Relation of Big Data and E-Commerce
- 1. Big Data Analytics and its Impact in E-Commerce Presented by: Ankita Tiwari (Research Scholar) Department of Electronics and Electrical Engineering IIT Guwahati
- 2. Content Background Big Data: A Buzzword Application of Big Data Analytics in E-Commerce Impact of Big Data on E-Commerce Steps of Data Analytics in E-Commerce Methods used in Data Science Algorithms used for Big Data Analysis Benefits of using Big Data in E-Commerce My Experience Future Challenges and Drawbacks
- 3. Background Almost every action in human life, its online or offline, is motivated by the some kind of data analysis.
- 4. Contd.. Understanding the situation (i.e. based on data analysis) in a more precise and perfect way helps you to achieve best of your goals. When it comes to a business, weather it is online or offline, you are required to be at one step ahead what customers are thinking or expecting.
- 5. Contd.. The day by day increasing technologies in data collection and analysis domain are making the life of merchants more and more easier. However it is not as simple as you are thinking, due the advanced data collection methods, technology has expanded to the point where we have “huge amount of” data. Organizing, studying and understanding this information has become even more complicated because we’re inundated with endless numbers, facts, percentages and perceptions.
- 6. Big Data: A Buzzword To deal with the problem of huge data present around us we have an approach called Big Data Analytics Big data has been a buzzword floating around the digital space for a few years now.
- 7. So, what exactly is big data Basically, Big data is the combined collection of traditional and digital data from inside and outside of an environment/company. The main purpose of Its collection is to be a source of analysis and continued discovery. Particularly the introduction of big data has allowed businesses to have access to significantly larger amounts of data, all combined and packaged for analysis. This data offers insight for e-commerce businesses. E-commerce business owners can take the information from big data and use it to study trends that will help them to gain more customers and streamline operations for success.
- 8. Application of Big Data In E-Commerce To identify the specific customer who are likely to buy specific products and anticipated demand using their social media activity, browsing patterns, their purchase history, blogs and forums activity, your customer data, demographic data, weather data, geopolitical situation, etc. Recommendations, advertisements or real time offers based on advanced customer segmentation and shopping patterns, thus influencing purchase decisions and up-sell Smart shopping experience, smart merchandising and marketing Predictive analytic that enable you to optimize pricing, inventory levels, check your competition pricing, predict the hot items of the season, improve your customer service, increase customer satisfaction and your margins
- 9. Contd.. Contact your customers and prospects when they are ready to buy, on their preferred channel (social media, SMS, email) in the most appropriate location (driving, at work, at the mall) Concrete use case: you arrive at the local mall → you check in via Facebook → within a matter of minutes, you get 30% coupon for purchases today at X retailer via email or SMS
- 10. Impact of Big Data on E-Commerce Approximately 80% higher sales for companies which use Predictive Analytic than those who have never done it. About 70% of customers feel completely frustrated and annoyed when you’re sending them incoherent offers and experiences through different channels. An estimated 60% increase in business margins and a 1% improvement in labour productivity for retailers who started using Big Data (McKinsey) About half of online shoppers are more likely to shop on a site that offers personalized recommendation (invesp Consulting)
- 11. Steps of Data Analysis in E-Commerce
- 12. Methods used for Data Analysis Classification Classification is the creation of classes that represent users and use cases. Class Probability Estimation tries to predict how to classify each single individual data asset. Based on the specific question to be answered, classes are created. Regression Regression can be confused with classification methods because the process of using known values to predict an outcome is the same. But Regression is the method of trying to predict a numerical value for a particular variable for that individual data asset. Similarity Matching Similarity Matching, looks for correlation of attributes.
- 13. Benefits of Using Big Data E-Commerce It helps ecommerce companies to develop product portfolio A better pricing experience may be offered online/in store experience can be improved via virtual reality Advertising and marketing budget may be reduced Assurance in the secure payments/transaction can be increased and made easier. Overall customer satisfaction may be improved Companies also have a increased shopper analysis.
- 14. MY Experiences
- 16. E-Magazine
- 20. Major issues faced during E-Commerce experience Finding the right products/content to sell/display for a person visits the e-platform. Provide optimised pricing. To attract the perfect customer using personalized display of products/content. To have a predictive measurement of traffic on ecommerce site. To promote their offers to customers using appropriate and personalized manner when they are away from ecommerce site. Nurturing the ideal prospects. Converting shoppers in to paying customers. Retaining Customers.
- 21. How these issues are related to Big Data Ø To display the right content/product to a person needs to analyse the information related to their habits, current situations, their responses in such situations etc. That require a lot of data to be collected and analyse. Ø For predictive measurement of traffic can be estimated by analysing the behaviour of customers, like at what time generally they tends to the shopping or visits the ecommerce site, and hence peak hours can be decided. Ø We need to know that what is the best possible way is to communicate the offers/Deals and hence should be aware that, at what time which of the communication method is suitable. Therefore it is require to have the data related to the usage of e-mail, WhatsApp, phone etc with accurate timings.
- 22. Contd.. Ø To prepare a more effective prospects related to their products, we need to have data related to the a likings of a customer, their needs, budgets etc and their expectations for a particular product, hence having big data can play a crucial role. Ø By the shopping experiences of the customers we can know have an about their level of satisfaction, to have this kind of data is very important in retaining the customers who visits the ecommerce site.
- 23. Role of Big Data in solving these issues Ø Provides the data related to the customers by accessing their social media accounts, browsing patterns, shopping experiences etc. Ø Helps in identifying the relevant data and develop a trend for a particular customer, also the prices for a product can be compared and made optimised. Ø Helps Retailers to figure out where their audience is and how to attract them efficiently without killing their marketing budget using the analysis of their activities and financial status via developing a predictive model based on the data analytics. Ø Analysis of the feedback and past shopping experiences helps ecommerce sites to understand their further expectations and preparing offers based on that can attract the new and retain the existing customer in more effective manner.
- 24. Future Challenges and Drawbacks 1 of 3 Internet users say they have stopped using a company's website or have stopped doing business with a company altogether because of privacy concerns (2013 Truste study) Some real life scenarios that involved privacy concerns: – Nordstrom: customer privacy concerns after using sensors from an analytics vendor to get shopping information from customers' smartphones each time they connected to a store's Wi-Fi service – due to widespread criticism from privacy advocates, Nordstrom is no longer using the service Urban Outfitters hip clothing retailer is facing a lawsuit for allegedly violating consumer protection laws; they told shoppers who pay by credit card that they had to provide their ZIP codes. The purpose was to obtain the shopper’s address.
- 25. Contd.. Facebook is often at the centre of a data privacy controversy, whether it's defending its own enigmatic privacy policies or responding to reports that it gave private user data to the National Security Agency (NSA). Other Drawbacks may include Cybersecurity Risks. Difficulty integrating legacy systems. Manpower's and IT Resources that may increases cost as well. Data security and quality maintaining costs.
- 26. THANK YOU!