Telling a Compelling Story with Marketing Data

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In recent months, marketers understandably have been scrambling to determine what their data is telling them based on dramatically shifting market conditions and changing consumer behavior.

Previously, data analysts could rely on months, if not years, of historical data that showed consistent patterns and gradual shifts over time.

However, 2020 has so far proven to be an anomaly, with COVID-19’s impact eliminating any chance of market predictability — even with an 18% increase in e-commerce sales so far. Forecasting is challenging, so we must rely on short-term data analysis and point-in-time trends to lead the way.

After all, we operate in an ecosystem built to attract, secure, and sell to consumers. So, analysts and marketers are wise to dig into data and extract a narrative that enables the optimization of actions. In many ways, it’s at one’s fingertips. Yet, as we evaluate data under the lens of persuasive storytelling, it is important to understand that macroeconomic trends will help to justify what we see and in the greater market context. Broader consumer trends will help us apply our conclusions and inform the nuances of our marketing approach.

The Practical Art of Data Storytelling

As we dig in, it is important to understand that data storytelling starts with defining your business question and understanding your audience. When defining your business question, ensure you can take action from the answer. For example, within affiliate programs you should consider:

  • How should I adjust marketing spend by channel in response to COVID-19?
  • What role does affiliate play in supporting overall customer acquisition?
  • What is the revenue contribution of publisher partners by the publisher category?
  • Which publisher partners are driving the highest and lowest ROAS?

The answers to these questions will drive investment decisions in specific channels and publisher partners.

Once you’ve crunched the numbers and completed your data analysis, you’re ready to share the results compellingly. It is critical to identify your audience and understand the following: Is the output of your analysis a presentation to management, a research paper to fellow data scientists, or is it a report that will be delivered to other marketers in the industry? Without knowing your audience, you will be challenged to answer the why behind the what in a way that will make sense.

Once we start to identify trends and patterns in the analysis it’s important to ask yourself these five things:

  • Is what I see in the data authentic and reflective of an ongoing trend or a one-time anomaly?
  • How can I validate my observations?
  • Is there a proxy or a benchmark that is observing the same pattern or trend?
  • Why is this trend happening?
  • How can I communicate this complex data analysis to my audience in a way that they will understand?

In addition to the data you’re using in the analysis, look for macroeconomic reports and indicators that can be woven into the story you are trying to tell with the data. You need to find sources that will add credibility and validate or disprove your working theories.

Finding the right sources is key. You can’t just pull up any random article on medium or a company blog and use it just because it reinforces that story you are trying to tell. When looking for macroeconomic data, you should look for well-known companies and researchers who have already established trust in the market.

Beyond reputation, you should make sure that they:

  • Publicly disclose their methodology
  • Clearly show the survey size
  • Detail whether or not they are using a randomized sample or are they just self-selecting a sample to tell a segmented story.

During the Coronavirus outbreak, to explain the why behind the what, I frequently turn to the following sources to extract macroeconomic trends and validate my observations:

The Delivery

Now that the analysis is completed, you can be confident in the findings and the proper macroeconomic data is woven into your storytelling, you must deliver the research to your core audience. Personally, most of my research is read by a wide range of people from my CEO to fellow data analysts and marketers. Knowing that a large portion of my audience is not data scientists, I must provide them easily digestible information clearly and concisely. You must understand the make-up of your audience and their ability to digest data.

Ultimately, the prevailing question we must ask ourselves is: are we able to tell a story that will demonstrate the why behind the what in today’s unpredictable environment? Macroeconomic trends from reputable sources will help you accomplish this by marrying their data with your findings to explain the why behind your results.


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