the product, user acquisition, retention, growth etc.
A critical area where analytical solutions are being used at voonik is Personalization. Today’s customer is flooded with choice and strapped for time. Voonik’s business proposition is built on solving this very problem. Instead of showing a million products to our user, we try to understand what our customers want to see and buy. This is an area where we leverage big data to understand where our customers are coming from, what their demographics, and psychographics are and when they are most likely to buy. We couple this data with in-app data on their browsing and viewing behavior to personalize their shopping feed.
How are you making use of this data and how effective is this data to get more customers. Would request you to share some used cases where using this analyzed data helped you to gain competitive edge.
Voonik has always had an edge over competitors by having a unique proposition in being a personal shopping app . We understand the need to differentiate our product from the rest of the pack. One of the rewarding cases where we found data to be very useful in this is the analysis of customer reviews. Voonik is the highest rated online shopping app in the playstore with a rating of 4.2 .We work on improving our critical success factors by listening to reviews.
Case in point : We discovered “good collection “ as one of the positive reviews we get . We worked on our product and merchandising to improve this and the results are monitored daily in reviews and improved sales .
What are the key challenges in implementing a data analytics solution?
The market is just realizing the potential of big data. So there is a lack of standardized ways of doing analytics or estimating the cost of analytics. So, this makes it challenging for management to divert valuable resources.
What is the future of data analytics in ecommerce and what is the key area of focus for data analytics in future and why?
Data analytics in eCommerce will be used to drive growth and profitability in companies with scale. The areas of focus will be the ability to capture and process more and more data and at an optimal cost.