Types of Data & Analytics in eCommerce For Growth


View more articles based on your role

Explore the crucial types of data in eCommerce – transactional, customer, website analytics, and market research – and how they drive business growth.


In the digital realm of eCommerce, data and analytics have become indispensable tools for consumer goods companies, shaping their strategies and fueling growth. Let’s explore how various types of data, including transactional data, customer data, website analytics, and market research, alongside advanced analytics techniques, drive business outcomes with tangible facts and figures.

Understanding the Types of Data

  1. Transactional Data:According to Statista, global eCommerce sales reached $4.28 trillion in 2020, highlighting the massive volume of transactional data generated daily. Manufacturers can leverage this data to identify purchase patterns, such as the most popular products, peak buying times, and average order values, to optimize pricing strategies and inventory management.
  2. Customer Data:Research by McKinsey reveals that companies utilizing customer data analytics are 23 times more likely to acquire customers and six times more likely to retain them. By harnessing customer data, companies can create personalized experiences, leading to increased customer loyalty and higher customer lifetime value.
  3. Website Analytics:A study by Smart Insights found that eCommerce websites with high conversion rates (top 25%) have an average session duration of 2 minutes and 35 seconds. Analyzing website analytics helps identify areas for improvement, such as reducing bounce rates and optimizing conversion funnels, leading to increased sales and revenue.
  4. Market Research:The global market research industry was valued at $76 billion in 2020, according to MarketResearch.com. Market research provides insights into consumer preferences, competitor strategies, and industry trends, empowering companies to make data-driven decisions and stay ahead of the competition.

Let’s do a deeper dive on each of the above points.

Transactional Data: Unlocking Insights for Enhanced Decision-Making

Transactional data forms the backbone of eCommerce operations, offering a wealth of insights into customer behavior, preferences, and market trends. Here’s an in-depth exploration of the various dimensions of transactional data and its applications:

  1. Product Details:Transactional data captures detailed information about the products purchased by customers, including SKU numbers, product names, descriptions, and attributes. Analyzing product-level data enables companies to identify top-selling products, understand demand trends, and optimize product assortments to meet customer preferences.
  2. Purchase Amounts:By tracking the purchase amounts associated with each transaction, companies can gain insights into customer spending patterns, average order values, and price sensitivity. Analyzing purchase amounts helps companies optimize pricing strategies,identify pricing thresholds, and implement dynamic pricing models to maximize revenue and profitability.
  3. Time and Location of Transactions:Transactional data includes timestamps and geographic location data, providing valuable insights into the timing and location of customer purchases. Analyzing transaction timing helps companies identify peak buying periods, seasonal trends, and promotional effectiveness, enabling them to optimize marketing campaigns and allocate resources more effectively.
  4. Payment Methods:Understanding the payment methods preferred by customers provides insights into their payment preferences and behavior. Analyzing payment method data helps companies optimize payment processing systems, enhance checkout experiences, and expand payment options to cater to diverse customer needs and preferences.
  5. Order Fulfillment Details:Transactional data also encompasses order fulfillment details, such as shipping methods, delivery times, and order status updates. Analyzing fulfillment data enables companies to optimize logistics operations, improve delivery efficiency, and enhance the post-purchase experience for customers, leading to higher satisfaction and loyalty.

Applications of Transactional Data

  1. Optimizing Pricing Strategies:Transactional data allows companies to analyze pricing elasticity and customer response to price changes. By segmenting customers based on their purchasing behavior and price sensitivity, companies can implement dynamic pricing strategies, promotional pricing, and targeted discounts to maximize revenue and profitability.
  2. Forecasting Demand:Transactional data serves as a valuable source of information for demand forecasting and inventory planning. By analyzing historical sales data and seasonal trends, companies can forecast future demand with greater accuracy, optimize inventory levels, and prevent stockouts or overstock situations, minimizing inventory holding costs and maximizing sales opportunities.
  3. Personalizing Marketing Campaigns:Transactional data provides insights into customer preferences, purchase history, and buying behavior, enabling companies to create personalized marketing campaigns and targeted promotions. By segmenting customers based on their purchase patterns and preferences, companies can deliver relevant and timely marketing messages, increase engagement, and drive conversion rates.
  4. Identifying Cross-Selling and Upselling Opportunities:Analyzing transactional data allows companies to identify cross-selling and upselling opportunities by understanding which products are frequently purchased together or upgraded by customers. By recommending complementary products or premium upgrades based on past purchase behavior, companies can increase average order values and maximize revenue per customer.

