Become a Data Explorer
Learning Objectives
The Exploration Goal: Who Are My Top Sellers?
You’re a sales manager at DTC Electronics, a leading provider of laptops, tablets, and other hardware devices. And you’ve just set out to master analytics.
You’ve got questions about your business, and the answers are in your data. So you need to become an explorer—a data explorer, that is—using CRM Analytics. As you work toward your badge for this module, you’ll start with a concrete goal that guides all your explorations. The basic concepts that you’ll learn will not only help you through this module but can be applied at your actual company. So, no time to waste—let’s go through the first use case!
Here’s your goal for this unit: The new quarter is starting and you want to run a bonus contest for the best seller in the company to drive sales in one of your product families. You don’t know which family to choose, but the answer is in your business data. You need to understand how your sales are spread among your products in order to choose the focus for your contest. CRM Analytics data exploration allows you to go from one answer to another naturally, and even answer new questions as they arise.
STOP! If you haven't completed the CRM Analytics Basics module, please go there first. You'll need to sign up for a special Developer Edition org before you can do this module.
Get Started with Queries
Make sure you’re logged in to CRM Analytics and that you’ve opened the app called My DTC Sales. You may have to click the App Launcher ( 
), and find and select Analytics Studio. Then search for My DTC Sales to browse the app.
), and find and select Analytics Studio. Then search for My DTC Sales to browse the app.
If an application error occurs while opening a dataset or dashboard, don’t worry. DE orgs sometimes encounter stale data that just needs a refresh. Start by clicking OK to close the error. Return to the CRM Analytics Home page and refresh your browser. You’re now ready for exploration!
Under the Datasets section, you should see a dataset called DTC Opportunity. Click to open it.
Now you’re in a tab called “New Lens.” You’ll see the initial state of your data exploration with a count of rows in your dataset. Hover your mouse over the bar to view a box with the exact number. If you wish to rename the Count of Rows label, click Show Fields Panel from the drop-down menu next to DTC Opportunity. Then, click 
. In the dialog box, enter the new label name and click Done to save your changes.
Throughout the exploration, you’ll ask questions about the data. Asking a question is what we call “running a query.” You’ll be changing the query one step at a time to get closer to your exploration goal, and you’ll see this simple bar transform into a sophisticated chart.
The left panel (where it says Bar Length, Bars, and Trellis) shows you the details of your exploration and lets you change the two main parts of the lens: the query and the visualization. You’ll see the visualization part later. The query can be split into three basic actions.
- Aggregating—Summarize the data by some measure. For example, the measure could be a count of the rows of data, as in the initial exploration state. Another common measure is a sum of the amounts.
- Grouping—Group the data by a certain dimension (more on dimensions in a bit). For example, group by product name or account.
- Filtering—Filter the data to narrow your results. For example, show only opportunities within the fiscal year.
Is the current query grouping by anything? Is it filtering by anything? Is it aggregating?
It’s not grouping or filtering, but it’s aggregating the count of rows, which is the default. Note that groups and filters are optional, whereas aggregation is required. Regardless of the query you use, there must be at least one measure to have a visualization.
Group Your Data
You’re interested in sales distribution among your products, but right now the numbers you see relate to all the products because there’s no grouping yet. In the first part of this exploration, you’ll try to find out which product family is bringing in the most revenue. To do so, you’ll group by product family, change the aggregation, and order the results.
Time to add a grouping by product family. Clicking the plus sign (+) under Bars opens a drop-down menu where you select the dimension to group by.
Don’t know what a dimension is? A dimension is a qualitative value, like region, product name, or model number. So it’s something you can group by.
In the list that appears when you click the Bars +, two categories appear: dates and dimensions. Dates are a special form of dimension that we’ll explore in more depth in the next unit.
Here, you want to group by Product Family. You can access the dimension faster by typing the name, then selecting it from the list.
Don’t worry if your charts look a bit different from the examples here and elsewhere in the trail. Slight differences in the data behind the charts might cause differences in the visualizations, but the basic elements of the charts should be the same.
