What does a NetSuite workbook look like in action? How do the visualization options actually impact the display of your data? In our previous blog, we looked at the basic components of a SuiteAnalytics Workbook. But some of these details don’t really click until you put them into practice. So, let’s create a sample NetSuite workbook.

Before You Get Started

First, you need to establish some workbook goals. What do you want this NetSuite workbook to accomplish? Technically you answered that question when you first created the dataset that you will use in the workbook. Since we already created a sample dataset in this series (if you missed that blog, check it out here), then we’ll just use that dataset for our workbook. Taking this dataset into mind, then, our goal with this workbook is to analyze the effect that our sales reps and campaigns have had on our quotes and sales orders. We want to be able to break this information down in different ways in order to highlight specific data, so we’ll need all of this information to be accessible in the same workbook. To accomplish this goal, we pulled fields from multiple record types while we were creating the dataset. Now that we know what information we’re after, we can go right ahead and create that workbook.

Building a Sample NetSuite Workbook

To create our workbook, we’re going to go to the Analytics page and select the Workbooks tab. Then, we’ll select the dataset we created previously. Now that we have the basic workbook in place, let’s start building it out and adding tabs to it. We’re going to have three different tabs on this workbook—one for each of the visualization options.


Let’s make a table first. To create a table, select the Table tile on the new workbook tab screen.

We want this table to show us the companies we have provided quotes for and the sales reps that were involved with those companies. To accomplish this, we’ll drag the Entity field, Type field, and Sales Rep field onto the table. Now our table looks like this: 

As you can see, we now have 11,091 rows in our table because our table currently includes both sales orders and quotes. To filter the results to include just quotes, select the three dots to the right of the Type column header and choose Filter. In the popup box, move Quote from the left column to the right and select Apply. 

Setting this filter narrows down the results to just the ones that we are interested in seeing. 

Before we leave this table, let’s set some conditional formatting. Suppose we want to highlight which customers do not have a sales rep assigned to them. To do this, select the three dots to the right of the Sales Rep column header and choose Conditional Formatting > Manage Conditional Formatting. 

As you can see, we set the rule to “is empty” and chose to have a red flag appear when a sales rep is absent. Now, our table looks like this. Notice that the quote filter has been applied, and notice the occurrences of a couple red flags to signal that no sales rep has been assigned to those customers.

And that’s a table! Before moving on to the next visualization type, it’s a good idea to name the tab you’re on so you can easily understand what information is in this tab and so you can quickly locate and use this workbook elsewhere in NetSuite (like in a dashboard portlet).


Next, let’s create a pivot. To do that, select the plus sign to the right of the current tab name. Then, select the Pivot tile.

For our pivot, we want to show the top ten lead sources for our highest-revenue customers. And at this point, when looking at our current dataset, we realize that we don’t actually have that information in our dataset. To edit our dataset and add that information, select the three dots to the right of the dataset name (highlighted in blue) and choose Open Dataset. In the dataset, choose the record type Entity Customer and drag the field Lead Source onto the data grid. Then, select the Apply to Workbook button at the top of the page. 

Now, back on our pivot workbook page, we’re ready to use the Lead Source field. We’ll drag the Lead Source field to the Rows section, the Entity and Type fields to the Columns section, and the Revenue field to the Measures section. Then, we’ll filter the Lead Source by the top 10. After refreshing the workbook page, here’s what our pivot looks like:

With this pivot, we can easily see what our top ten lead sources are as well as our top customers. Notice, however, that because we haven’t filtered down the type of transaction, we have a column for both quotes and sales orders. For this pivot, however, we only need to see revenue from sales orders. In order to do that, filter the Type field to show only sales orders. After setting that filter, this is what our pivot looks like: 

Now that we’re finished with the pivot, we can name this workbook tab and move on to our final tab. But before we do that, we need to address the warning sign to the left of the dataset name. When we added Lead Source to the dataset, we didn’t actually save the dataset. To ensure that you don’t lose your work, go ahead and save the dataset now by selecting the three dots next to the dataset name and choosing Save Changes.


For our final workbook tab, select the plus button to add a new tab and choose the Chart tile.

Before we start adding fields to this chart, we need to determine what kind of chart we want. The default chart is a column chart, but you could also use bar charts, area charts, line charts, and even various stacked charts. For this tab, we’ll just use the default column chart. 

For our chart, we’re interested in seeing some of the top stats for a particular campaign we’ve run. We want to see our highest-revenue customers from that campaign. To get those results, we’ll drop the Campaign field in the X-Axis section, the Entity field in the Series section, and the Revenue field in the Measures section. Then, we need to filter the Campaign field to the specific campaign we want to know more about and the Entity field to the top 10 customers. Here’s what our chart looks like:

As with the other tabs, once we are satisfied with the results we will give this tab a descriptive name. Then, we’ll save the entire workbook so we don’t lose all our work.

Finetuning Workbook Results

As you may have noticed, workbooks give you a lot of options, and it can be easy to get overwhelmed by all the options. But once you get comfortable with the different visualization types and with using sorting and filtering to your advantage, workbooks will become much less intimidating. To be sure you are getting the best results possible, don’t hesitate to experiment with the different options in order to finetune your workbook results.


We’ve now created a basic NetSuite workbook! Have you been following along with this dataset and workbook, or did you experiment with your own? Let us know in the comments how things went for you! Now that we’ve taken a close look at datasets and workbooks, in the next several blogs we’ll be moving into our next key SuiteAnalytics topic: reports. To keep up with this series, be sure to subscribe to our newsletter below to have each blog delivered right to your inbox!