Rise of Data Analytics amid Unprecedented E-commerce Boom

Updated: Feb 13, 2021

In the 2nd Quarter of 2020, driven by an evolution in purchasing pattern and accelerating technological breakthroughs, US retail e-commerce sales have rocket up to $211.5 billion, up from $160.4 billion in the 1st Quarter; the amount of e-commerce shoppers is expected to reach 2.14 billion in 2021, up from 1.66 billion global digital buyers in 2016, based on Statista data. The share of the Q2 e-commerce sales as a percentage of the total retail sales doubled in the US during the last 4 years.

Potentials come with difficulties, however, as Profitero state in their monthly report, 51% of the (more) firms expressed that “measuring and reporting on how ecommerce is performing as a distribution channel” is a top challenge.

Amidst the distressing environment, smart people spot opportunities in those challenges. The behavioral shift and the difficulties we’re witnessing will have a profound impact on our lives, and will clear more room in the e-commerce marketplace.

Therefore, data analytics becomes the primary avenue of growth for most companies, used to conduct market research, sales and profit analysis. Furthermore, it can also be used to boost exposure in online marketing campaigns.

Below are two most-used areas for data analysis by e-commerce retailers.

Product Selection

It’s of outmost importance to choose the product that has biggest potential. You can do this through collecting useful data. Here are some important dimensions you might want to consider:

  • new products like a new T-shirts that has been recently launched

  • popular products an example would be a current trending best-seller toy on amazon

  • niche products are products geared toward specific costumer groups, they have high profit margin despite lower sales

Then, base your decision on a product performance report — there are two types of perspectives included in this report:

  • Summary view — here you will obtain a summary of all key characteristics for a specific product, like categories, serial code, price, reviews and sales. Sort products by the metric you desire, and use your own rule to work out the best selection.

  • Detailed view — find out why the store and product you select succeed by either investigating the sources of their traffic and sales, their ads distributions, or by tracking them overtime.

This tool is really powerful and can greatly boost e-commerce sales by:

  • improving sales & conversions rates

  • increasing the AV of customers

  • reducing bounce rates & cart abandonments

This task can appear daunting at first, but the good new is Allfactor Analytics can provide you with featured tools to find products of your choosing. Using ours tool, merchants can gather valuable information related to product performance.

Price Optimization

Price is the nexus and the eye of the market. Knowing the optimal price will help you reach potential untapped demographics and improve your bottom line.

There are two major types of analytical techniques to determine your price.

Regression Modeling

Regression is a mathematical tool to test the correlation between two characteristics. After gathering data on products and store, you can run regression model on the various data points around sales, conversion rates, seasonality, product attributes, marketing channels. Doing this helps to fix optimal prices for your products.

Competitive Pricing

Competitive pricing, also called dynamic pricing, is the practice of modifying your price based on your competitors price information. However, it requires a constant monitoring of price updates from millions of potential products. Don’t worry, the powerful analytics designed by Allfactor will deliver these information right to your hands.

Undoubtedly, when you are looking at data in isolation, you are missing the big picture as in cross-channel reporting. Mistakes and wrong decisions can easily occur. But having all your data scattered across channels and platforms can be a real nightmare. With Allfactor’s smart e-commerce analytics tracking, you will be able to break down data silos and boost productivity, efficiency, and business agility. It helps you avoid drilling into hundreds of Shopify pages and Amazon stores. Besides, having all your data stored in one place will give you a clear insight of users’ behavior and detect any area for improvement.