Transactional data is a valuable asset for eCommerce companies, providing insights into customer behavior, preferences, and market dynamics. By analyzing transactional data, companies can optimize pricing strategies, forecast demand, personalize marketing campaigns, and identify cross-selling and upselling opportunities, ultimately driving revenue growth and enhancing the overall customer experience. As eCommerce continues to evolve, transactional data will remain a cornerstone of success, enabling companies to make informed decisions and stay ahead of the competition in the digital marketplace.

Customer Data: The Key to Personalized Experiences and Customer Loyalty

Customer data forms the foundation of personalized marketing strategies and customer-centric approaches in eCommerce. Here’s an in-depth exploration of the various dimensions of customer data and its applications:

  1. Demographic Information:Customer data encompasses demographic details such as age, gender, income level, occupation, and geographic location. Analyzing demographic information allows companies to understand their target audience better and tailor marketing messages and product offerings to specific demographic segments. For instance, a company targeting young urban professionals may focus on trendy, tech-savvy
    products, while targeting families with children may emphasize practicality and value.
  2. Contact Details:Customer data includes contact information such as email addresses, phone numbers, and mailing addresses. Utilizing contact details enables companies to engage with customers through targeted email marketing campaigns, SMS notifications, and direct mail promotions. By staying in touch with customers, companies can nurture relationships, provide personalized support, and encourage repeat purchases.
  3. Purchase History:Tracking customers’ purchase history provides valuable insights into their buying behavior, preferences, and product interests. Analyzing purchase history allows companies to create personalized product recommendations, cross-selling opportunities, and loyalty rewards tailored to individual preferences. By understanding customers’ past purchases, companies can anticipate future needs and offer relevant products and services, enhancing customer satisfaction and loyalty.
  4. Preferences:Customer data includes information about customers’ preferences, such as product categories, brands, styles, and features. By analyzing preference data, companies can segment their audience based on common interests and preferences and deliver targeted marketing messages and product recommendations. For example, a fashion retailer may segment customers based on their style preferences (e.g., casual, formal, trendy) and tailor product recommendations and promotional offers accordingly.
  5. Interactions with the Brand:Customer data tracks interactions with the brand across various touchpoints, including website visits, social media engagement, customer service interactions, and in-store visits. Analyzing interaction data provides insights into customer engagement levels, satisfaction levels, and brand loyalty. By monitoring customer interactions, companies can identify opportunities to improve the customer experience, address customer concerns promptly, and strengthen brand loyalty.

Applications of Customer Data

  1. Creating Detailed Customer Profiles:By consolidating and analyzing customer data, companies can create detailed customer profiles that encompass demographic information, purchase history, preferences, and interaction data. Detailed customer profiles enable companies to gain a holistic understanding of their customers’ needs, behaviors, and preferences, allowing for more targeted marketing and personalized experiences.
  2. Segmenting the Audience:Customer data allows companies to segment their audience based on various criteria such as demographics, purchase behavior, and preferences. By segmenting the audience, companies can tailor marketing messages, promotions, and product offerings to specific customer segments, increasing the relevance and effectiveness of their marketing efforts.
  3. Delivering Personalized Experiences:Customer data enables companies to deliver personalized experiences tailored to individual preferences and interests. By leveraging customer data, companies can deliver targeted product recommendations, personalized promotions, and customized content that resonate with individual customers, enhancing engagement and driving conversion rates.
  4. Identifying High-Value Customers: Customer data helps companies identify high-value customers who contribute significantly to revenue and profitability. By analyzing customer lifetime value, purchase frequency, and average order value, companies can identify their most valuable customers and prioritize efforts to nurture and retain them.
  5. Nurturing Customer Loyalty:Customer data enables companies to build stronger relationships with customers and foster loyalty. By tracking customer interactions, preferences, and purchase history, companies can personalize communications, reward loyalty, and provide exceptional customer service, increasing customer satisfaction and loyalty.

