In the dynamic and competitive world of e-commerce, where data-driven decisions are becoming the standard, choosing the right analytical tools is crucial for success. Intuition, although valuable, is not enough to understand complex customer behaviors, optimize marketing activities, or effectively manage inventory. Online stores face many challenges: data is scattered across numerous systems — from the store platform, through web analytics tools, to advertising systems and social media. Their integration and interpretation can be complicated, and there is often a lack of time or specialized resources for advanced analytics.
There are many solutions available on the market, but two of them often appear in the context of data analysis: Dataorganizer.io, our specialized tool created with e-commerce in mind, and Looker Studio (formerly Google Data Studio), a popular and versatile Business Intelligence tool from Google. Which one will better meet the needs of your e-commerce business? This article, prepared by the Dataorganizer.io team, will guide you through a detailed comparison to help you make an informed decision.
The growing complexity of the e-commerce ecosystem, with multiple sales and marketing channels, forces companies not only to collect data but, above all, to synthesize it effectively. Data fragmentation, described as “data scattered across dozens of tools” and “dozens of hours spent on updates,” leads to an incomplete picture of the customer and the effectiveness of activities. As a result, companies that cannot integrate their data may lose competitive advantage to those that have coherent insight and can respond more quickly to market changes. At the same time, we observe the democratization of analytics — tools are also becoming available to smaller players, which changes the competitive landscape. Dataorganizer.io positions itself as a tool for “everyone, regardless of store size,” aiming to “democratize and accelerate analytical services.” Similarly, the free version of Looker Studio lowers the entry threshold. Thanks to this, smaller e-commerce stores gain the ability to compete at the data analysis level with larger players, which can lead to greater innovation in e-commerce strategies, as more companies have access to the information needed to experiment and optimize.
Dataorganizer.io: Analytics tailored to your online store
Dataorganizer.io is our analytical platform designed from the ground up with the specific needs of the e-commerce industry in mind. Its creators, being practitioners in this field, set themselves the goal of solving real problems that online stores face on a daily basis — primarily the dispersion of data and the time-consuming process of analyzing it. The philosophy of Dataorganizer.io is based on making analytics simple, fast, and accessible to every store, regardless of its size or analytical resources. The key element here is the automation of basic analytical tasks, which allows users to focus on drawing conclusions and taking actions, rather than tedious data preparation.
Key features of Dataorganizer.io for e-commerce
The platform offers a number of features directly addressing the challenges of online stores:
- Automatic integrations with platforms and advertising systems: Dataorganizer.io prides itself on “One-Click Integration” capability and quick configuration, which according to declarations takes less than one day. The tool integrates with key e-commerce store platforms such as WooCommerce, Magento 2, Shopify, IdoSell, Shoper, PrestaShop, as well as with the popular marketplace Allegro. Additionally, it provides connections with analytical and advertising systems, including Google Analytics, Google Ads, Meta Ads, Criteo, and Tradetracker. Importantly, these are “no-code” integrations, which means they do not require programming skills to set them up.
- Ready-made analytical dashboards (“Cards”): One of the main advantages of Dataorganizer.io is the availability of ready-to-use analytical dashboards, called “Cards,” which become active immediately after connecting data sources. The platform offers 10 such predefined cards, covering key areas of e-commerce operations, including: “Summary” (general KPI overview), “Sales and Costs” (financial analysis), “Attribution” (conversion paths), “Products” (assortment analysis), or “Customers” (behaviors and segmentation).
- Specific e-commerce analyses “out-of-the-box”: Dataorganizer.io provides specific, predefined metrics and analyses that are essential for effective online store management. These include price elasticity analysis, average price trend, promotion history, product view rate, sales and category rankings, category interest trends, add-to-cart ratios, daily COS (Cost of Sales) indicator, ROAS (Return on Ad Spend) for individual platforms, conversion funnel analysis, sales attribution, or popularity of various product variants (e.g., sizes, colors). The availability of these analyses “out of the box” significantly accelerates the process of obtaining valuable insights.
- “Data Fusion” — combining data from multiple sources: The platform intelligently combines and presents metrics from different systems in a coherent and transparent manner. This is not just data aggregation, but their contextualization, which allows for a comprehensive picture of operations and understanding the interdependencies between different aspects of the business.
