Data visualization has advanced enormously over the past few years, with tools processing vast amounts of information at faster speeds to turn complex data into graphically displayed, comprehensible insights. Facts and Factors predicts that the global data visualization market size will grow roughly 10.15% each year through 2028.
The Rise (and Limitations) of Dashboards
As we advanced from the age of Excel to that of Google Analytics, dashboards quickly gained popularity. We got used to being able to scan a selection of key performance indicators (KPIs). However, while this was a big improvement over spreadsheets, understanding why or how we arrived at a certain point is way more complicated than what a dashboard could show us.
Making marketing or business decisions based solely on KPIs can be risky—especially if you have a diversified plan and you’ve taken a wide variety of actions over time. The greater the number of variables, the riskier the correlations.
Even the Best Dashboards Are No Substitute for Analysts
Dashboards can provide great information at a glance, but they do not provide actionable insights. A skilled analyst is necessary to see data in a holistic way, help draw conclusions and guide decisions. The problem? That can be time-consuming and, therefore, expensive.
Any mathematician, accountant or economist will tell you that numbers are powerful storytellers. And while trained eyes may not need to have digits plotted graphically to see patterns, cycles, correlations or trends, as data quantity increases, even they can benefit from a little technology assist.
For those of us not trained to see the meaning in data, understanding what the numbers are trying to say is likely to be even harder. Thankfully, the advancement of artificial intelligence and algorithms have helped data viz tools evolve to better support storytelling, contextualized data and decision making.
As an agency, we frequently hear stories about organizations that implemented CRM systems to collect customer data, but never really used that data for anything beyond automating email campaigns. It’s not by chance that Salesforce ended up acquiring data viz leader Tableau in 2019. After all, marketers are rarely data scientists. People need to see connections, rather than be expected to infer what’s in the data.
Today, business intelligence no longer has to rely on rule-based programs to deliver static reports. Instead, augmented analytics use AI techniques such as machine learning and natural language generation to automate data analysis, visualization, querying and insight generation. (Side note/rabbit hole—if you want to go deeper, Dataconomy has a great post explaining how this works.)
Leveraging ChatGPT to Streamline Data Viz
As the world seeks applications for ChatGPT, it’s no surprise that the AI tool is being used to create quick, custom data visualizations. Data analyst Tarik Kaoutar walks through five simple steps for creating charts to effectively communicate insights:
- Loading and mining data in a Python or R environment (“simple” is relative).
- Preparing your data, by putting it in a proper format for analysis
- Describing the data you have available (such as field names or types) to ChatGPT
- Asking ChatGPT to create the code for your visualization
- Create your visualization in Python or R
I’m not entirely sure that’s an easy ask from the average person on the street, but for anyone with some coding background, it may be a great shortcut. And, from a design perspective, the results may want to be made more attractive. But ChatGPT makes short work of creating images that communicate clearly.
The Bottom Line
There’s no doubt that the ability to analyze, contextualize and provide deeper meaning around KPIs can increase business leaders’ speed and confidence in decision making. However, not everyone has the budget to bring on professional analysts. That’s where data visualization tools play an important role.
Implementing these tools, however, can be a complex task—especially if the plan is to merge data from multiple sources, including third-party data. The process involves significant planning and security diligence to ensure that you have selected and implemented the right tools properly, so expect it to take time. If you want to stay ahead of the game, get familiar with the top trends in data and analytics and start moving now.
The FATFREE team includes experts in data acquisition and analytics, sales and marketing CRM, and teasing out the insights in your information. Make the most of what you have—reach out to FATFREE today.