Data Visualization: 5 Key Lessons from

Contents:

• Why is data visualization automation necessary?
• Important nuances of working with stakeholders
• Problems with agencies: how to avoid common mistakes
• Problems with APIs: don't trust service promises

Data visualization is becoming a key tool for analysts, allowing them to effectively present complex sets of information. Mentioning the term "dashboard" in meetings with colleagues immediately generates interest and attention, emphasizing the relevance and significance of this topic in modern business. Dashboards not only help with quick data analysis but also with informed decision-making, making them indispensable in the analytics process. Understanding how to use visualization correctly to achieve maximum impact and improve productivity is essential.

Why is automated data visualization necessary?

Modern analytics services offer a wide range of information, which can make it difficult to understand. Many experts in this field note that the complexity of data analysis increases with its volume. Effective use of analytics requires the ability to filter and interpret large amounts of data, which is crucial for making informed decisions.

Key performance indicators (KPIs) to track may include the following:

• Google Analytics data;
• Data from four social media platforms, where we combine organic traffic and paid advertising;
• Website user survey results;
• Website availability, reliability, and SEO performance monitoring data;
• Email newsletter statistics.

This list is not exhaustive, but we're starting with the basics. Each tool offers a unique way to present data, and manually collecting information, especially from social media, can be a significant challenge. We suggest focusing on effective methods and tools that can help simplify the process of data collection and analysis, making it more convenient and less time-consuming.

Different stakeholder groups have unique needs for key performance indicators (KPIs). They expect to receive up-to-date data as quickly as possible, preferably for the previous day rather than a whole week. This often leads to analysts constantly creating charts in Excel or developing separate dashboards on platforms such as Tableau. As a result, analysts often spend significant time preparing reports for colleagues, which can reduce the overall effectiveness of decision-making processes. Streamlining these processes and implementing automated reporting systems can significantly improve the accessibility and speed of data delivery for all stakeholders.

Analyzing results and planning future improvements becomes extremely difficult. In extreme cases, this can be done by someone else, but this approach does not always guarantee achieving the desired results. Effective analysis requires a deep understanding of the situation and active participation of the team, which ultimately contributes to a more precise definition of steps to optimize processes and achieve the set goals.

In this case, we interacted with several stakeholder groups.

• Senior management, who need data at a strategic level;
• Communications department management, interested in the big picture;
• Business unit managers, interested in the results of their products;
• Local managers, who want to see the big picture, monitor the situation in other countries and, of course, stay abreast of developments in their market.

Creating at least 61 dashboards causes significant stress for analysts. In such conditions, automation of dashboard generation processes becomes an obvious and necessary solution. Automation not only reduces stress but also significantly increases the efficiency of analysts by improving the quality and speed of data collection. Implementing automated dashboards allows you to focus on analyzing and interpreting information, rather than the routine work of creating them.

Important nuances of working with stakeholders

The data visualization project began with identifying key metrics. We developed a one-page measurement plan that details which metrics will be tracked, where the data comes from, and why analyzing it is critical. This approach ensures the accuracy and relevance of analysis, which in turn contributes to more informed business decisions. Data visualization becomes an effective tool for monitoring and evaluating metrics, which helps identify trends and improve overall performance.

The greater the number of stakeholder groups, the more diverse measurement plans need to be developed. Combining all the data into a single table is impractical, as redundant information can cause confusion among users. For effective analysis and decision-making, it's important to structure data so that each group can easily navigate the information. Proper data organization facilitates a more accurate understanding of results and improves collaboration among stakeholders.

To effectively develop a measurement plan, we met with various stakeholder groups. Each group has unique needs and expectations regarding data visualization. By considering these aspects, we can create a more holistic and tailored approach to analyzing and presenting information.

Collaboration with marketers proved particularly effective. They are already accustomed to working with data and view dashboards as an important tool for optimizing business processes. They have clearly defined key performance indicators (KPIs), allowing them to focus on achieving their goals.

Department managers are interested in how data visualization can help evaluate the performance of their teams. However, such requests are often too general. This leads analysts to delve into details that don't always correspond to the specifics of the area of ​​interest. It's important to make requests clearer so analysts can provide more relevant and useful data for analyzing team performance.

One of the key aspects I noted during the interview was the importance of achieving high precision in responses. This is especially relevant when interacting with managers of large projects, who often don't have time for detailed explanations. Maximum precision in communication helps avoid misunderstandings and promotes effective collaboration, which is especially important in a rapidly changing business environment.

