What is the right business intelligence solution for my online shop?


One of the questions we regularly get when talking to online retailers is: What is the right business intelligence solution for my online shop?

Before founding Wunderdata, we have both worked with complex enterprise business intelligence solutions, and developed business intelligence tools ourselves. We used these tools both at freshly founded online shops, and at established businesses with 100+ millions in revenue.

From our experience, we know it can be difficult for a shop owner to make sense of all the options out there, so we put together a quick guide to give you an overview of how different approaches – Enterprise, Self-Built / DIY, and cloud based software-as-a-service solutions – compare.

The right solution, ultimately, will be the one delivering the insights you need, while minimizing its weight on your critical resources. We used exactly those critical resources, in particular the ones most eCommerce businesses lack, as dimensions for the comparison:

      • Time (e.g. to setup the BI solution and to learn how to use it)
      • Financial Resources / Costs (e.g.: licensing and maintenance costs)
      • Expertise (e.g.: to setup, query databases, analyze results)

1. Enterprise solutions:

Traditional enterprise solutions are provided by companies like Microstrategy, SAP, Oracle or IBM. A typical set up involves purchasing dedicated hardware and software to run on premise.


Setup usually takes several weeks or months from design to implementation. It will involve working with IT and all other departments.


Although Enterprise BI providers offer different BI packages and keep their prices hidden, license and maintenance costs generally start from 5000€ per month.


These tools offer extremely sophisticated analysis and depth of insights. They need preparation and expertise to be used at full power, and learning curves can represent an obstacle for casual business users, often creating information bottlenecks or the need for consultants and dedicated data experts


  • Very wide applicability, nearly every analytical need can be solved with this kind of tools.
  • Best suited for companies with complex or specific analysis requirements, which go beyond eCommerce needs
  • Companies need to be ready to spend several months in implementation and employee training, and budget six digit investments.

2. Self-built solutions (SQL + Excel)

A typical DIY setup will involve having IT run SQL queries, and business users doing spreadsheet based analysis.


The setup time and effort of a self-built solution can vary greatly depending on the skill set within the company and the requirements. Usually, unless there is a full time task force dedicated to the project, implementation can take several months.


Licensing costs are low or nonexistent for DIY approaches. When considering also the indirect costs of planning and IT resources, advantages can vaporize. Performance limitations of SQL and Excel can hinder the scalability of this solution.


High expertise is required to set up this system, while most business users will be comfortable with Excel analysis. Spreadsheets are good at discrete analysis, but have to be re-done every time a new request arises. The lack of a standardized way to construct spreadsheets hinders the creation a single version of the truth. Higher expertise is needed if complex analysis is required.


  • Best suited for small companies with a low need for analytics or where growth is not an immediate priority.
  • Companies need to have high know-how in technical and analytical business intelligence and account for internal IT resources.

3. Cloud BI, SaaS solution for eCommerce.

A typical SaaS solution will provide you with your own data warehouse in the cloud where all your data sources are joined. A visualization layer is applied on your data warehouse and it is accessible via browser with a multi-tenant approach.


Setup time is short, and can vary from a few minutes (e.g. Wunderdata) to a few days for more custom implementations. The effort for IT and business users is minimized to providing database credentials.


License and maintenance costs are tailored for SMEs, and usually priced to evolve as the company grows. This provides maximum flexibility and a low overhead. From a technical standpoint, solutions often are big-data ready.


While ensuring depth of analysis through focus on specific SMEs needs, SaaS solutions aim at being user friendly for the average business user. This is done through eliminating the need for IT or database managing skills and specific efforts to offer intuitive data visualization.


  • Best suited solution for most small and medium sized online shops.
  • Cost effective and user friendly solutions compared to enterprise tools.
  • The focus of these tools limits their analysis possibilities to eCommerce needs.

4. Conclusions

Each of the three BI solutions has its pros and cons. Whether it is the sophisticated analysis capabilities and high price of Enterprise solutions, the high setup effort and analysis, but lower costs of a DIY approach, or a more balanced, less customizable yet SME-focused, cloud BI solution.

  • If your business has both economical resources and analytical skills we encourage you to think about an enterprise solution.
  • A DIY approach might be the best option if you have very limited economic resources but have IT and analytical skills, or if you have very limited data analysis requirements.
  • For all other SMEs, research has shown that conventional BI systems which are focused on large organizations, do not meet the needs of SMEs (Hwang et al., 2004; Scholz et al., 2010; B. Bergeron, 2000) so a solution optimized for eCommerce is the best choice. Research has shown that some of the critical factors for BI implementations in SMEs are:
    1. fast, easy, lightweight and low cost applications, built for flexibility and responsiveness (Salmeron & Herrero, 2005),
    2. to leverage existing staff, avoiding solutions that require new staff and/or consultants (Wixom & Watson, 2001)

Ultimately, you should keep your most precious resources in mind, and choose the solution that will minimize the impact on them:

  • Choose the solution that minimizes implementation time and effort, so you can start working data-driven quick.
  • Choose one which minimizes employee’s pre-required know-how, so that everyone in the company adopts it and actively uses it.
  • Choose one which represents the smallest overhead and is designed to scale with your business, as far as pricing and data handling capabilities.