Helping Hermann’s Cake and Coffee Shop

Hermann has been running his own coffee shop and bakery for the last two years and has built up quite the loyal following. Some of his most loyal customers even call him “Uncle H” as he’s always around to share a story.

He used to be a motorbike mechanic in one of the older parts of the city but found that with all the tech companies moving in, he could make quite a lucrative business from selling them coffee and cakes. It turns out that techies really love having cool and unique places to hang out and work. Having spent most of his time hanging out with bikers, he has a lot of great stories which he would often entertain his patrons with over a nice hot drink and pastry.

Nowadays, the fervor which he used to devote to his motorcycle business has been transferred into his coffee shop. He focuses on having the finest organic and vegan food, and he is obsessed about tuning his coffee so that his coffee is ten times better than the shops down the road.

How can you help him to understand a bit more about his business using your new Data Studio techniques (Figure 2-1)? He will pay you with free coffees and cupcakes for a month if you can help him to make more money.

What Information Should You Show in Your Reports?

The first question is the most important one to understand. All people are trying to achieve something, so if you can make sure you have built alignment with them, it makes it easier for you to work together.

Identifying the exact information that will help them toward that goal is the next question. Typically most people will come to you with a set of requirements that they believe they need. It’s up to you as the data person to understand those requirements and make sure that they are really helping them to achieve what they need. If they don’t, you will find out really quickly because no one will look at your reports.

As you produce more reports, you will pick up experience with being able to filter out the “extra noise” and will be able to hear the various cues that indicate that the person is not sure of what they want or need and is just using their best guess. This will let you step in and guide them toward something more concrete and helpful.

The audience’s data expertise is covered in the third question, and it’s extremely difficult to gauge at the start of your working relationship with them. It’s also a question that most people will very rarely answer truthfully up front. People are generally very defensive when you ask straight out about how much they know about data. Instead of asking people outright, there are much better techniques to get this information.

I have had people tell me that they use Google Analytics “all the time” yet, when I look at their Google Analytics accounts, I can see that the accounts are hardly used (and in many cases giving inaccurate data). It’s not just at manager level, I have several experiences of working with extremely senior data directors who claimed to be experts, and I was surprised to find out that they didn’t understand simple concepts such as user conversions or bounce rate. Just because they got to their position without knowing the fundamentals of data analytics doesn’t mean you can’t teach them something new. If you are dealing with people who are not very sophisticated in terms of their data experience, then being able to give them answers in a simple and clear way will be vital.

On the other hand, some users are extremely sophisticated, and if you give them simple answers and no detail, they will quickly become frustrated and not trust the results you are giving them.

The fourth question, “How should it be presented,” is the most important one. The more you practice building dashboards, the more effective you will be at getting traction in your business.

Finding Out What Hermann Needs

When you start working with a new client or stakeholder, you need to try and understand what their need is. For Hermann’s coffee shop, it’s pretty clear. He has grown his shop organically by focusing on building relationships with customers and having a great quality set of products that people love. In the old days, that was enough, but nowadays, if you aren’t using data to drive your business, then you are only seeing a “slice” of the picture.

Hermann’s brief is to challenge you to use data to help him make more money. This is a pretty big ask and one we are unlikely to be able to fulfill. A lot of people just assume that waving the data “magic wand” on their business will suddenly materialize into money. Hermann is clearly one of these people. This is typically the part where you try and help them understand where data sits in the food chain.

Your answer should always be the same. You explain to Hermann that together we can use data to try understand better what’s going on which can help inform his decisions. Sometimes that leads to more money being made, sometimes it doesn’t.

Most business owners will look a little uncomfortable when you tell them that you might not be able to give them what they are expecting, but that’s OK. It’s better to make sure you manage people’s expectations instead of trying to deliver something that’s not realistic. The important thing is build up a good history of showing results and you will be able to use this to build trust early on with potential customers/internal teams.

The one guarantee that you can give anyone is that by making his data visible and easily accessible you can help to make smarter decisions in order to grow any business.

Back to your meeting with Hermann, you have a list of the four key questions you would like to ask him based on the previous section.

How Data Studio Can Help Hermann

If you can show Hermann how to use Data Studio to take his sales data and automatically process it and generate a report from the raw spreadsheet data, then you could help him to make decisions faster. He also wouldn’t need to pay the accountant to enter the data and return the data back to him. Instead he can focus on driving the improvements can come from the data.

You also suspect that since Hermann is so focused on his products, he will be able to ask much better questions of his data if he is able to take control of it himself. This might be the largest win for him in the long run.

Hermann forwards you the last few reports that he received from his accountant so you can see what reporting has changed. The good news is that we can definitely improve on it! Let’s crack on with the work.

Building a Report for Hermann’s Cake and Coffee Shop

Step 5: Create a Raw Table View of the Data

Whenever I start looking at the data that I need, I find that the easiest way to understand it is to use table control to investigate the raw data. This gives an overview of the data before we zoom down into the detail to get the information we need. It’s also handy for doing some initial quality checking and double checking that the data is there and it’s in the format we expect.

To create a raw table view of the data:

1. 1.

   Click “Add a chart” and select the first table icon on the top row as shown in Figure 2-2.

    
2. 2.

   Click the rectangle where you would like to place the table and you will see the data from your Google Sheet appear.