- “DataChat AI” — conversational analytics in practice: An innovative feature is DataChat AI, which enables interaction with data using natural language. The user downloads a JSON file with data prepared by the system, uploads it to their favorite chatbot tool (e.g., ChatGPT), and can ask questions about, for example, marketing campaign results, sales effectiveness of products and categories, key KPI indicators, or sales trends. This feature can also support the automation of report and analysis creation.
Dataorganizer.io does not so much sell a tool as built-in expert knowledge in the field of e-commerce analytics. Ready-made dashboards and predefined analyses reflect best practices and indicate key indicators that a store owner should monitor. The user does not have to define what and how to measure on their own — they receive it in the package. This is a huge time saver and minimizes the risk of errors in defining metrics, which makes Dataorganizer.io a kind of “virtual e-commerce analyst,” especially valuable for companies that do not have their own specialists.
Moreover, the “DataChat AI” feature has the potential to fundamentally change the way small and medium-sized e-commerce enterprises interact with data. The ability to ask questions in natural language eliminates the need to know SQL or operate complicated BI tool interfaces in order to get quick answers to specific business questions. This, in turn, can lead to more dynamic decision-making, faster hypothesis testing, and greater operational agility, as the “bottleneck” in the form of an analyst or complicated report is removed.
Pricing model
The pricing model of Dataorganizer.io is transparent and based on subscription, where fees are charged for the number of active connections to data sources. The cost of a single connection decreases as their number increases — for example, the first four connections cost 24 EUR each per month. The platform emphasizes no hidden fees and the availability of all functionalities within the subscription price. For new users, there is a 14-day free trial period.
Although the pricing model based on the number of connections is simple and understandable, it may not be optimal for every business structure. Companies with many small markets, separate stores, or numerous advertising accounts may relatively quickly reach a higher cost threshold, even if the total volume of processed data is not very large. Therefore, the value of Dataorganizer.io should be assessed not only through the prism of the number of connections but primarily the depth and degree of automation of analyses it offers for each of these connections. For some, this cost will be fully justified by time savings and the value of ready-made, specialized analyses; for others, with a more dispersed but less analytically intensive structure, it may prove less beneficial.
Who is Dataorganizer.io for?
Dataorganizer.io seems to be an ideal solution for e-commerce stores that do not have dedicated data analysts or extensive IT teams. It is a tool for those who need to quickly obtain valuable insights without having to go through complicated configuration and programming. Companies that want to automate basic analytical tasks in order to focus on strategic actions and business development will also find Dataorganizer.io a valuable partner.
Looker Studio (formerly Google Data Studio): Versatility and flexibility in data visualization
Looker Studio, previously known as Google Data Studio, is a popular tool from Google that enables creating interactive dashboards and reports. Its main advantage is versatility — it offers the possibility to connect to hundreds of different data sources thanks to an extensive library of connectors (over 800, including over 600 from partners). The user interface based on the “drag and drop” method is generally considered intuitive, which facilitates creating custom visualizations and reports tailored to individual needs.
Creating e-commerce dashboards in Looker Studio
Looker Studio, despite being a general-purpose tool, can be successfully used for e-commerce data analysis. However, this requires from the user greater involvement in configuration and customization, which often means the need to have specialized knowledge or additional resources that smaller e-commerce stores may not have.
- Connecting to various data sources: Users can connect to popular e-commerce data sources such as Google Analytics (including GA4), Google Ads, Google Sheets, as well as, through appropriate connectors or GA4 events, with data coming directly from store platforms (e.g., Shopify). There is also the possibility of blending (combining) data from different sources in one report, which allows for creating more comprehensive analyses.
- Sample metrics and visualizations for e-commerce: In Looker Studio, you can create various visualizations of key performance indicators (KPIs) for e-commerce. It is popular to use scorecards to present such metrics as number of sessions, transactions, average order value (AOV), e-commerce conversion rate, or total revenue. You can also build time series charts (e.g., to track sales trends or number of sessions over time), bar charts (e.g., to compare sales by device categories or marketing channels), geographic maps (e.g., to visualize transactions by regions), and tables (e.g., for detailed analysis of traffic sources, new user behaviors, and revenue generated by them). Looker Studio also offers ready-made templates, including those dedicated to e-commerce, which can speed up the process of creating the first reports.