One of the managers at a local market was interested in the number of visitors who came to the main website through their local resource. Creating such a report turned out to be simple, but it soon became clear that he was referring to data on visitors coming through local advertising campaigns. These are two completely different metrics that require separate analysis. A proper understanding of traffic sources allows you to more accurately evaluate the effectiveness of advertising investments and adjust your promotion strategy.

It is important to remember that you should not unconditionally trust the opinions of stakeholders. It is recommended to always clarify metrics with specialists who are directly involved in attracting traffic and interacting with clients. This will help you obtain more accurate data and form informed decisions to improve the effectiveness of your marketing strategies.

Problems with Agencies: How to Avoid Common Mistakes

While developing a reporting automation project, we encountered a number of challenges. At the initial stage, we did not have a clear idea of ​​the scope of the project, but stakeholder requirements obliged us to provide comprehensive reports on all data sources on a monthly basis. Ultimately, we decided to implement a "quick fix" and contacted an agency to create a report template in .ppt format integrated with Excel. This allowed us to streamline the reporting process and improve data visualization, which in turn contributed to more effective decision-making based on the information provided.

The choice of an agency with which we had established a positive working relationship turned out to be unsuccessful. The managers assured us of their ability to cope with the task, but the reality differed significantly from expectations. The initial step of creating a link between the presentation and Excel proved impractical, as effective data visualization tools such as Google Data Studio and Power BI are already available on the market. These solutions offer a higher level of functionality and ease of use, allowing us to focus on strategic tasks rather than technical aspects.

We agreed to the proposed solution, which, in turn, led to a lengthy project deadline. Dashboard design requires a unique approach, different from website design or infographics. As a result, we spent two months developing a template that, while useful later, could have been implemented more efficiently and quickly. Streamlining the dashboard development process will help reduce time and resources, which is essential for achieving successful results in the future.

After completing our collaboration with the agency, we began searching for qualified contractors, paying particular attention to their experience in visualizing data from our sources. As a result, we launched a new project with a Danish agency, forming a team consisting of a project manager, a data scientist, a programmer, and dashboard experts. This collaboration is aimed at creating effective solutions for analyzing and presenting data, which will improve decision-making and increase business efficiency.

The project's optimistic deadlines traditionally presented a challenge for us. I had already budgeted for an additional month, given the complexity of creating 61 dashboards. As a result, we successfully completed the work on time.

Quality assurance proved to be a key stage of the project. In projects like this, it is crucial not only to extract data correctly but also to ensure that the final dashboards meet the established specifications. Errors can easily be missed, especially when multiple data sources are used on the same slide, such as different views from Google Analytics. Thorough data validation and verification ensure the high quality of the final reports and dashboards, which in turn facilitates informed decision-making based on analysis.

This step requires a meticulous and thorough specialist who can thoroughly check all the details. Unfortunately, the agency didn't have the right people, so I had to take on this responsibility myself and bring in colleagues for additional support. This ensures high-quality work and minimizes the likelihood of errors.

API Issues: Don't Trust Service Promises

Creating a dashboard in Google Data Studio using data from Google Analytics may seem like a simple process. However, when integrating data from social media, users often encounter serious API-related issues. These complexities can hinder the retrieval and display of the required metrics and indicators. For successful data integration, it's important to understand the specifics of working with social platform APIs and their limitations. Streamlining your data retrieval process will help you create a more informative and functional dashboard, which in turn will improve your analysis of marketing campaign effectiveness and audience engagement.

Numerous services, including Falcon.io, offer access to their APIs, but the cost of these services can often be quite high. If you haven't budgeted for these costs, it can create an unexpected financial burden for your team. Be sure to factor API costs into your budget to avoid unpleasant situations and ensure the efficient operation of your project.

Gaining access to an API doesn't always guarantee receiving the necessary data. In our experience, we were able to convince a web survey service manager to provide free API access, but this didn't solve our problem. Such cases highlight the importance of not only API access but also the quality and availability of the data it provides.

After gaining access and setting up the connector, we encountered an unpleasant situation. It turned out that the API doesn't provide the necessary data export by user group, offering only a general set of information. For deeper analysis, we needed specialized software, which, in turn, required additional financial investments. This API limitation significantly complicated the data management process and increased our costs.

Our budget is limited and our timeline is tight. Therefore, before deciding to work with the API, it's important to carefully consider your costs and capabilities. We recommend using additional resources, such as the official Google Data Studio documentation, to gain a deeper understanding of the API and avoid potential issues. Proper planning and understanding of available tools will help optimize the process and reduce costs.