9 Best Data Analytics Tools for Ecommerce Businesses

Online businesses have access to nearly unfathomable amounts of data, including website traffic, sales transactions, customer feedback, and more. When used properly, this data can offer major benefits. According to a 2022 Harvard Business Review survey, businesses that were considered leaders in data analytics (including the use of artificial intelligence in analytics) outperformed their peers in operational efficiency, customer satisfaction, revenue, profitability, and employee satisfaction by between 15% and 30%.

Savvy business owners can harness the full potential of the information they collect with data analytics tools, transforming datasets into actionable insights. Read on to learn more about different approaches to data analytics and the data analysis tools that can help improve your business.

What is data analytics?

Data analytics is the process of collecting, storing, and analyzing data.

Specifically, it involves cleaning (i.e., removing errors, inconsistencies, and duplications) and mining raw data to uncover trends and patterns that drive business decisions. Raw data is data that exists in its original form, not processed or improved in any way. It can be structured (following a fixed format like phone numbers) or unstructured (following no set format like social media posts).

Data analysis can help explain past performance and predict future performance, answering specific questions about your sales and marketing efforts, customer behavior, and market opportunities.

How businesses collect and analyze data

Small businesses can collect various types of data, including:

• Website visitor behavior

• Sales performance

• Customer demographics

• Inventory turnover rates

• Social media engagement metrics

• Customer feedback

Each data source provides valuable insights when properly analyzed and interpreted. Here’s one example of how an ecommerce shop might benefit from using data analytics:

Consider the owner of an online skin care store analyzing sales data stored in the business’s ecommerce platform. She discovers that 25% of customers who purchase sunscreen also purchase after-sun lotion.

Having identified this pattern, the company bundles the products, offering a discount when they are purchased together. It promotes the bundle all summer, particularly in advance of long weekends and holidays, when customers are likely to be spending time outdoors. As a result, sales of both products increase substantially compared to the previous summer.

Types of data analytics

• Descriptive analytics
• Diagnostic analytics
• Predictive analytics
• Prescriptive analytics

There are several ways to analyze data. Here are the four primary types worth knowing about:

Descriptive analytics

Descriptive analytics show you what is happening or what has happened within your business by summarizing historical data into meaningful reports and dashboards. This foundational type of analytics provides a clear picture of performance but does not explain why events occurred. Descriptive analytics works by aggregating and organizing historical data into easily digestible formats like charts, graphs, and summary statistics.

Diagnostic analytics

Diagnostic analytics dives deeper, uncovering the reasons behind an event or trend. This type of analysis examines the relationships between different variables to identify the root causes behind observed trends or anomalies. It uses data mining techniques and drill-down capabilities to explore data at granular levels of detail and identify correlations in the dataset. Diagnostic analytics often involves comparing different periods, customer and product segments, or conditions to isolate contributing factors.

Predictive analytics

Predictive analytics uses historical data and statistical analysis to forecast future trends and outcomes. This forward-looking approach enables businesses to anticipate opportunities and challenges before they arise. Predictive analytics employs machine learning algorithms and statistical models to identify patterns in historical data that can predict future behavior. These models consider multiple variables simultaneously to generate probability-based forecasts.

Prescriptive analytics

Prescriptive analytics represents the most advanced type of analysis, suggesting comprehensive strategies for building your business. It combines insights from descriptive, diagnostic, and predictive analytics to recommend specific actions that optimize business outcomes. Prescriptive analytics uses complex algorithms, simulation models, and optimization techniques to evaluate multiple scenarios and recommend a course of action. It considers constraints, objectives, and potential outcomes to provide data-driven recommendations.

Data analytics business example

Let’s take a look at how the owner of the skin care store mentioned earlier might use all four types of data analytics in her business:

• Descriptive analytics. The owner uses descriptive analytics to review her Q2 sales data, comparing it to Q1 and the previous year’s Q2 performance. The data reveals a 20% quarter-over-quarter drop in sales.

• Diagnostic analytics. To understand why sales declined, she applies diagnostic analytics and discovers the drop correlates directly with her most popular product, mineral sunscreen, being backordered for most of the quarter.

• Predictive analytics. Using predictive analytics, she analyzes historical trends showing that mineral sunscreen sales had been growing steadily at 5% per quarter before the Q2 shortage. Based on this pattern, she can forecast that sales will rebound and continue growing at that rate once inventory is restored.

• Prescriptive analytics. Finally, prescriptive analytics recommends specific actions to avoid another decline like in Q2: Maintain three months of mineral sunscreen inventory (rather than her current four-week supply), establish a backup supplier, and consider expanding her sunscreen line to reduce dependence on a single product.

Collecting the data your business needs

Before you can analyze data, you need to collect it systematically. Small businesses should focus on gathering information that directly relates to their key performance indicators and business objectives.

Start by identifying the most critical metrics for your business. An online retailer might prioritize:

• Website conversion rates

• Average order value

• Customer acquisition costs

• Customer retention rates

Meanwhile, a service-based business might focus on client satisfaction scores, project completion times, and referral rates.