    

Now that we have the data successfully coming through from Google Sheets into our table, we can start to try and make the data useful to our client.

Helping Users to Ask Questions of the Data

Based on the data, we are going to try and help Hermann to understand his sales data in a bit more detail. A good starting point is to do some exploratory data analysis to understand the shape of the data. Some of the simpler questions we can answer using the data are

• What products are responsible for the majority of his sales?

• What types of flavors are customers buying the most of?

• How do the sales of these products compare vs. last year?

A raw table of data doesn’t really give us a clear indication of what’s going on with the sales. It just displayed to us a wall of text and numbers, which is difficult for our brains to process and interpret. We want the report to do the heavy processing for us to help our users understand the data. We can do this with by transforming the raw table into something more visual, such as a pie chart. By adding a pie chart to the Data Studio report, we are gifting the user an easier way to interpret the data. Humans are visual creatures and we relate to the world around us by using our senses to understand the world of us. The world of data is much the same; by adding visual features to the report that guide the user as to what the information is saying, it lets them focus on what is most important for them.

Add a Pie Chart

To add a pie chart to show the breakdown of sales:

1. 1.

   Click “Add a chart” and select the first Pie Chart control (Figure 2-3).

    

1. 2.

   Click where you want to place the chart.

   When we first add the pie chart, Data Studio defaults to showing the first field in the data set which is “Product Name.” It also defaults to showing us the data from this year. As you can see from Figure 2-4:

   • Our top selling product is “Banana Loaf,” closely followed by the delicious Lavender Cupcake. Good old traditional Chocolate Cake is sitting in at third most popular.

   • Our top four products account for roughly 50% of our total sales.

   • Each one of our top four products is selling roughly the same proportion of units.

    

Step 6: Duplicate the Pie Chart and Change the Dimension to “Product Type”

Let’s take a different view of the data to get a different perspective by duplicating the pie chart and changing the dimension to product type (Figure 2-5). To do this:

1. 1.

   Right-click the pie chart and select Duplicate.

    
2. 2.

   Drag the pie chart immediately to the right of the original pie chart.

    
3. 3.

   Select the new pie chart and click “Product Name” in the right Panel under “Dimension” and select “Product Type.”

    

When we selected the dimension called “Product Type,” we told Data Studio to reprocess the data in our table, and instead of grouping it by product name, we should instead group it by product type. By changing this “dimension” that it uses, it changes the lens that we use to look at the data and shows it from a different perspective. Dimensions (and metrics) are the fundamental building blocks for data reporting, and we will be exploring these further in the next few chapters in the book.

Step 7: Use Scorecard Control to Show Sales

With all reports, it’s important to recognize that there is a hierarchy of importance. Think back to your report cards that you received from your teacher at school. The most important information that you wanted to know was what your grade was for each subject. How would you have felt if the grade was hidden away at the bottom of several paragraphs of comments about how hard you worked? You would have been very frustrated and confused about why they had hidden away such important information. Much in the same way, we need to use scorecards to highlight the most important information to readers of our report.

Typically use scorecards to show off what we typically call “KPIs,” or key performance indicators.

The best and most concise definition of KPI I have seen comes from the UK’s Company Act where they define KPIs as “factors by reference to which the development, performance or position of the business of the company can be measured effectively.”

You will now see the scorecard with the “Number Sold” label (Figure 2-6).

For Hermann, his KPI is going to be how much product he sells so this is something to show immediately in the report. We use the scorecard control to show the number of products sold at the top of the report.

Step 8: Add a Date Comparison to the Scorecard

People’s fashion, tastes, and trends change regularly, and it’s up to businesses to use data to respond to these changes. If you are able to follow the changes in your customers’ tastes or even seek out new customers’ tastes to exploit, then you are winning.

We are going to help Hermann start on his journey of understanding what trends are affecting his business and give him an idea of what has changed over time with his sales. We hope that by doing this we might be able to identify some opportunities that he hasn’t thought of yet.

The “previous period” option is perhaps one of the most powerful features in Data Studio. It will take the current time period that you are looking at and compare it against the previous equivalent time period. You can thus use this control to compare week on week, month on month, or even year on year to see how your sales are changing.

We want to keep things simple for now so we are going to select “Last Year” and press “Apply” to complete our “Year on Year Scorecard.”

After a second or two, you will see below your scorecard a green arrow appear next to “47%” (Figure 2-7). This shows that the number of products sold has gone up 47% since last year which is an amazing result for Hermann.

Now that you know how to do basic comparisons with date ranges on scorecards, the good news is that you can do the same thing for tables too. Why don’t you try do the comparison year on year for the table of data you have and see which of Hermann’s products are responsible for driving his improvement in sales since last year.

Back to the Books

One of the most valuable things about trying to use data to solve a “real” world problem as we did in this chapter is that you begin to realize that there are gaps in your knowledge and there are new things that you need to learn.

From your first experiences using the Data Studio tool, you probably noticed there are so many new concepts and terms being used all over the place. Don’t worry, you’ll get the hang of them as we go through the book.

Recap

We tried out some simple controls such as tables, scorecards, and pie charts and even started doing some basic comparisons of this year vs. last year.

In the next chapters, we will expand on this, but hopefully you now have a good feel for using the Data Studio interface to explore your data.