3 Reasons why Google Data Studio is a step toward the democratization of analytics, but falls short on delivering data analytics to those who need it the most.
Google recently enabled unlimited reporting in their Google Data Studio. In doing so, they practically made their flagship data analytics tool free for everyone to use.
At a high level, Google Data Studio provides a comprehensive suite of analytics capabilities including:
- Integrating data from multiple data sources, including SQL databases, Google Analytics, and Google Sheets.
- Formatting and cleaning integrated datasets to prepare them for analysis.
- Producing and sharing data visualizations and dashboards based on the cleaned datasets.
Traditionally, these features have only been available in paid tools such as Chartio and Quill. Therefore, the introduction of a free Google Data Studio is a great leap forward toward universal access to data analytics.
First of all, I want to first applaud Google for this forward-thinking decision. A free data visualization and integration tool is is a critical step toward the democratization of analytics.
However, I also believe that, just like Google Analytics, making Google Data Studio free is just the first step in the process of making data analytics easy, enjoyable, and valuable for all businesses.
While Google Data Studio (GDS) provides many useful features, it falls short in helping SMBs understand and extract value from their data because:
- Although it has great data cleaning and integration capabilities, GDS does not guide an organization’s overall data strategy or help it decide what datasets to collect and analyze in the first place.
- Although its visualization and dashboarding capabilities enable rapid testing of business hypotheses to find answers to “known” business questions, GDS does not help organizations uncover surprising insights, or “the unknown unknowns”.
- Although GDS can help businesses monitor and track metrics, it doesn’t tell you how to identify and choose good metrics to track in the first place.
Let me elaborate.
GDS does not guide an organization’s overall data strategy
Data analytics is never an end in itself. It is always a means to achieve some business objective.
Therefore, before ever beginning an analytics project, you need to be crystal clear about how it can add value to your business — whether that’s growing revenue, cutting costs, or acquiring more customers.
Without a clear strategy, you will not even know what datasets to collect in your organization in the first place, nor will your analysis drive any immediate business insights for you.
Google Data Studio makes collecting and cleaning datasets in your organization easier than ever, but it doesn’t help you come up with a strategy for data collection in the first place.
However, coming up with a good data strategy and understand the immediate value of data is the biggest challenge preventing small and medium businesses to adopt analytics in their organizations.
As part of the Humanlytics customer development process, my team interviewed 70+ small and medium sized businesses (SMBs) (read more here). Out of all those businesses interviewed, the two biggest pain points we found were related to data strategy, rather than the analytics project itself:
- Adoption: “We don’t understand the business value of implementing data analytics at our company.”
- Interpretation: “We lack the talent and resources to make sense of the data we have and extract actionable insights from the data.”
Even though many companies also complained about pain points with integration, cleaning, and visualization, it is really data adoption and interpretation that are preventing SMBs from using any analytics at all in the first place.
These two challenges are not solved at all by Google Data Studio because you still need experienced analysts or consultants to assist SMBs and help them understand how to use data in their organization, and data talent is usually prohibitively expensive for those businesses.
GDS does not help organizations uncover surprising insights, or “the unknown unknowns”
During the analytics process, there are three types of questions you can ask your data:
- The “known knowns”: What are insights that we already know that we want to validate or track regularly?
- The “known unknowns”: What are the factors that we know we don’t know, which we need to investigate?
- The “unknown unknowns”: What are some hidden insights that we are not already aware of that might provide opportunities?
Whereas the ability to uncover “known knowns” and “known unknowns” are pivotal in helping companies to establish data-driven action and investigation processes, the ability to uncover unknown unknowns are considered to be the most valuable insights an analysis can provide.
This is because the ability to uncover “unknown unknowns” can provide your company with an analytical edge over your competitors and give you unique information and patterns your competitors aren’t aware of.
Google Data Studio’s visualization and dashboarding capabilities enable organizations to answer questions on the “known knowns” level (through dashboarding and active monitoring), and “known unknown” level (by providing data visualization tool). However, it falls short on being able to provide capabilities to uncover “unknown unknown” insights.
By nature, it takes both extensive data analytics experience and time to uncover the “unknown unknowns.” Not only does an analyst need to rapidly slice and dice data using multiple dimensions, they also need to have the statistical acumen to identify anomalies in their data.
Furthermore, as more dimensions are added to an analysis, the analytics labor required increase exponentially.
For example, if you want to identify bounce rate by traffic source, you might only need to do 3 analyses, but if you want to identify bounce rate by traffic source AND geographic origin, you will need 5*5 = 25 analyses, and the complexity only increases exponentially as you add more dimensions.
Gradually, it becomes humanly and economically impossible to conduct analysis that will uncover all revelant “unknown unknowns,” and Google Data Studio does not alleviate this analytics pressure enough to make it economically viable.
3. Although GDS can help businesses monitor and track metrics, it doesn’t tell you how to identify and choose good metrics to track in the first place
Google Data Studio’s interactive dashboard and data visualization features enable users to track important metrics in almost real-time and communicate these analytics results to their entire team.
This metric tracking and monitoring feature is very important for many businesses because it can offer them real time feedback on their business actions, and enable rapid iteration and adjustment of their strategies.
However, while tracking metrics is important, many SMBs we interviewed struggle to come up with those metrics in the first place.
This is because coming up with good metrics is very difficult, requiring both intensive industry experience and good analytics acumen.
Typically, good metrics need to be comparable, understandable, relevant, and actionable. They also need to be granular enough to capture real information, and concise enough to avoid paralysis by analysis (I talked more about choose good metrics in this article here).
On top of these criteria, businesses also need to avoid “metric traps” such as “vanity metrics” (those that do not have context), and “false metrics” (those that do not reflect business objectives) during their metrics selection process.
Furthermore, because it is only recommended for a business to track around 10 metrics at one time, even one faulty metric can harm the decision-making processes of a company greatly. This in turn can erode trust in a culture of data-driven decision-making.
For SMBs without experienced analytical talent, it is usually extremely difficult to select good metrics for Google Data Studio to track in the first place. Therefore, in this area the GDS tool falls short again in helping these companies adopt analytics.
In this article, we examined few important business questions Google Analytics CANNOT help businesses accomplish.
However, the purpose of this article is by no means to criticize Google Data Studio, but rather to point out the fact that it should not be treated as a “cure-all” for all analytics problems in businesses.
In my view, instead of making analytics easier for SMBs, Google Data Studio is making data analytics and visualization easier for marketing analysts and analytics agencies.
In fact, the only time we talked to interviewees who were very interested in Google Data Studio are consultants who loved how easy it is to communicate their findings to their clients.
The problem here is that it is usually the large enterprises are served well by data consultants — that’s why they keep coming back to them with large contracts. But let’s not forget about SMBs, which comprise 55% of our nation’s jobs and make up the backbone of our economy. They often don’t have the money or resources to hire a team of data scientists or consultants.
Until SMBs can understand the actionable business insights that they can extract from data by tracking known knowns, testing known unknowns, and discovering unknown unknowns, we still have a long way to go…
At Humanlytics, we hope to build a tool for SMBs that not only helps them answer their business questions and track metrics in real time, but also tell them what questions they should be asking and teach them how to implement solutions.
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