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Predictive Analytics for eCommerce Industry

With the adoption of predictive analytics technology, business owners can predict future risks and understand market opportunities to make better decisions. Modern data analytics technologies can help eCommerce businesses generate more profit by adjusting their business strategies according to the latest industry trends and customer buying patterns.

Business owners, especially eCommerce companies, understand that predicting trends can be a distinguishing factor for success. Leveraging the technology and stored data will help data analysts predict customer behavior based on search history or previous shopping cart activities and build strategies. This guide revolves around why eCommerce businesses need predictive analytics in 2022 to stay competitive in the market.


Importance of Predictive Analytics in eCommerce Business

eCommerce is proliferating with the dynamic shift of buyers from traditional buying to online shopping. Research suggests that sales will account for 16% of the total retail market in 2022 (as compared to 13% in 2021). The enormous amount of data generated can help in customer profiling, traffic analysis, and web log analysis to build profitable business strategies that bring more customers. Some of the things eCommerce owners can comprehend with analysis of stored data include:

  • Predict customer experience when they are surfing the website for shopping 
  • Understand how customers engage with online stores and how long they stay on the website 
  • Identify the buying habits of the customers by understanding shopping patterns 
  • Analyze the customer preferences to make their shopping experience more personalized

Besides these standard ways to use the technology, there are multiple other data analytics examples that one can focus on to generate revenue, such as creating promotional offers and more.

ALSO READ: Data Warehousing vs. Data Virtualization – How to Store Data Effectively?

Integrating Data Analytics Software In eCommerce Business

E-commerce has grown to an exceptional level, and companies are leveraging technologies to improve customers’ online shopping journey. Retail predictive analytics – one of the most influential technologies – helps companies predict trends and distinguish themselves from the crowd. Below are the top five reasons to integrate data analytics in the eCommerce business.

  • Enhanced Business Intelligence 

With the advent of Business Intelligence tools, companies can predict customer expectations and market trends to improve overall customer experience. Using the past data available can help eCommerce businesses to get an edge against the competition. The accuracy of the decisions derived from previous data enables eCommerce owners to make quick decisions that improve profitability.

  • Automated Product Recommendation

Recommending the right additional products to customers can improve the chances of sales. Predictive customer analytics considers the purchase history, browsing history, previous customer behavior, and the current season to automate product recommendations. Prospective customers get product recommendations according to their buying behaviors, which makes them feel valued and boosts their shopping experience.

Tech giants like Spotify, Amazon, and Netflix use data from disparate sources to create a personalized user experience.

  • Management Of the Supply Chain

For an eCommerce business to grow, they need to focus on supply chain management. Predictive analytics, with the capabilities of Machine Learning, enable business owners to improve stock management, better cash flow usage, enhanced order fulfillment, and much more. Experts can identify the industry patterns to reduce overstock and prevent understock issues, helping them save money.

Inferenz helps eCommerce business owners to implement Business Intelligence tools and predictive analytics solutions to accelerate business growth. The tech experts of Inferenz have helped a Germany-based pharmaceutical company to leverage the power of data analytics in healthcare to predict diseases. Read the case study here.

  • Fraud Management 

Recognizing unusual patterns and preventing fraud are the two most crucial steps to running a profitable online business. Predictive data analytics tools help online retailers to identify customer buying behaviors and payment methods. When business owners have the correct information, they can take steps to reduce credit card payment failures, boost sales and conversions, and secure their online business.

  • Run Effective Campaigns 

Running effective campaigns is more convenient with data analytics, as it allows companies to utilize advanced MI algorithms and determine the correct product pricing based on current demand, season, time, weather, and holidays. Aligning product prices with customer preferences and market trends will ensure the success of brands while minimizing the expenses of failed campaigns.


ALSO READ: Implementing Predictive Analytics for Promotion & Price Optimization

Grow Your Business By Implementing Predictive Models With Experts 

Instead of wasting time and resources on human judgments, more and more businesses are choosing intelligent technologies to power up their sales and lead the market. Extensive data analysis allows analysts to identify significant market needs, trends, and risks and get valuable insights for generating better eCommerce business ideas.

If you intend to implement predictive analytics in your eCommerce business and accomplish your business goals, contact the predictive analytics experts of Inferenz.