You can see that the aggregation, Count of Rows, is now calculated for every group. But you want to see the revenue brought in by each product family, so you need to change the aggregation. Aggregations are typically made on measures.
What’s a measure? A measure is a quantitative value, such as revenue or exchange rate. In other words, it’s a number you can do math on, such as calculating the total revenue and minimum exchange rate.
- Under Bar Length, click Count of Rows to change the aggregation. The drop-down menu that opens shows you the calculations you can make using a measure, such as Sum or Average.
- You want to see the total revenue brought in by each product family, so click Sum. The list on the right shows the available measures.
- Select Amount.
The chart has been updated, and you can see that the value on each bar is different now!
It would be interesting to order the results to show the family with the biggest sum or total price (the biggest revenue) on top. Simply click Sum of Amount in the chart's axis label to view sales by product family arranged in descending order.
Now you have an interesting view of your sales by product family. You can see that laptops have made a strong showing and have moved into the second place over digital media. DTC has also made a big push behind the light laptop family product—boosting inventory and marketing activities—to go after the home and education markets. Can laptops catch accessories? Can you boost light laptop sales? That’s it! You need to run your sales contest on laptops to motivate your sales reps to sell this product family—especially DTC light laptops!
Drill into Your Data
There’s still a lot of valuable information in your data, so you keep digging. You want to learn how your top sales reps are promoting laptops so you can share the best practices for your sales bonus contest. Let’s see who’s at the top of the leaderboard.
Just by clicking the blue Laptops bar, you can drill into laptops sales data. Click once to select the bar, and then right-click to open the drop-down menu. Alternatively, click the Drill-down button ( 
). Select Opportunity Owner, and let the magic happen!
You can change the dimension and measure labels using a configuration file called extended metadata (XMD). For example, you can change Opportunity Owner to Opp Owner Name. For more details, see Labels Section in the online help.
With a click, you changed the single bar of global sales into a sales rep leaderboard for laptops. Take a look to see what changed in the query.
- Under Bars, the grouping has changed from Product Family to Opportunity Owner.
- You’re filtering the product family by laptops only.
You now have an answer to the leaderboard question! But wait! Is it the real answer?
Filter Your Data
Before jumping to conclusions when you have your query results, make sure you ask the full question. In this case, you’re looking at all the closed opportunities. Closed opportunities can be won or lost opportunities. So to see which sales rep is bringing in the most revenue to the company, you need to filter by the won opportunities only.
You can filter by measures, aggregated measures, dates, and dimensions. We’ll cover the different filters in more depth later on. For now, you want to filter out everything except won opportunities.
- In the Filters tab, click the plus sign (+) under Filters.
- Search for Won, and then click it.
- Select the value true.
- Click Apply.
Did you notice the animation when you added the filter? It’s a great visual way to understand how the results change. Your top sales reps are different when you’re focusing only on the won deals. Some reps went down, others went up, and it’s important to know how they moved when you focus on won opportunities.
Keep Digging: Ask the Next Question
Now that you have a leaderboard, it makes sense to break things down in more detail. Which products in the laptop family are selling the best? With traditional business intelligence tools, you had to ask IT this new question and wait until they could process your request. With CRM Analytics, it’s a matter of a few clicks. Self-service!
The first step is to add a new grouping by the product name. You probably remember how to do it by now, but just in case, switch to the Data tab. Then, click the plus sign (+) under Bars and then select Product Name. You’ll see a couple of interesting changes in the chart.
- There are now two dimensions under Bars on the left of the bar chart: Opportunity Owner and Product Name.
- The chart now highlights the second grouping (product name) by color. The right side of the chart includes a legend showing the color-product relationship.
Colors are defined from a default palette for now. You can manually choose the colors through the extended metadata (XMD) configuration file. See Colors Section in the Salesforce online help.
This visualization tells you what products are bringing in the most revenue. As you hoped, light laptops are doing great. Let’s bring this information together with information in the sales rep leaderboard by changing the visualization.