In summary, customer data is a valuable asset for eCommerce companies, enabling them to create personalized experiences, drive customer loyalty, and optimize marketing strategies. By analyzing demographic information, purchase history, preferences, and interaction data, companies can create detailed customer profiles, segment their audience, and deliver personalized experiences tailored to individual preferences. As eCommerce continues to evolve, customer data will remain a critical driver of success, empowering companies to build stronger relationships with customers, foster loyalty, and drive sustainable growth in the digital marketplace.

Website Analytics: Unlocking Insights for Enhanced User Experience and Conversion Optimization

Website analytics play a pivotal role in understanding user behavior, optimizing website performance, and driving conversion rates in eCommerce. Here’s a detailed exploration of the importance and applications of website analytics:

  1. Understanding User Behavior:Website analytics provide valuable insights into how usersinteract with the website, including metrics such as page views, session duration, bounce rates, and exit pages. By analyzing user behavior, companies can gain a deeper
    understanding of how visitors navigate the website, which pages they engage with the most, and where they drop off in the conversion funnel. This understanding enables companies to identify usability issues, optimize website design, and improve the overall user experience.
  2. Optimizing Conversion Funnels:Conversion funnels represent the journey that users take from initial interaction with the website to completing a desired action, such as making a purchase or signing up for a newsletter. Website analytics allow companies to track users’ progression through the conversion funnel, identify bottlenecks or points of friction, and optimize the funnel to improve conversion rates. By analyzing conversion data, companies can identify areas for improvement, such as simplifying the checkout process, reducing form fields, or enhancing call-to-action buttons, leading to increased conversions and revenue.
  3. Reducing Bounce Rates:Bounce rate refers to the percentage of visitors who navigate away from the website after viewing only one page. High bounce rates can indicate issues such as slow page load times, irrelevant content, or poor navigation. Website analytics
    enable companies to identify pages with high bounce rates and investigate the underlying reasons for user abandonment. By addressing factors that contribute to high bounce rates, such as improving page load times, optimizing content relevance, and enhancing site navigation, companies can reduce bounce rates and keep visitors engaged for longer periods, increasing the likelihood of conversion.
  4. Improving User Engagement:Website analytics provide insights into user engagement metrics such as time on page, scroll depth, and interaction with interactive elements such as videos or forms. By analyzing user engagement data, companies can identify content that resonates with users, optimize page layouts, and enhance the overall user experience. For example, if users spend more time on pages with video content, companies can prioritize video production and placement to increase engagement and retention.
  5. Measuring Marketing Effectiveness::Website analytics allow companies to measure the effectiveness of their marketing campaigns by tracking key performance indicators such as traffic sources, referral sources, and conversion rates. By analyzing marketing attribution data, companies can identify which marketing channels drive the most traffic and conversions, allocate resources more effectively, and optimize marketing spend for maximum ROI. Additionally, website analytics enable companies to track the performance of specific campaigns, A/B test different creatives or messaging, and refine marketing strategies based on data-driven insights.

Market Research: Empowering Informed Decision-Making and Competitive Advantage

Market research plays a pivotal role in shaping business strategies, identifying growth opportunities, and gaining a competitive edge in the eCommerce landscape. Here’s a detailed exploration of the importance and applications of market research:

