Big data is either in structured or unstructured form. Necessary details about customers such as name; address, contact number, purchase history, etc. that the companies store in their customer relationship systems are referred to as structured. On the other hand, data derived from customer’s social media posts, likes/dislikes, browsing-history, etc. can be termed as unstructured. Both forms are crucial for the success of any given e-commerce website.

Who Is Buying What, When, And From Where?

Big data combined with various eCommerce analytics tools like KISSmetrics, Metrilo, Crazy Egg, Google Analytics, HumCommerce, RetentionGrid, Metrilo, Clicky, etc. prove to be life-savers. These solutions can help administrators to track customers based on their sex, location, age, device, and other demographics. Such analytics solutions can also help in retention analysis.

The data obtained from these programs can help sellers to focus more on areas of their website that manage to keep customers engaged for hours.

Increasing Up-selling And Cross-selling Revenues 

Which steps are parts of the buyer’s journey? In most cases, buyers select the products that they wish to buy and read reviews. Then, they check for discount codes and purchase the item from wherever they get the best deal.

Keeping track of this customer journey is not possible with human analysts. However, new-gen analytics tools with an intelligent algorithm can help in understanding the buyer’s online behaviors.

Segment-wise data-rich profiles of customers can be created based on past purchases, clicks; products viewed, favorite brands, etc. Personalized product recommendations can be made by the predictive intelligence system from time to time. They can be programmed for predicting and displaying the right product recommendations on the portal as well as in marketing emails. 

Ecommerce personalization software programs like RichRelevance, OptinMonster, Yusp, Monetate, Bunting, Dynamic Yield, Barilliance, Evergage, Cxsense, Emarsys, Einstein (Salesforce Commerce Cloud), Apptus, CloudEngage, and GeoFli, etc. can derive the best out of big data. 

Experts suggest companies witnessed as much as 40.38 percent increase in their revenue within 36 months period after adopting predictive intelligence tools. 

You can opt for a reputed Big Data application development firm to get these and other widgets deployed on your e-commerce portal. Most widgets also integrate with ready to use solutions like Shopify, Magento e-commerce, etc.

Data-Backed Price Management

Some online market places have algorithmic price optimization programs in place. These software solutions keep the product prices in line with those displayed on the competing shopping portals. The program uses big data for identifying customer perception and adjusts prices depending on the product’s demand, availability, as well as other programmed factors. Put simply; the system resembles Wall Street high-frequency trading.

Deloitte recently released their research work on the impact of advanced pricing analytics on businesses. It pointed out how online sellers witnessed an increase in their business margins by 2 to 7 percent after implementing data-backed price management. As per the study, the ROI reported by participating companies during the 12 months after implementing the technology showed a whopping increase of 200-350 percent.

Big Data In Inventory Management

Several studies have pointed out that following inaccurate inventory management practices can result in productivity losses, plunging profits, and upset consumers. Thankfully, predictive analytics platforms, combined with big data, offer the perfect solution.  

The demand for various items depends on several aspects like holidays, weather patterns, political factors, and so on. Thanks to predictive analytics tools, firms can increase or reduce their inventory accurately and efficiently even in case of demand fluctuations. 

Companies have been using seasonal consumption data for ages. However, these days, big data offers precise predictions concerning upcoming purchase trends. The systems make suggestions to accommodate seasonal fluctuations.

Software programs can calculate the possible weather impact on people’s shopping habits. The logic is simple; if the climatic predictions indicate a warmer climate; buyers would opt for pure cotton garments. On the other hand, colder climates would trigger the sales of jackets, coats, and of course, the barbecue.

Not just brick and mortar stores but even online portals end up with excessive amounts of stocks at their warehouses due to inaccurate predictions about consumers’ demands. Then, they are left with no other option but to sell the stock at reduced prices and make way for the new stuff according to the market.

Big data, combined with data analytics systems, can help firms by adjusting inventory automatically.

Handling Product Recall Cases Efficiently

Small and large brick and mortar, as well as online sellers, need to act fast when it comes to handling product recall cases. Big data helps in quickly highlighting problematic batches, product shipment number, and buyer’s contact details within minutes.

The world’s top online shopping portal, Amazon also uses data analysis tools as a part of the products recall mechanism. The firm monitors customer feedback and health hazard warnings on various government websites to determine potential recalls.

Use Of Big Data For Advertising 

Several ad agencies around the world have their in-house expertise for analyzing their client’s vast amounts of data these days. 

This is helping them to offer the best possible impact and reach for every client’s advertisement. Predictive analytics can be used for studying user behavior patterns, and selected groups of customers can be targeted with ads. The process helps in avoiding controversial ad fraud issues. 

Selecting Shipping And Payment Options According To The Customer’s Product Return Rate

Sellers, especially those in the fashion industry, often come across customers who order multiple products with free shipping and return half of them, highlighting some or the other issue. 

Big data powered AI solutions make sure that buyers who return products more frequently do not get free shipping as well as cash on delivery option. Such customers are offered products with the lowest return rate and chargeable shipping options to ensure the shopping site’s overall return rate remains under control.

Are you looking for a custom eCommerce development company that can help your shopping site with widgets, big data, and AI-powered software solutions? You should contact Smart Sight Innovations. Their team of experts has deployed eCommerce development solutions for large online sellers as well as startups.