How to Conduct a Comprehensive E-Commerce Data Audit

Why e-commerce audit and continuous optimization are key

In the dynamic world of e-commerce, where competition is fierce and customer preferences change rapidly, making business decisions based solely on intuition is a direct path to failure. Success requires solid foundations — data that provides reliable information about what works, what needs improvement, and where untapped opportunities lie. Data-driven decisions not only support intuition but, above all, help control activities, optimize strategies, and maximize return on investment (ROI).

However, many e-commerce companies struggle with a fundamental challenge: data fragmentation. Key information is often scattered across a dozen different tools — the store platform, Google Analytics, advertising systems (Google Ads, Meta Ads), CRM tools, and even spreadsheets. Manual collection, combination, and analysis of this data consume dozens of valuable hours each month, generate the risk of errors, and often lead to an incomplete or even misleading picture of the business situation. This lack of a coherent view hinders effective management and inhibits growth.

In response to these challenges, DataOrganizer was created, a SaaS (Software as a Service) platform designed specifically with the needs of online stores in mind. It’s an automated solution that aims to solve the problem of scattered data and time-consuming analysis. Its primary value is the automatic combination of data from multiple key sources (such as store platforms, analytical and advertising systems) in one central location. Moreover, DataOrganizer provides ready-to-use analytical dashboards that visualize key indicators and trends, and the data is automatically updated, always ensuring fresh insight into the business condition. A significant advantage is the lack of need for complicated technical configuration — the tool is ready to use practically “from day one,” which significantly saves time and resources. This simplicity of use and elimination of the need for specialized technical knowledge make advanced analytics accessible not only to dedicated analysts but also to managers and store owners, democratizing access to data supporting development.

The purpose of this article is to present a practical guide that will show step by step how to conduct a comprehensive e-commerce audit using DataOrganizer. The ways of using this tool for ongoing monitoring and continuous optimization of online store activities will also be discussed. We will focus exclusively on features described in available materials, such as dashboards, visualizations, data export mechanisms (including export for AI analysis), and notifications, deliberately avoiding information about generating static PDF files.

Understanding the condition of your e-commerce: key audit areas

A comprehensive e-commerce audit includes analysis of many aspects of store operations. DataOrganizer, thanks to integration of data from various systems and ready-made analytical dashboards, provides information necessary to evaluate key areas:

• Sales and costs: Analysis of net revenues (realized and in progress), marketing costs from various platforms (e.g., Google Ads, Meta Ads), calculation of key profitability indicators such as ROAS (Return on Ad Spend) and COS (Cost of Sale). The “Sales and costs” dashboard is the central place for auditing financial condition.
• Traffic and user behavior: Understanding where users come from (traffic sources), how they engage with the site content (sessions, duration, bounce rate), how they interact with products (views, additions to cart), and how their path to purchase proceeds (conversion funnels). The “Google Analytics Data” dashboard provides key data in this area.
• Marketing effectiveness: Evaluation of the effectiveness of individual marketing channels and advertising campaigns (Google Ads, Meta Ads, Criteo, TradeTracker) in generating sales. Analysis of attribution paths, i.e., understanding which touchpoints with the brand contributed to conversion. The “Attribution” and “Performance” dashboards are invaluable here.
• Product analysis: Assessment of assortment performance beyond simple sales rankings. Analysis of interest indicators (ratio of views to cart additions), price elasticity (how price changes affect demand), effectiveness of promotions and discounts. The “Products”, “Product Prices”, and “Discounts” dashboards provide detailed data in this area.
• Customer analysis: Understanding behaviors and preferences of different customer segments, in particular comparing new and returning customers. Identification of the most popular products in individual groups and analysis of purchase frequency. The “Customers” dashboard allows for a deeper understanding of the customer base.
• Logistics and payments: Analysis of customer preferences regarding delivery and payment methods, assessment of the popularity of individual options and their impact on sales. The “Payments and Deliveries” dashboard helps optimize these areas.