  1. Understanding Consumer Preferences:Market research provides valuable insights into consumer preferences, behaviors, and purchase drivers. Through surveys, focus groups, and data analysis, companies can gather information about consumer preferences for product features, pricing sensitivity, brand perception, and shopping habits. Understanding consumer preferences enables companies to tailor their product offerings, marketing strategies, and customer experiences to meet the evolving needs and preferences of their target audience.
  2. Analyzing Competitor Strategies:Market research allows companies to monitor competitor strategies, product offerings, and market positioning. By conducting competitive analysis, companies can identify competitors’ strengths and weaknesses, assess market share, and benchmark their performance against industry peers. Analyzing competitor strategies provides valuable insights into market dynamics, emerging trends, and competitive threats, enabling companies to adapt their strategies and differentiate themselves in the marketplace.
  3. Identifying Industry Trends:Market research enables companies to stay abreast of industry trends, technological advancements, and market disruptions. By monitoring market trends, consumer behavior shifts, and emerging technologies, companies can anticipate market changes, identify new growth opportunities, and proactively innovate to stay ahead of the curve. Whether it’s the rise of mobile commerce, the growing popularity of social commerce, or the emergence of new sales channels, market research helps companies navigate the evolving eCommerce landscape and capitalize on emerging trends.
  4. Informing Product Development:Market research provides valuable insights into customer needs, pain points, and unmet demands, informing product development and innovation initiatives. By soliciting customer feedback, conducting market surveys, and analyzing market trends, companies can identify opportunities for new product development, product enhancements, or product line extensions. Market research ensures that companies develop products that resonate with their target audience, address market gaps, and deliver superior value propositions compared to competitors.
  5. Supporting Strategic Decision-Making:Market research serves as a foundation for informed decision-making across various aspects of business strategy, including pricing, distribution, marketing, and expansion. By gathering market intelligence, analyzing competitive landscapes, and evaluating consumer trends, companies can make data-driven decisions that mitigate risks, capitalize on opportunities, and drive sustainable growth. Whether it’s entering new markets, launching new product lines, or repositioning existing brands, market research provides the insights needed to make strategic decisions with confidence.

Market research is a critical component of success in eCommerce, providing companies with the insights needed to understand consumer preferences, monitor competitor strategies, identify
industry trends, and inform strategic decision-making. By leveraging market research, companies can tailor their product offerings, marketing strategies, and customer experiences to meet the
evolving needs and preferences of their target audience, gaining a competitive advantage and driving sustainable growth in the dynamic eCommerce landscape. As eCommerce continues to
evolve, market research will remain an essential tool for companies seeking to stay ahead of the competition and capitalize on emerging opportunities in the digital marketplace.

Applications for Business Strategy and Operations

The eCommerce market is projected to reach $6.54 trillion by 2022, according to eMarketer. With such growth opportunities, strategic planning backed by data analytics is crucial. Companies can
use market research and customer data to identify emerging trends and adapt their strategies to meet evolving consumer demands.

  1. Inventory Management:According to the National Retail Federation, US Manufacturers lose $1.75 trillion annually due to overstock and out-of-stock inventory. By leveraging transactional data and predictive analytics, companies can optimize inventory levels, reduce stockouts, and minimize carrying costs, resulting in improved profitability.
  2. Marketing and Customer Engagement:A study by Epsilon found that 80% of consumers are more likely to make a purchase when brands offer personalized experiences. By analyzing customer data and website analytics, companies can deliver targeted marketing campaigns and personalized recommendations, driving higher conversion rates and customer satisfaction.
  3. Competitive Intelligence:Research by IDC indicates that companies leveraging competitive intelligence solutions achieve an average ROI of 171%. Through market research and competitor analysis, companies can gain insights into competitor strategies, market trends, and emerging opportunities, enabling them to stay ahead of the competition and maintain a competitive edge.


In conclusion, data and analytics are essential drivers of success in eCommerce, empowering companies to make informed decisions, optimize operations, and deliver exceptional customer experiences. With the exponential growth of eCommerce and the abundance of data available, companies that harness the power of data analytics will be well-positioned to thrive in the digital marketplace. By leveraging transactional data, customer insights, website analytics, and market research alongside advanced analytics techniques, companies can unlock new growth opportunities and stay ahead of the competition in an ever-evolving landscape.

author avatar
Alan Yong CEO / Founder
Alan Yong is a distinguished eCommerce expert with an impressive career spanning over 30 years, primarily focusing on the consumer goods sector across multiple global markets, including the two largest consumer markets, China and the United States. With a deep expertise in multi-channel eCommerce, big data & analytics, performance marketing, and consumer-based supply chain and logistics, Alan has held pivotal roles as CEO and Global General Manager for multinational consumer packaged goods companies, driving significant digital transformations and eCommerce success.