- Customization capabilities and flexibility: One of the strengths of Looker Studio is its great flexibility in terms of customizing the appearance and layout of reports. Users have full control over choosing themes, fonts, colors, and placement of individual elements on the dashboard. It is possible to add interactive filters, date range controls, which allows report users to explore data on their own. Ready-made reports can also be embedded on websites or in intranets, which facilitates sharing information within the organization.
The main strength of Looker Studio is its versatility and deep integration with the Google ecosystem, which makes it a natural choice for companies already intensively using tools such as Google Analytics, Google Ads, or Google Sheets. However, this universality means that Looker Studio is not “out of the box” optimized for the specific needs of e-commerce. For an online store owner, this means the necessity to independently build business logic and appropriate visualizations, which is time-consuming and can distract from key business activities. In this context, the “free” nature of Looker Studio may prove illusory if one considers the cost of employee time or external consultants needed to create and maintain useful, e-commerce-tailored dashboards. In Dataorganizer.io, these costs are included in the transparent subscription, offering ready-made solutions from day one.
Looker Studio, being primarily a visualization tool, shifts the responsibility for quality, consistency, and data modeling to the user or source systems. If the input data is of poor quality, incomplete, or inconsistent, Looker Studio will only reflect these problems in visualizations. Although it offers some basic data transformation capabilities, it does not have advanced, built-in ETL (Extract, Transform, Load) mechanisms at the level that more specialized data platforms might offer. For the e-commerce industry, where data often comes from many different systems (store platform, advertising systems, CRM, marketing automation tools), ensuring consistency and accuracy of data before loading it into Looker Studio is absolutely crucial and may require the implementation of additional tools or processes. This problem is partially addressed by the more advanced, paid Looker tool (not to be confused with Looker Studio), which has a dedicated LookML data modeling layer.
Availability (free and Pro versions)
Looker Studio is available for free for both report creators and viewers. There is also a paid version, Looker Studio Pro, which offers additional features aimed at larger organizations and enterprises, such as advanced team content management, integration with Google Cloud Project, and dedicated technical support from Google. The sample cost of Looker Studio Pro is $9 USD monthly per user per project.
Potential challenges for e-commerce
Despite many advantages, using Looker Studio in the e-commerce context may involve certain challenges:
- Need for independent configuration of advanced analyses: Unlike specialized tools such as Dataorganizer.io, Looker Studio does not offer ready-made, advanced analyses specific to e-commerce (e.g., price elasticity, advanced attribution). The user must design and configure them independently.
- Complicated data blending and performance: Combining data from many different sources (so-called data blending) can be complicated and time-consuming. Moreover, data processing often takes place in the Looker Studio tool itself, which with large and complex data sets can lead to performance problems and slow loading of reports. Some point to the lack of native “data blending” as a significant limitation.
- Required technical/analytical skills: To fully utilize the potential of Looker Studio and create truly valuable, advanced e-commerce reports, appropriate technical skills (e.g., understanding data structures, APIs) and analytical skills (ability to define metrics, interpret results) are often needed. For many e-commerce store owners, this is a barrier that cannot be overcome without additional support.
- Quality and cost of third-party connectors: Although Looker Studio offers an impressive number of connectors, the depth and quality of integration with specific e-commerce platforms (beyond standard connections with Google Analytics) can vary. Many connectors to popular e-commerce systems are provided by third parties, which may involve additional fees, functional limitations, or varying levels of technical support. The user must carefully research the available connectors for their key systems and assess whether they meet their needs.
