At Gratia, we embrace intuition, emotions, and the spark of inspiration — three essential pillars supporting creativity’s multifaceted marvel. But while we thrive on the “soft” elements, we never overlook the “hard” data, as data-driven decision-making has become indispensable in communication.

In this snack 🥒, we’ll explore three powerful types of analytics that can revolutionize how your company makes decisions, engages with its audiences, and streamlines its operations: descriptive, predictive, and prescriptive analytics.

Ready to dive in? Let’s break them down!

 

 

Descriptive analytics. Or understanding the past.

It’s the basic one: we crunch data sources to get insights objectively and clearly. We want to understand and describe what happened, answering questions such as: What happened?

* What happened (For example, the performance of a campaign or piece).

* When (e.g., if it was the correct date, if it ran alongside another, if it was the first time, if there was competition).

* Where (e.g., what platform, area, country).

* Who was involved (e.g., what campaign, piece, action)?

* How did it happen (Triggers, exponentiation, or mitigators)?

Why did it happen? Here, we seek to connect the dots and understand the root cause of what was measured.

Mathematical techniques (measures of central tendency, dispersion, graphical representations, frequency tables, comparisons, etc.) are used to answer these questions, which are well-known to those familiar with the subject.

Digression: we use “etc.” because it is a short snack, not a scientific paper!

This analytics improves the understanding of data and identifies patterns, trends, and relationships between them that might go unnoticed at first glance. It’s super helpful because it facilitates informed and strategic decision-making.

 

Predictive analytics. Or anticipating the future.

You’re planning a back-to-school campaign and need to decide if you should ramp up investment in communication, distribution, and sales force because you anticipate higher sales. But where do you get that insight? No, a crystal ball won’t cut it — you turn to data.

The core purpose of predictive analytics is to forecast future outcomes so you can make more intelligent, more proactive decisions. This involves building predictive models — complex algorithms that analyze data to uncover patterns and relationships that aren’t immediately obvious.

Predictive analytics stands out for its sophistication, leveraging advanced statistical methods, machine learning, and data mining to anticipate future trends based on historical data and current behaviors. It empowers businesses to reduce risks, seize new opportunities, personalize marketing, enhance customer experiences, and make proactive choices.

Beyond comms, here are some other typical applications: forecasting product demand, detecting fraud, predicting equipment maintenance needs, and even estimating wildfire risks. It’s everywhere, helping businesses and individuals make informed decisions in real-time.

 

Prescriptive analytics. Or making wise decisions.

Knowing what is most likely to happen and what to do about it are two different things. Therefore, this analytics recommends (prescribes) the best actionable based on future predictions and what-if scenario analysis.

In other words, it further suggests what should be done to achieve an objective.

Here, we get into oceans of data and much human lucidity. Events rarely (if ever) occur in isolation. Technology shows us correlations, but human talent has to detect the interconnections and build what-if scenarios to understand in detail what needs to be done to change future trajectories.

Just as your doctor prescribes the best medicine based on a thorough examination of your medical history and analyses, the best prescriptive actions are based on a well-understood hypothetical context.

 

The magic is in the combination.

By this point in the snack, we guess it has become clear:

* Descriptive: you understood what happened and detected patterns.

* Predictive: you anticipated what might happen.

* Prescriptive: you suggest and act with precision to achieve better results.

 

Now, you may wonder if you must use one or all three. Not all companies can reach the maximum sophistication; starting with the most basic is a significant advance.

 

But if you’re desperate to incorporate analytics for your marketing or internal communications, take it easy — CALL US!!! 🔥🔥 Just kidding: you can start calmly. To obtain descriptive insights, you have accessible tools like Google Analytics. Then, you can scale progressively, integrating predictive solutions with platforms like Tableau or Power BI. Now, turn to experts for prescriptive analytics to help you build the model.

 

Data is as valuable as vision, intuition, and creativity in communication. Analytics is not just for technical teams. And if you got a Humanities degree and thought numbers were not for you, well, it’s time to change your mentality.

Thoughts?

Thanks for reading this Gratia snack — now create something amazing!

For a deep dive into this article, visit the podcast episode.

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