“E-commerce is not an industry; e-commerce is a tactic.” – Tobias Lütke

Are you from the eCommerce industry? Are you looking at increasing sales and revenue? Are you skeptical about sales whenever a new strategy is tried out? Are you unclear about past happenings and future outcomes?

If the answer is ‘Yes’, you need comprehensive data analysis in your eCommerce business segment.

Revenue in the eCommerce market is projected to reach US$1,011.00bn in 2023. Revenue is expected to show an annual growth rate (CAGR 2023-2027) of 11.51%, resulting in a projected market volume of US$1,563.00bn by 2027.

The eCommerce industry is one of the fastest growing segments around the globe, with increasing demand and supply patterns. The world of technology has escalated the eCommerce and mobile industry and the mode of shopping has changed.

Growth has brought forward certain challenges to the eCommerce industry like severe competition, security and privacy, customer service, logistics, brand and reputation management, and staying abreast with technology.

That is where the role of data analysis comes into the picture. Data analysis is one modern-day technology that can help take business-driven decisions based on accumulated data and thereby enhance business profitability and productivity. It delves deeply into the fact and figures to extract meaningful information that can assist in taking intelligent decisions.

Let us understand in detail, what is data analysis and how is it turning beneficial for the eCommerce industry. The article also lists the best practices for data analysis and different types of analysis that can be performed in the eCommerce sector.

What is Data Analysis?

Data analysis is the procedure to clean, changing, process raw data, and extract actionable, relevant information that assists businesses in making informed, intelligent, and insightful decisions. The output could be in the form of a range of dashboards and reports. A dashboard displays the data in an understandable and comprehensive way so that easy data interpretation can be done.

Data analysis in the eCommerce sector refers to modern-day tools and processes that businesses leverage to collect and analyze data, with the help of key metrics. It helps organizations in staying competitive and identify hurdles in their selling methodologies. It collects data about customer habits and website performances for enhancing the online shopping experience.

Data analysis in the eCommerce industry involves certain components like:

• Metrics – a standard of measurement for reports and dashboards
• Reports – a visual representation of the past data and future data
• KPI – key performance indicator to measure degrees of success by comparing actual data to forecasted data
• Analytics – used to predict performance in the future
• Dashboards – a comprehensive look at the entire reporting scenario with drill-down facilities

Why is Data Analysis Important in the eCommerce Industry?

Here are some of the salient benefits of data analysis that are being observed in the eCommerce industry:

• Enhanced customer experience

Data analysis helps in analyzing visitors’ behavior on the website, making it simple to understand what they want and for the visitors to get what they want, with our suggestions. It also assists in upgrading the portals and websites with better features so that there is more client retention and new prospects coming up.

• Secure Online Payment

With the help of analysis tools, a safe and secure payment approach can be implemented across eCommerce portals. These tools help in detecting fraud and ensuring a secure online payment cycle. It is inevitable to have a safe payment portal since eCommerce goes hand in hand with online payments.

• Effective Sales and Marketing Campaigns

Data analysis can assist eCommerce organizations in measuring the success ratio of their sales and marketing campaigns and how beneficial they have been. It also helps in enhancing business decision-making, garnering more client attention, and creating more marketing campaigns.

• Evaluation of Trends and Patterns

With data being the center point, there are so many trends and patterns that will show up as an output. These trends and patterns can be studied and analyzed and decisions can be made based on that. It helps in ensuring that the right products are available at the apt time with ease and simplicity.

• Personalized Customer Experience

The customer is the king, knowing what the client wants is the right way to do good business and that is what analysis helps with. You can personalize your client experience with the analytical information that has been accumulated, understanding the priorities and likings of the customer.

• Thorough Inventory Management

With proper data analysis, stakeholders can predict the trend for purchasing and thereby manage and control their inventory with perfection. They can maintain enough stock to meet future demands, at the same time, not overstock themselves. They can even judge the approximate sales cycle, based on the analytical figures.

• Incorporation of Business Strategies

With the emergence of shopping strategies, enhanced business decisions can be taken. The detailed analysis of data shows the customer preferences, dislikes, patterns, etc. that can help in taking further business decisions and going in for augmented business profits. It can even guide you into the highs and lows of demand and supply, to prepare you best.

What Types of Data Analysis Are Used in the eCommerce Industry?

In the eCommerce industry, there are certain data analysis strategies that can be used for better decision-making:

• User Behaviour

Perceive user behavior once they move through the portal. Collect data of how much time is the visitor spending time on the site and other relevant information, for further analysis. Predict the likings of the customer and suggest basket items.

• User demographics

Collect and analyze information about visitors’ ages, locations, and preferences by connecting to social media. Understand which visitors can be converted into customers and enhance marketing strategies.

• Referral Information

Understand how visitors have come to learn about online retailers to optimize their marketing strategies and budget. Reports to show links through which visitors have accessed the portals.

• Conversion Rates

Finding out the rate of conversion of visitors to clients and the number of people who have been moving ahead in the sales cycle is important and a key metric in the eCommerce industry.

• Cart Analysis

Looking at the customer basket, one can evaluate the combination of products that they buy or are likely to purchase in the future. This can help in evaluating better offers, discounts, and promotions for better business.

Best Practices to Be Followed While Doing Data Analysis in eCommerce Segment

Following these tips will always assist in making the most of data analysis:

• Collect all your marketing data across various channels
• Go in for the apt tools for data analysis that suit our business
• Keep updating data with respect to seasons and trends
• Keep monitoring the eCommerce site’s shopping flow
• Establish a connection between clients and their shopping statistics
• Perceive the number of eCommerce metrics you need
• Focus on attaining the best data quality
• Garner centralized and integrated data from sources

Summing It Up

Data analysis is on a high now. There are many data analysis tools that are assisting organizations in making optimal use of their data. Some of the popular data analytics tools for eCommerce are Google Analytics, Hotjar, Mixpanel, Supermetrics, Aftership, Delighted, Woopra, Databox, Optimizely, etc.

There are certain important trends that are being observed in the eCommerce industry – customer retention through analytics, increasing adoption of predictive analytics, omnichannel and multichannel retailing, and real-time analytics through AI/ML technology. There is an interesting future to observe!

Ridgeant’s data analytics consulting helps you unlock actionable insights and evolve into a data-driven organization to optimize performance and increase growth. We offer exemplary services like data visualization services, analytics and BI modernization, BI implementation support, data mining, self-service BI and managed services.

Our flexible engagement models, tailored approach, and use of the latest tools and technologies result in efficient and secure data pipelines for analysis. Associate with us to know us better and transform your ideas into reality.