Dataorganizer.io vs. Looker Studio: direct comparison for E-commerce
To facilitate the choice of the appropriate tool, below is a tabular comparison of Dataorganizer.io and Looker Studio in terms of key aspects relevant to e-commerce business.
| Feature | Dataorganizer.io | Looker Studio |
|---|---|---|
| Main purpose/Specialization | E-commerce specialization, providing ready-made analytical solutions | General Business Intelligence tool, data visualization from various sources |
| Ease of configuration for e-commerce | Low (Plug & Play), quick implementation below 1 day | Medium to high, requires independent configuration of dashboards and e-commerce metrics |
| Ready-made e-commerce analyses and reports | Yes, many predefined dashboards (“Cards”) and analyses | Limited; templates available, but most analyses require independent building |
| Integrations with e-commerce platforms (e.g., Magento, Shopify, WooCommerce, Allegro) | Native, deep “no-code” integrations | Dependent on availability and quality of connectors (Google’s own or third-party), variable depth |
| Integrations with advertising systems (Google Ads, Meta Ads) | Native, optimized for ROAS/COS analysis | Standard Google connectors, possibility to connect with Meta Ads through partner connectors |
| Depth of product data analysis (e.g., price elasticity, promotion analysis) | Built-in, e.g., price elasticity analysis | Requires independent configuration of logic and calculations |
| Depth of customer data analysis (e.g., purchase path, segmentation) | Built-in, e.g., customer path analysis, behaviors of new vs. returning | Requires independent configuration, possibility to build advanced segments |
| Reporting automation | Yes, full reporting automation, notifications of indicator changes, support for weekly presentations of results and team summaries | Possible through scheduled email deliveries, requires configuration |
| AI support in analysis (e.g., natural language queries) | Yes, DataChat AI feature | Standard none; possible integrations with external AI tools (requires advanced configuration) |
| Data modeling | Predefined data models optimized for e-commerce | Flexible, user models the data themselves; possibility to use LookML in Looker (not Studio) |
| Required technical/analytical skills | Low, designed for non-technical users | Medium to high for advanced applications and custom configurations |
| Pricing model | Paid per active connection to data source | Free (basic version), optional paid Pro version |
| Time to obtain first valuable insights | Fast, thanks to ready-made dashboards and analyses | Dependent on configuration complexity and user skills |
| Support and community | Direct support (information on the contact page) | Large user community, extensive Google documentation, paid support for Pro version |
Dataorganizer.io’s approach to e-commerce data analysis can be described as “solution-in-a-box” — it provides ready-made, specialized solutions that aim to quickly solve specific analytical problems of online stores. Looker Studio, on the other hand, is a versatile “platform” on which the user can build their own, customized solution. This gives much greater flexibility, but at the same time requires more work, knowledge, and resources. It can be said that Dataorganizer.io focuses on what to analyze and how to do it in the specific e-commerce context, while Looker Studio provides tools for analyzing, leaving it to the user to decide what and how they want to analyze.
The choice between Dataorganizer.io and Looker Studio is often a choice between implementation speed and specialization versus long-term flexibility and universality. Dataorganizer.io promises immediate benefits, such as “100% of store sales data,” “over 20 hours saved monthly,” or “100% reporting automation.” Looker Studio, on the other hand, offers the ability to “connect to virtually any type of data” and create “fully customizable dashboards.” An e-commerce company must therefore decide whether its priority is to immediately solve typical analytical problems specific to e-commerce, or to build a platform that can evolve in any direction, even beyond standard e-commerce analytics. This decision may depend on the company’s stage of development, available resources, and the anticipated trajectory of growth and diversification of activities.
The “hidden cost” of Looker Studio for e-commerce should also be taken into account. The free license may be tempting compared to the paid Dataorganizer.io. However, as mentioned earlier, the “free” nature of Looker Studio may involve significant personnel or consulting costs, necessary to configure and maintain useful reports. Moreover, if a company chooses Looker Studio due to the lack of license fees, but is unable to effectively build the needed e-commerce analyses, it effectively loses potential benefits (e.g., from price optimization, more effective campaigns) that it could achieve faster thanks to a ready-made, specialized solution like Dataorganizer.io. This is a significant opportunity cost that should be included in the decision-making process.
Key Benefits of Dataorganizer.io for your E-commerce Business
As the creators of Dataorganizer.io, we are proud that our tool, created specifically with e-commerce in mind, offers a range of specific benefits that can significantly impact the efficiency and profitability of your online store.
- Time savings through automation and ready-made solutions: One of the most frequently emphasized advantages is the automation of processes related to collecting, combining, and presenting data. Ready-made analytical dashboards and automated reporting processes eliminate the need for hours of manual work. Thanks to our tool, users can save over 20 hours per month, which they can devote to analyzing conclusions and implementing improvements.