Most businesses already collect significant amounts of data through their existing systems. For example, you can utilize your ecommerce platform to capture sales transactions, customer information, and product performance data. Your website analytics tool can track visitor behavior, traffic sources, and conversion paths, while your email marketing platform can provide access to open rates, click-through rates, and subscriber engagement levels.

The key is consolidating this information into formats that analytics tools can process. Many platforms offer built-in export features for API connections, allowing you to extract data into spreadsheets or databases.

9 data analytics tools

• Data mining
• Data visualization
• Business intelligence

Effective data analytics tools transform complex data sets into actionable insights. Here’s a roundup of nine analytics tools across three key categories (data mining, data visualization, and business intelligence) to help you tap into your business’s data.

Data mining

Data mining tools help businesses uncover hidden patterns and relationships within their datasets. These tools use statistical analysis and machine learning algorithms to uncover insights that aren’t immediately obvious through traditional reporting.

1. Altair RapidMiner

Altair RapidMiner is a comprehensive data science platform with drag-and-drop functionality, making advanced analytics accessible to business users. It provides extensive data preparation tools and collaborative features. The platform requires minimal programming skills.

Caption: Altair

Pricing: RapidMiner offers a limited free version for noncommercial purposes. Paid pricing is available upon request.

2. Knime

Knime Analytics Platform is an open-source alternative for data mining and analytics. It provides visual workflow design, extensive data manipulation capability, and integration with various programming languages. The platform offers excellent flexibility, connecting with any data source and file format, and doesn’t require vast programming knowledge.

Pricing: Being open source, Knime has a free version for personal use. Team plans start at $99 per month.

3. Sas Enterprise Miner

Delivering enterprise-grade mining capabilities with extensive statistical analysis and modeling tools, Sas Enterprise Miner provides automated model selection, comprehensive data preparation features, and robust performance optimization. The platform offers powerful analytical capabilities but requires technical expertise to use effectively.

Pricing: Sas pricing is customized for each company.

Data visualization

Data visualization tools transform complex data sets into charts, graphs, and interactive dashboards that make patterns and trends immediately apparent. These data analysis tools excel at presenting information in a way that facilitates quick decision-making and clear communication.

4. Shopify Analytics

Shopify Analytics provides built-in reporting and analytics specifically designed for ecommerce businesses. It offers prebuilt dashboards that show sales performance, customer behavior, and product analytics. For entrepreneurs looking to hone in on a specific trend, Shopify Analytics allows users to create customized reports from scratch and layer metrics as they drill down into the issue. The tool’s Reports page provides rich data about a specific set of metrics, with each report including a visualization that highlights your primary metrics. Additionally, Shopify’s broad library of integrations includes other data visualization tools.

Pricing: Shopify Analytics is free with a Shopify account, which starts at $29 per month (billed annually).

5. Microsoft Power BI

Microsoft Power BI is a comprehensive business intelligence tool that enables connections to a wide range of data sources, including databases, files, and online services. This tool is effective at creating a single source of truth for your business data. Power BI provides drag-and-drop dashboard creation and advanced analytics features. You can visualize any data and share those visualizations in Microsoft Teams and other workspaces, on the web, and in apps. 

Pricing: Microsoft Power BI has a free version, included with a Microsoft Fabric account. Paid plans start at $14 per user per month.

6. Tableau

Natively integrated with Salesforce, Tableau delivers data visualization with powerful analytical capabilities and an intuitive interface that enables you to combine visualizations on a single dashboard. You can use this tool to create complex, interactive visualizations using diverse data sources. While it can be used without coding abilities, the learning curve can be steep for users who are less technically inclined.

Pricing: Plans start at $35 per user per month, billed annually.

Business intelligence

Business intelligence tools combine data from multiple sources to provide comprehensive insights into business performance. These analytics platforms typically offer dashboard creation, automated reporting, and collaborative features that support data-driven decisions across organizations.

7. Looker

Now part of Google Cloud Platform, Looker is a modern business intelligence tool with strong data modeling capabilities and collaborative features. Looker can integrate with Google Analytics’ data collection and data analysis tools to provide elevated visualization and reporting capabilities. It offers SQL-based data exploration, embedded analytics options, and real-time data processing. Looker has strong data governance and sharing capabilities, but requires SQL knowledge for advanced usage.

Pricing: Contact the Looker sales team for plan pricing.

8. Qlik Cloud Analytics

The successor to QlikView, Qlik Cloud Analytics delivers associative analytics that allow users to explore data relationships in a cloud-based environment. It offers robust data compression, efficient query performance, and intuitive visualization options. The platform handles large datasets effectively, although its user interface requires some specialized training to use effectively.

Pricing: Qlik licensing costs vary based on deployment options and the number of users; contact the provider for details.

9. Google Analytics

While Google Analytics isn’t a full business intelligence platform, it remains one of the leading and most widely used web analytics platforms, offering detailed insights into website performance, user behavior, and conversion tracking. It integrates with other Google services and provides extensive customization options. While Google Analytics excels at web-based analysis, it has limitations when analyzing offline business data or integrating with non-Google platforms.

Pricing: The standard version of Google Analytics is free.