Data science as the name suggests is data driven by science. It is a method to extract relevant data or insight from the data in various forms which can either be structured or unstructured. It is kind of similar to data mining.

If we talk about business terms, it helps businesses provide a richer understanding of the clienteles’ by capturing and integrating the information of the prospect’s online behaviour. At this period, e-commerce is the essence of almost every business. The world at this time is immersed in data from many sources. Data science and ‘data scientists’ have revolutionized modern business. With the boom of e-commerce, the aspect of Analysis (“A” from the DMAIC theory) has broadened by leaps and bounds. Before, we talking about the benefits, let’s talk about how it is used in e-commerce.

In the field of e-commerce, customer and sales data are integrated into a database which is further linked with the email marketing and ad platform data. A thorough analysis of these gives a data scientist a 3D view of (i) Customer lifetime value, (ii) Personality analysis, (iii) Churn detection, (iv) Customer segmentation, (v) Cohort analysis, and (vi) Trend analysis. This helps the business to work and forecast new and beneficial acquisition and retention strategies. This is exactly the evolution it has brought to the modern business.

Let me explain it this way – assume you’re on a shopping app/website browsing. You scroll downwards and see that the app/website has recommendations based on your browsing/shopping history. Did you ever ponder as to how the app/website know your preferences and suggests products that you might end up buying? That, my friend, is data science. This method can be classified under Acquisition strategy. You might initially have logged in to the website just to browse, but recommendations have a probable chance of triggering a sale. Another example of it is boosting cross-selling (selling a different product to an existing consumer). Once you select a product, most websites/apps recommend a bundle option of similar or related products. Statistics say that cross-selling is a major part of today’s e-commerce business. As a matter of fact, websites/apps these days also recommend items based on perceived customer journeys. This is also a part of the acquisition. The technique just tells you what other customers have loved so far and thus intrigues a prospect increasing the chances of a successful sale. Retention strategy is when businesses use offers, promo codes, discounts, etc. to a prospect and flash sales to retain market. Big brands use data science and scientists to monitor stock and manage promotions accordingly.

Apart from the above, data science can help a new online business to determine strength and impact of the online vs. physical brand. It can help provide detailed analysis to a retailer on physical shops vs. online sales. Also, the inclusion of data science in online business will help sellers offer personalised deals per customer based on individual browsing habits and patterns. It helps a company to anticipate customer behaviour and understand connections of customer’s product reviews and shopping behaviour with other customers further leading to successful Prediction model (surfing behaviour vs. {ed162fdde9fdc472551df9f31f04601345edf7e4eff6ea93114402690d8fa616} deal-making).

Thus, data science helps to gain sales/conversion providing optimized information about customers. Numbers speak, isn’t it?

Keywords:

Data science

Data mining

Online sales

e-commerce