Why Digital and Market Research Agencies Prefer Non-Data Science Friendly Software Solutions

As a professional tasked with optimizing Google's search engine results, I have noticed a consistent trend among digital and market research agencies regarding their choice of software. Many of these agencies, despite the availability and popularity of tools like Tableau, QlikView, or Birst, still opt for what can be considered non-data science friendly software. This choice is deeply rooted in a variety of factors, the most prominent being a significant data scientist shortage. In this article, we'll explore why many agencies find themselves using software that may not be the most efficient, user-friendly, or cost-effective.

The Complexity of Data Science Tools

Both Tableau and QlikView, as powerful as they are, come with a steep learning curve. Despite being widely recognized as user-friendly compared to many alternative tools, their complexity can be off-putting to those without a strong background in data science or advanced analytics. This complexity stems from the underlying need to perform extensive data preparation, analysis, and visualization, tasks that often require specialized knowledge.

Data Scientist Shortage

One of the most significant factors driving the preference for non-data science friendly software is the shortage of data scientists. In the real world, digital and market research agencies are often short on this critical resource. With data science roles being highly prized and often requiring advanced degrees and significant experience, many agencies opt for simpler tools that can be managed by less specialized team members.

The Impact on Productivity

The disparity between the complexity of data science tools and the availability of data scientists can have a significant impact on productivity. Agencies that must rely on these tools run the risk of being slowed down due to the need for in-depth training or the restriction to hiring more data scientists. Non-data science friendly software, on the other hand, often requires less specialized knowledge and can be developed more quickly and efficiently.

Cost Considerations

Another factor contributing to the preference for non-data science friendly software is the associated cost. While tools like Tableau and QlikView come with advanced features and are highly customizable, they also require significant upfront investment. Agencies with tight budgets may opt for simpler, less expensive solutions that do not require a specialized workforce or significant training costs.

Real-World Solutions

Instead of relying solely on data science-friendly tools, agencies are increasingly exploring other solutions. Many are turning to custom-built dashboards, simple spreadsheets, or even basic visualization tools. While these solutions may lack the advanced analytics and data manipulation capabilities of dedicated data science platforms, they offer a more accessible and cost-effective alternative.

Conclusion

The preference of digital and market research agencies for non-data science friendly software is a complex issue driven by a combination of factors including the shortage of data scientists, the need to maximize productivity, and cost considerations. While data science tools like Tableau and QlikView offer powerful functionality, they may not always be the most practical choice for agencies under budget and resource constraints. By understanding these dynamics, agencies can make more informed decisions that better suit their needs and resources.