Choose the Right Visualization
As a reminder, an exploration has two main parts: the query and the visualization. A query returns results, the way a question gets an answer. The results can be displayed differently depending on the visualization, just as there are different ways to answer a question! In your visualization, the bars show the result of your query in what we call a bar chart visualization. You’ll see the different visualizations and learn when to use each one as you go through the other units.
You want to identify the rep who’s best at selling laptops, so you want to see one bar per owner name, but keep the product name grouping. So what if you could “stack” the values for each sales rep?
To see the options for charts, click the chart gallery icon ( 
) at the right. Locate Stacked Bar and click it to see what happens. Then click again to close the charts panel.
Tip
By hovering over each visualization, you’ll see a message telling you how many measures and dimensions it can handle. It’s a good way to learn which chart is best for which situation.
Each visualization has a different way to handle multiple groupings or measures. Try clicking the charts icon ( ) again, and then select Donut. In this case, it’s creating a donut for each first grouping (Opportunity Owner) and displaying the second grouping on it (Product Name).
As you did at the beginning, you can hover over any segment to get more information about the values. Multiple grouping charts give you even more valuable information than single groupings, for example you can see the percentage of each second dimension value.
Donut charts are a good way to quickly see the composition of your data. Here’s a summary of the best chart to use based on the insight you’re seeking:
Now try grouping by the product name first.
- Under Trellis, delete Opportunity Owner.
- Change Segments to Opportunity Owner.
- Under Trellis, click + to add Product Name.
The visualization now has donuts for each product. On each donut, the second grouping is now by opportunity owner.
Navigate Your Exploration History
As you continue exploring, you might want to go back to a previous visualization. For example, let’s say you decide the donuts aren’t the right way to look at the data. In fact, the stacked chart you had a few steps ago would have been perfect to share with your team. If only you could move backward in your exploration. The good news is, you can! The arrows at the top allow you to freely move back and forth in your exploration.
You can click 
to go back one step. Or click 
from the More menu to go back where you started. Let’s go back to the stacked bar chart that you wanted.
to go back one step. Or click from the More menu to go back where you started. Let’s go back to the stacked bar chart that you wanted.- Click
to see the full list of your exploration steps. - Click Updated chart to: Stacked Bar.
- Click again to close the History panel.
Important
Changing the chart type can also change the query behind the chart. When that happens, the query remains in it’s changed state, even if you then select the old chart type again. To be sure you’re working with the initial query, use the history tools to go back to the earlier visualization.
Notice that the legend makes the chart look crowded. Let’s adjust the layout.
- Click the Properties icon (
) to open the Formatting panel. - Click the v next to Legend.
- Select Show legend inside chart area.
- Under Position, select bottom-center.
- Click again to close the Formatting panel.
Save Your Work in a Lens
You got an interesting answer from your data, but you don’t want to have to redo the exploration each time you need the answer. That’s why you can save your exploration in what we call a lens. It will be part of an app, so that you can share it with a group of people or save it to access later. It will also be available on your mobile device!
- Click Save.
- Enter D01 - Laptops Salespeople - Wall of Fame as the title.
- Change the app by clicking My Private App and then selecting My Exploration.
- Click Save.
A lens keeps the query (aggregation, grouping, and filtering) and the chart type, but not the results. It’s like saving the question and not the answer, because the answer is too big, and you can have it instantly by asking the question again.
You’re on Your Way, Explorer!
Voilà. You had a goal in mind, which you successfully fulfilled through a quick exploration that you saved to share with your coworkers. It’s time to high-five yourself!
Here are the main concepts you should take away.
- A dimension is a descriptive value, whereas a measure is a value you can do math on.
- Each visualization is efficient in specific use cases. Choose visualizations based on the major insights you want to derive from them.
- Don't be afraid to go exploring. You can see every step of the journey in the history and navigate between the steps easily.
- You can save an exploration in a lens.
- When you’re exploring data, you’re just mixing and matching four basic actions: aggregating, grouping, filtering, and creating a meaningful visualization.
In the next unit, you’ll spend more time on date-based explorations that include groups, filters, and visualizations. Are you ready to learn more?