The central element of the audit in DataOrganizer is 10 ready-made dashboards. They constitute an organized analytical structure, providing consolidated and visualized data in the key areas mentioned above. Their huge advantage is automatic updating, which guarantees access to the freshest information without the need for manual refreshing. Such a predefined dashboard structure is a significant facilitation, especially for companies starting to work with the tool, as it ensures a quick start and coverage of the most important aspects of the e-commerce business. At the same time, the division of dashboards reflects typical functions and departments in the company (marketing, sales, product management, finance, logistics), which facilitates the implementation of the tool in the organization and assignment of responsibility for monitoring and optimization of individual areas.

E-commerce audit step by step using DataOrganizer

Conducting an e-commerce audit using DataOrganizer can be divided into several logical steps, fully utilizing the platform’s capabilities.

Step 1: Connecting your data ecosystem (“One-Click Integration”)

The first and fundamental step is integrating all relevant data sources with the DataOrganizer platform. This process has been designed with maximum simplicity and speed in mind. The platform refers to it as “One-Click Integration,” emphasizing that it does not require specialized technical knowledge or coding skills (“no-code”). The entire process of connecting data, from registration to obtaining the first reports, can take less than one day.

To add a data source, the user typically selects the appropriate integration from the list, provides a name (e.g., the name of the market or account), and follows the step-by-step instructions displayed on the platform. DataOrganizer offers a wide range of ready-made integrations key for e-commerce:

• Store platforms: WooCommerce, IdoSell, Shoper, PrestaShop, Magento 2, Sky-Shop, Shopify.
• Analytics: Google Analytics (essential for analyzing traffic and behaviors).
• Advertising platforms: Google Ads, Meta Ads (covering Facebook and Instagram), Criteo.
• Affiliate networks: TradeTracker.
• Marketplace: Allegro.

After connection, DataOrganizer automatically retrieves historical data and ensures continuous, daily synchronization (24/7), thanks to which the information on the dashboards is always up-to-date. Automation of this process eliminates the need for manual exporting and importing of data, which is one of the main “time thieves” in traditional e-commerce analytics.

Step 2: Using ready-made dashboards for analysis

After connecting data sources, ready-made dashboards become the heart of the audit. Instead of reviewing each of the ten dashboards, the audit can be started from those that provide the most strategic information about the business condition:

• Summary dashboard: This is the starting point of each audit. It collects key performance indicators (KPIs) in one place: revenues, marketing costs, number of orders, granted discounts, share of new vs returning customers, marketing efficiency indicators (COS, ROAS). Comparisons with previous periods allow for instantly identifying positive and negative trends and possible anomalies requiring deeper analysis.
• Sales and costs dashboard: Essential for profitability assessment. When auditing this dashboard, attention should be paid to: sales forecasts based on historical data, return on investment (ROI) from individual marketing channels, trends in the cost of sale (COS), and dynamics of revenues and costs compared to previous months. Analysis of this data helps in conscious planning of the marketing budget and allocation of resources where they bring the best results.
• Performance dashboard Key for auditing the effectiveness of marketing activities. This dashboard allows verification of whether data reported by advertising platforms (e.g., Google Ads, Meta Ads) correlates with actual sales registered in the store system. It enables identification of campaigns that generate high costs with low sales (candidates for optimization or deactivation) and those that show great potential for scaling.
• Products dashboard: Indispensable when auditing the product offer. Analysis should not be limited to sales rankings. Available indicators should be used, such as price elasticity (which products can be raised in price, and which respond better to promotions?), sensitivity to promotions, and engagement indicators (high views with a low number of additions to the cart may signal problems with description, price, or photos). This data helps make decisions about development, optimization, or withdrawal of products from the offer.
• Google Analytics data dashboard: Used for auditing user experience (UX) and the purchase path. Analysis of the conversion funnel visualization clearly shows at which stages (e.g., from product view, through addition to cart, to order completion) most potential customers are lost. Identification of these “bottlenecks” is key for optimizing the purchase process.
• Customers dashboard: Enables auditing the customer base and understanding their behaviors. Comparing purchasing patterns of new and returning customers provides valuable information for customer acquisition and retention strategies. Identification of preferences (e.g., most popular product variants) and products that most effectively attract new users allows better tailoring of the offer and marketing communication.

