This content, written by Elena Rowell, was initially posted in Looker Blog on Aug 9, 2017. The content is subject to limited support.
Have you ever heard the quote “Those who do not learn history are doomed to repeat it”? Data is business’ way of learning history. Without looking at what we have done, we cannot know what worked and what did not.
How about this one - “Without data, you’re just another person with an opinion.” You will always have opinions that are fueled by experience (helpful) and emotion (sometimes not so helpful). But when you add data, you still have the experience and emotion and you also have cold, hard, numbers.
Okay, last quote - “I have not failed. I’ve just found 10,000 ways that don’t work.” Data allows you to test things quickly. If you can access granular data, you can see successes and failures before they impact higher level metrics. If you test something and can quickly identify that it doesn’t work and change that test, it’s not a failure— it’s a learning.
Dashboards are a great way to access and share this data. A powerful dashboard not only brings data into the conversation — it tells a story with that data.
In this series of blogs, I will talk through some of the best practices I follow every time I build a new dashboard, as well as some of the analytical foundations that go into telling the best story possible with data.
So you’re making a new dashboard. Wahoo! Before you dive into the data and start building tiles, I recommend asking yourself these five questions. In my experience, answering these questions at the outset helps me to create a more effective dashboard. So, without further ado, here we go!
What am I going to do with it?
If the answer to this question does not immediately fly to the tip of your tongue, you probably don’t need a new dashboard. There are a myriad of creative things one can use a dashboard for, but for the most part, the goal of a dashboard is to….
- ...track an ongoing initiative or campaign. This could be anything from quarterly meeting goals to current ad campaigns. I have a number of different dashboards that help me keep an eye on my various in-flight campaigns, both big and small, so I can see if we need to tweak everything.
- ...lookup known entities. These are great, because they allow you to quickly pull up all the information you need on anything from a customer to a campaign. My favorite here is my event lookup dashboard which allows me to look up any past events to see the current state of the leads associated with it.
What question(s) am I trying to answer?
This answer may take a little bit longer to come up with, since it’s generally a more complex thought. A great dashboard combines multiple pieces of data to answer a broader question. Instead of asking “How many people have registered for my event” you want to think about the bigger picture: “Am I on track to hit my registration goal?” This larger question allows you to look at your question from multiple angles and give a fuller picture of the situation. When you start to build, this answer will become your guiding light. As such, we’ll come back to it later in this post.
Is there an existing dashboard that I can use to answer my question?
As marketers, we have learned to reduce, reuse and recycle anything possible. Can we turn this blog into a white paper? What about a webinar? The same principles hold true for dashboards. Why create something new if someone has already done the work? If you can’t find something that answers your question completely, you still might be able to find a dashboard you can use as a jumping off point.
What am I measuring?
Before you can start putting a dashboard together, you have to understand what you’re measuring and how you’re measuring it. Here are some examples of simple ways to measure your work:
- Attempts - How many times did someone try to do something?
- Impressions - How often do people see something?
- Successes - How many times did people successfully do that thing?
- Conversions - What percentage of people who did X progressed to Y?
- People - How many different people did something?
- Totals - What was today’s total revenue/total time on site/total net profit**?
- Averages of things that vary - What was the average/median/mode number/time of this thing?
- Quality - How many people used X and how many tried to use X but failed?
- Quality Ratios - What percentage of the people who tried to do X had issues?
- Against basic dimensions - Here we’re going to combine two pieces of data to get answer a more specific question - For example, How many orders were placed today by people between 16 and 25? What about between 26 and 35?
Now that you’ve answered all those questions at a high-level, it’s time to start building. Check back next week for part two of this series. In that post, I will step through outlining a dashboard, as well as touch upon some of the key things to keep in mind as you build.