Maximize Your Marketing Data by Asking Great Questions

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In a previous post, I introduced the three types of analytics and shared that the first step of starting an analytics project is to ask yourself: What is the objective, intention, or question that you want answered?

This post helps you identify great questions you can answer with email analytics and metrics.

Marketing data is a powerful resource. Today, more than ever before, you have the ability to access a treasure trove of valuable data about your customers’ actions. However, the data is only as valuable as the questions you ask.

Characteristics of Great Questions

You know that you are asking great questions when:

  1. The answer to the question will provide clarity or insight
  2. The answer to the question will bring value to your organization or team

Notice that a great question isn’t limited by the data that you already can access. I recommend instead that you identify the questions you want to be answered and then verify that you have access to the data that you need to answer the question or put in place the people, systems, and technology to collect the relevant data.

A question must be improved if it makes you feel uncertain or unclear about the next steps. In other words, if you don’t feel a clear “I know our next step” after you identify your question, then the question needs refinement. Attempting to answer a poorly defined question with your data will most likely be a waste of time. Invest time up front clarifying your question(s) before you dive into spreadsheets, reports and/or code.

It is helpful to identify (or revisit) your questions:

  1. Before you start analyzing data you’ve already collected and
  2. Before you start collecting data -- so that you can be sure you are capturing the right data points.

Two Parts to Great Questions:

Part 1: Clearly define your focus.

I recommend you start crafting your question by identifying what you want. Typically, you’ll focus on something that you want to increase (e.g., revenue, profits, opens, clicks, conversions, engagement) or decrease (e.g. bounces, complaints). Once you’ve selected your focus, make sure you clearly define it to remove any ambiguity. Words like “revenue,”  “engagement” and “conversion” always need to be defined clearly.  Also,  it often helps to specify a time range.

Example 1

  • Unclear: I want to focus on revenue.
  • Clear: I want to focus on the quarterly revenue per email sent (RPE) for product A

If you are looking to increase revenue, make sure to clarify what you mean. Are you interested in revenue across the whole organization, the revenue for a specific set of offerings, or the revenue for a single offer?

Example 2

  • Unclear: I want to focus on conversion rate.
  • Clear: I want to focus on the weekly conversion rate, where the conversion rate equals the number of people that RSVP’d for the webinar after clicking the RSVP link in the invitation email divided by the total number of people that were sent an invitation.

Conversion can mean so many different things, so it is essential that you clarify it. You’ll know you’ve clearly defined it when your feelings of uncertainty disappear.

Part 2: Define what you want to know about the focus.

Now that you have a focus, the next part is identifying what you want to know. Specifically, are you curious about:

  • What has happened?
  • What could happen? What will happen in the future?
  • What is the best way to improve?

Each of the bullets above relates to the three types of analytics (Descriptive, Predictive, and Prescriptive) [I discuss those three types of analytics here.]

If you are unsure about what you want to know, always start with “What has happened?” Answering that question is the foundation for the other two questions. Once you understand what has happened, new questions to ask will often come to mind. Often, after using Descriptive Analytics and Metrics to describe what has happened, you’ll also be curious as to “Why?” or “What if we compare that to ….?” and can start to compare and contrast successful campaigns and high-converting pages to identify patterns and root causes.

Putting those two things together, you’ll craft a great question (see the examples below) and be ready to maximize the use of your marketing data!

Part 1

I want to focus on the quarterly revenue per email sent (RPE) for product A

I want to focus on weekly conversion rate*

Part 2

What has happened?

What was the RPE for product A over the last quarter?

What was the RPE for product A during Q1 of 2020?

How does the last quarter of 2020 compare to the first quarter of 2020 for the RPE for product A?

What was the conversion rate last week?

What was the conversion rate for the 10th week of the year for 2018, 2019, and 2020?

What is the distribution of the weekly conversion rate over the last six months?

What could happen? What will happen in the future?

What is the RPE for product A forecast for Q3 2021?

What is the RPE for product A  forecast for each quarter in 2022?

What is a comfortable target for next week’s conversion rate?

What is a stretch goal for the conversion rate three weeks from now?

What is the best way to improve?

What are some recommendations for increasing RPE for product A for next quarter?

What changes do we need to make to our invitation email that will increase the conversion rate?

*where the conversion rate equals the number of people that RSVP’d for the webinar after clicking the RSVP link in the invitation email divided by the total number of people that were sent an invitation.

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