- Deeper understanding of the customer and their purchase path: Dedicated dashboards, such as “Attribution,” “Customers,” or “Google Analytics Data,” provide detailed information on customer behaviors, sources from which they come to the store, the effectiveness of individual channels in the conversion process, and purchasing preferences of different customer segments. This allows for better matching of offers and communication.
- Optimization of product offerings and prices: The tool provides analyses necessary to make informed decisions regarding assortment and pricing strategy. Features such as price elasticity analysis, examination of the popularity of individual products, evaluation of promotion effectiveness (available in the “Products,” “Product Prices,” “Discounts” dashboards) help maximize margins and sales.
- More effective management of marketing campaigns and budget: Thanks to the “Performance” and “Sales and Costs” dashboards, which integrate data from advertising and sales systems, it is possible to precisely track key indicators such as ROAS (Return on Ad Spend) and COS (Cost of Sales) for individual campaigns and platforms. This enables optimization of marketing expenses and allocation of the budget where it brings the best results.
- Faster and more accurate business decisions thanks to easily accessible, processed data: Dataorganizer.io not only collects data but immediately presents it in the form of useful insights. This means that decision-makers have access to processed information “here and now,” which significantly reduces the time needed for analysis and allows for faster response to changing market conditions.
- Access to advanced analytics without the need to hire specialists: At Dataorganizer.io, we believe that advanced e-commerce analytics should be accessible to everyone. Therefore, our tool “democratizes” this access. Small and medium-sized companies, which often cannot afford to hire dedicated data analysts, gain insights through Dataorganizer.io at a level previously available mainly to large players with extensive analytical teams.
Dataorganizer.io, through automation and providing ready-made analyses, can help e-commerce companies avoid the so-called “analytical paralysis.” This is a situation where a company collects huge amounts of data but does not have the appropriate tools, knowledge, or resources to transform them into specific, useful actions. As mentioned, companies often spend “dozens of hours” on manual data processing. Dataorganizer, offering ready-made dashboards and predefined analyses, directs the user’s attention to key indicators and potential areas for optimization, instead of leaving them with raw data and an empty spreadsheet or dashboard.
The benefits of implementing Dataorganizer.io can go beyond direct business decisions, positively affecting the company’s organizational culture. Easy access to understandable data and the ability to ask questions to the AI system in natural language mean that various people in the company — not only the management, but also marketing, sales, or customer service employees — can base their daily activities and new initiatives on hard data, not just intuition. In the longer term, this can lead to building a more aware, effective, and innovative organization that systematically learns and improves its processes based on the analysis of facts.
When Looker Studio may be the right choice for E-commerce?
Although Dataorganizer.io is, in our opinion, the optimal solution for most e-commerce companies, there are specific situations in which a more universal tool, such as Looker Studio, may prove to be a better or more appropriate choice.
- Need for very flexible visualization and custom reports: If standard e-commerce analyses offered by specialized tools are not enough, and the company needs to create unique, very specific visualizations, combine data in an unusual way, or present them in a form that goes beyond predefined templates, Looker Studio with its flexibility can be a good solution.
- Integration with a wide range of atypical data sources: In a situation where key business data for e-commerce is in systems with which Dataorganizer.io (or another specialized tool) does not integrate, and Looker Studio offers an appropriate connector (own or partner), it becomes a natural choice for consolidating and visualizing this data.
- Limited budget (using the free version for basic analyses): For startups, very small online stores, or companies just starting their journey with data analytics, the free version of Looker Studio can be an initial starting point. It enables connecting basic sources, such as Google Analytics, and creating the first, simple reports without incurring license costs. However, it should be remembered that as analytical needs grow, the free tool will quickly show its limitations, and the cost of customizing it may exceed the benefits of a dedicated solution like Dataorganizer.io.
- Having team members with data configuration and modeling skills: If the company has its own data analysts or technical people who have the skills and time to independently design, build, and maintain advanced e-commerce dashboards in Looker Studio, and is ready to devote their time to building an analytical system from scratch instead of using ready-made, specialized solutions, then the flexibility of this tool can be fully utilized. An example would be a Looker Studio specialist.
