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Here’s Why You Are Addicted to Online Shopping
Does your phone keep prompting you with the perfect jacket or the exact shoes you were thinking of getting? Does it send you discount offers on the book you were curious about? How does Myntra, Amazon, Jabong or Flipkart know exactly what you are thinking and exactly what you want? The answer is Big Data!
Data Sciences have truly become a part of our lives in unimaginable ways. With retail data increasing exponentially in volume, variety, velocity and value, retailers are aware that each of these interactions hold potential for profit. This creates a grand entry for the new-age hero, the data scientist!
Data anaytics and retail create a magical combination. For example -Target had their analytics team sit down and figure out how to tell if a customer might be pregnant, even before any announcement was made. By analyzing purchasing trends, it turned out they could not only assign a level of likelihood that a customer was pregnant, but could even predict a probable due-date. The use of data science and big data analytics aids in the following ways:
- Predicting trends and styles of popular products
- Forecasting demand for goods and services
- Identifying likely customers
- Optimizing pricing structures
A McKinsey report suggests that use of business analytics, could increase a retailer’s profit by almost 60%. Studies like this are evidenced by many retailers making a beeline to tie up with big names in software to provide them with advanced analytics, business intelligence and data management.
Let’s explore some of the ways that data scientists are changing our online shopping experience.
1. Merchandising – Improved layouts and product placements, using heat sensors and image analysis to identify consumer behavior patterns. This in turn allows for identification of shopping trends and cross selling opportunities which of course makes way for higher profits due to the combination of both internal and external data. Post purchase use information is also gathered using product sensors to determine further markets for the product.
2. Marketing – Timing is everything! Being at the right place at the right time with the right price could be what sets you apart from your competition. Data Analytics creates an opportunity for location based personalized offers with real time pricing using ‘second by second’ metrics. Campaigns can be targeted using business analytics that can segment customers, and identify the right channels to attain optimal ROI.
3. Customer Experience – Predictive Analytics creates personalized recommendations and multi-level reward programs based on purchase preference, search history, online data and sentiment analysis of social media streams. This leads to an enhancement of the customer experience across all channels and devices, both online and offline.
Who would have thought there is so much captured in a simple click of a button to buy your favourite product? The opportunities stretch far and wide, and will be interesting to watch what a new slew of big data scientists will roll out in the future.
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