Important information about DataOrganizer dashboards available in the e-commerce audit includes their scope of analysis, key questions they answer, and available metrics:

Summary dashboard enables assessment of the overall health of the business and key KPIs. It answers questions about the general condition of the store, growth or downward trends of key indicators, and significant changes compared to previous periods. Available metrics include revenues, marketing costs, number of orders, average order value (AOV), COS, ROAS, data on new and returning customers, and results by markets.

Sales and costs dashboard focuses on profitability and marketing budget planning. It helps determine which marketing channels generate the highest return on investment, what the COS trend is, and what the sales forecasts are. It contains metrics such as revenues, costs by source, revenue forecasts, ROI by channel, COS, and sales and cost dynamics compared to previous periods.

Performance dashboard analyzes marketing effectiveness and verifies platform data. It checks compliance of data from advertising platforms with actual sales, identifies inefficient campaigns, and those with potential for scaling. Available metrics are costs and results by campaign/platform, actual ROAS/COS, and comparison of platform data with store data.

Products dashboard evaluates assortment performance and supports offer and price optimization. It answers questions about best-selling products, potential for price increases, reactions to promotions, and conversion problems on product cards. It contains sales rankings, data on price elasticity, sensitivity to promotions, view and cart addition indicators, and product conversion.

Google Analytics data dashboard analyzes the customer journey, UX, and conversion optimization. It identifies places where the purchase path is abandoned, the most common user paths, tracking of key actions, and the effectiveness of the purchase process. Available metrics are traffic sources, sessions, bounce rate, conversion funnel, user paths, and events such as adding to cart or starting checkout.

Customers dashboard examines customer behaviors, supports segmentation, and loyalty analysis. It answers questions about differences in behaviors of new and returning customers, products attracting new customers, and purchasing preferences. It contains data on the number of customers (new/returning), revenues by customer type, most frequently purchased products by customer type, and data by day of the week.

Step 3: In-depth analysis using visualizations and data export

Ready-made dashboards are an excellent starting point, but the true depth of an audit often requires more detailed analysis. DataOrganizer offers tools for such deepening:

• Interpretation of visualizations: Dashboards contain numerous charts (e.g., revenue and cost trends) and interactive tables. One should learn to interpret them. Interactive tables allow for quick sorting and filtering of data by clicking on a column header, which makes it easier to find interesting segments. A key function is dynamic period comparisons (e.g., current month vs previous month, year to year), which allow assessment of the dynamics of changes.

Analysis of specific areas:

• Conversion funnels (Funnel Analysis): The “Google Analytics Data” dashboard contains a visualization of the purchase funnel, which clearly shows at which stages (e.g., from product view, through addition to cart, to order completion) most potential customers are lost. Identification of these “bottlenecks” is key for optimizing the purchase process.
• Cohort analysis (indirectly): Although the platform does not directly use the term “cohort analysis,” the “Customers” dashboard allows comparing behaviors of customers acquired at different times (implicitly, through segmentation into new and returning and analysis of their actions over time). Analysis of how customer purchasing patterns change as time passes from the first purchase provides valuable information about loyalty and customer lifetime value (CLV).
• Profitability of products/channels: By combining data from the “Sales and costs,” “Performance,” and “Products” dashboards, one can accurately assess which products generate the highest margin and which marketing channels deliver the most valuable customers at the lowest cost.
• Customer journey analysis: The “Attribution” and “Google Analytics Data” dashboards allow tracking how customers interact with various touchpoints (ads, social media, search engine, email) before making a purchase. Understanding these paths helps in optimizing marketing strategy and budget allocation.

• Data export for further analysis (JSON for AI): DataOrganizer enables downloading processed data. A particularly interesting and modern function is the ability to export prepared data in JSON format, ready for use in external tools based on artificial intelligence, such as ChatGPT. Instead of reviewing static reports, one can “converse” with the data, asking questions in natural language about campaign results, product performance, key business indicators, or sales trends. Just download the JSON file and upload it to the selected AI tool, starting, for example, with the command “check and describe the contents of the file.” This feature opens up completely new possibilities for flexible and in-depth analysis, beyond predefined dashboards, and constitutes a strategic asset of the platform in the era of the growing role of AI in business.

Step 4: Identification of problems and areas for optimization

The purpose of an audit is not only to collect data but, above all, to interpret it in order to identify specific problems and optimization opportunities. When analyzing data from DataOrganizer, one should look for warning signals and potential opportunities:

• High traffic, low conversion (Dashboards: GA Data, Performance): May indicate problems with user experience (UX) on the site, unattractive offer, too high prices, technical errors, or mismatch of traffic to the offer.
• High marketing costs, low ROAS (Dashboards: Sales and costs, Performance): Suggests inefficient advertising campaigns, poor targeting of target groups, inappropriate ad creatives, or too high competition in given channels.
• Many additions to cart, few transaction completions (Dashboards: Products, GA Data): Often indicates problems in the checkout process (too complicated, requiring registration), unexpected or too high delivery costs, lack of preferred payment methods, or technical problems in the final stages of the path.
• Declining sales dynamics of key products (Products dashboard): May be a signal of changes in market trends, growing competition, product quality problems, unattractive price, or simply the need to refresh the offer and marketing communication.
• Low customer retention (Customers dashboard): Indicates potential problems with product quality or after-sales service, lack of loyalty-building activities (e.g., loyalty programs, personalized communication), or strong competition offering better conditions.

The use of period comparisons and data segmentation (e.g., analysis of behaviors of new vs returning customers) is key to precisely locating sources of problems and understanding their scale. DataOrganizer’s structured approach, based on ready-made dashboards, significantly facilitates conducting a basic audit. However, an in-depth understanding of the causes of problems often requires synthesis of information from various dashboards and potentially the use of more advanced methods, such as analysis of data exported to AI tools.

DataOrganizer advantage: key benefits for your online store

Regular conducting of audits and using DataOrganizer for continuous monitoring brings a number of measurable benefits for an online store:

• Consolidated data in one place: End of information silos. The platform integrates data from multiple sources, giving a full, 360-degree view of the business.
• Automation and huge time savings: Significant reduction (even by 20+ hours per month) of time spent on manual collection, combination, and analysis of data. Automatic updates and ready-made visualizations replace tedious reporting. This time saving is a key value proposition for companies experiencing pain related to manual processes.
• Speed of implementation and ease of use: The ability to launch advanced analytics within one day, without the need to engage programmers or have specialized technical knowledge.
• Better business decisions: Access to reliable, current data supports making more informed and accurate strategic and operational decisions.
• Marketing optimization and ROI maximization: Precise understanding of which channels and campaigns bring the best results allows for more efficient allocation of the marketing budget and increase in return on investment.
• Compliance with regulations: The platform ensures compliance with data protection regulations, such as GDPR.

Transform data into profits with DataOrganizer

In today’s competitive e-commerce environment, ignoring data is like navigating without a map and compass. Regular, comprehensive audit and continuous monitoring of key indicators are absolutely essential to maintain competitiveness, optimize activities, and dynamically develop an online store.

DataOrganizer appears as a powerful partner in this journey. The platform not only solves the fundamental problem of scattered data and time-consuming analysis through automation and centralization, but also provides ready analytical tools in the form of clear dashboards and modern features, such as collaboration with AI. It enables e-commerce companies, regardless of their size or technical background, to make smarter decisions based on facts, which directly translates into better financial results.

If you want to stop wasting time on manual data collection and start utilizing the full potential of information dormant in your business, it’s worth considering DataOrganizer. The platform offers the opportunity to familiarize yourself with its functionalities through a 14-day free trial period or viewing a demo account. It’s an excellent opportunity to see how DataOrganizer can help transform your data into real profits.