Looker Studio, thanks to its flexibility, can be a better tool for “data exploration” and discovering non-obvious patterns for people with an analytical bent. It allows for creating any visualizations and testing various hypotheses, which for an analyst constitutes a kind of “sandbox” for discovering new dependencies. On the other hand, Dataorganizer.io, with ready-made dashboards, is more oriented towards providing ready answers to predefined, key business questions in e-commerce, focusing on monitoring and optimizing known metrics. These are two different philosophies of using the tool.
The decision to choose Looker Studio may also be dictated by the company’s long-term strategy, which assumes building a central data repository, e.g., a data warehouse in Google BigQuery. In such a scenario, Looker Studio becomes a natural, flexible front-end for visualizing data from various areas of the company’s operations, not just e-commerce. If the company is planning to invest in a data warehouse to consolidate all company data (sales, marketing, finance, operations), Looker Studio appears as a logical tool for reporting from this warehouse. Even if it is initially used only for e-commerce data analysis, its potential is much broader, which can be an important argument for companies with ambitions to scale and diversify their analytical activities.
Summary: How to Choose an Analytical Tool That Will Strengthen Your E-commerce?
The choice between Dataorganizer.io and Looker Studio is a choice between a ready-made, specialized solution created by e-commerce experts for e-commerce, and a universal platform requiring independent configuration.
Dataorganizer.io stands out as a specialized tool for e-commerce, offering automation, fast implementation, and ready insights. Its main advantage is ease of use for non-technical people and providing predefined analyses key for online stores. It is a solution that aims to quickly deliver value and relieve users from manual work related to data preparation.
Looker Studio is, on the other hand, a versatile and flexible tool, whose basic version is free. It offers broad integration possibilities with various data sources and allows for creating fully custom visualizations. However, to effectively use it in e-commerce, it requires more configuration, and often also analytical or technical skills.
As the creators of Dataorganizer.io, we are convinced that our tool offers the best value-to-price ratio for online stores that want to make data-driven decisions but do not necessarily have extensive analytical departments.
The final choice of tool should be dictated not only by current needs but also by the vision of analytics development in the company and the willingness to invest — whether time or money — in its construction. Does the company want to “buy” a ready-made, specialized analytical solution for e-commerce, which is Dataorganizer.io, or “build” its own, more universal but requiring more resources, as in the case of Looker Studio? The answer to this question depends on the appetite for risk, available competencies, and how central a role analytics is to play in the company’s future.
Recommendations:
- For small and medium-sized e-commerce stores, especially those that do not have dedicated data analysts, and are looking for a quick return on investment in analytics and ready, easy-to-implement solutions: Dataorganizer.io is definitely the best choice. Our tool has been designed to solve your problems from day one, without unnecessary complexity.
- For companies with technical and analytical resources that need very custom analyses, want to integrate e-commerce data with many other, atypical systems in a maximally flexible way, or plan to build a central data warehouse: Looker Studio may prove to be a better choice, offering greater freedom and control over the analytical process.
- For startups and microbusinesses with a very limited budget, which are just starting their journey with analytics and want to analyze basic data (e.g., from Google Analytics): The free version of Looker Studio can be a good and economical starting point, bearing in mind, however, its limitations and potential hidden costs as needs grow.
It is also worth considering the possibility of synergy or a phased approach. A company can start with Looker Studio for basic needs, and as it grows and needs more advanced, specific e-commerce analyses, consider Dataorganizer.io. The opposite approach is also possible — starting with Dataorganizer.io for a quick start and obtaining immediate benefits in key e-commerce areas, and later supplementing it with Looker Studio for custom visualizations or integration with systems that Dataorganizer.io does not support. Such a hybrid model, although it requires managing two tools, may offer the best features of both worlds for some, more analytically mature organizations.
We encourage you to carefully analyze the needs of your e-commerce business and, most importantly, to test Dataorganizer.io. We offer a 14-day free trial period, which is an excellent opportunity to find out for yourself how our tool can revolutionize analytics in your store. Remember that an appropriately selected analytical tool is not an expense, but an investment in the development of your online store, and we at Dataorganizer.io are here to help you with this.