Retail data is increasing exponentially in volume, variety, velocity and value with every year. Smart retailers are aware that each one of these interactions holds the potential for profit.
Next Data Science focuses on predicting trends and styles of popular products, forecasting demand for goods and services, identifying likely customers and optimizing pricing structures.
NDS also works on Customer intelligence which is basically the practice of determining and delivering data-driven insights into past and predicted future customer behaviour. To be effective, customer intelligence must combine raw transactional and behavioural data to generate derived measures.
Case Study 1:
How to co-relate the circular view of the customer which is manually a hectic task?
Next Data Science is using the Hadoop analytics by co-relating the history of the customer with the registration program.
Using the analytics part filter out the other products that the customer most likely to purchase and thus target the customer which is difficult to handle manually.
Case Study 2:
How to work on the brand sentiments of the customer that can be in-accurate if done manually?
Next Data Science offers the Big Data Analytics platform that works on the behavioural trend using the social media platform.
With the advanced brand studies, the results becomes less diagonal and can be affect able for the marketing programs.
Case Study 3: