Submit a request

How can we help?

Articles in this section

Choosing the Right Chart & Calculated Fields

Updated

Picking a chart type that answers your question, and creating calculated values a card can plot.

On this page:

Choosing a chart

Start from the question you’re answering rather than the chart you like: how many deals closed last quarter, are we on track against target, and so on. The question determines the chart type.

Trends. For questions like revenue by month for last year, or how incoming leads are trending over the last six months, line charts are the best option. Dates run across the bottom (x-axis) and values down the side (y-axis), like a stock market chart.

Sales Activity and Average Sales Size Over Time — A line chart displays two metrics—Number of Sales and Average Sales Size—across dates from October 11–13, 2017, with Average Sales Size peaking sharply around 50,000 on October 12 at 14:12. This visualization helps users understand how to interpret sales trend reports within Insightly CRM dashboards.

Sales Activity and Average Sales Size Over Time

Comparisons. To compare how one rep is closing sales against others, or which marketing piece brings in more customers, use line charts, bar charts, or a combination of the two to display similar data together and spot a pattern or a winner.

Expected Revenue by Responsible User Bar Chart — This bar chart displays the sum of expected revenue broken down by responsible user (Anthony Nguyen, Ben Richardson, and Caitlin Deming), with multiple colored bars representing different revenue categories for each person. Anthony Nguyen shows the highest expected revenue values, making this useful for sales managers comparing pipeline performance across team members in Insightly CRM.

Expected Revenue by Responsible User Bar Chart

Comparisons by region. To see where business is coming from, use maps to visualize revenue sources. You can choose from global, continental, or country maps.

US Bid Amount Distribution by State Map — A choropleth map of the United States displaying the sum of bid amounts by state, totaling $5,734,000, with California showing the highest value at $1,480,000 in dark blue and other active states including Colorado, Missouri, Alabama, New York, and Alaska shown in lighter shades. This visual helps users understand how Insightly CRM can aggregate and display opportunity or bid data geographically across a custom report or dashboard.

US Bid Amount Distribution by State Map

Comparisons along a trendline. To see how many projects were completed in each category in each month, use stacked area charts. They merge separate line graphs into one chart, shading the area below each line a different color so differences compare easily.

Expected Revenue Over Time Area Chart — This stacked area chart displays the sum of expected revenue across multiple CRM pipeline stages between October 11–12, 2017, with a notable peak around October 12 at 14:12. It helps users understand how to visualize and track revenue trends over time using Insightly’s reporting features.

Expected Revenue Over Time Area Chart

Relationships. To find a correlation between two values, such as a customer’s first purchase amount and their total number of transactions, use a scatter plot. Plotting the intersection of two values as points can reveal a trend you might not otherwise spot.

Scatter Plot of Sales Volume vs. Average Deal Size — This scatter plot shows the relationship between the number of sales and the average sales size for different records, with most activity clustered at lower sale counts (under 10) and a wide range of average deal sizes up to $500,000. A user would reference this to understand how deal size varies across sales representatives or pipelines, helping identify high-value but low-volume patterns.

Scatter Plot of Sales Volume vs. Average Deal Size

Goals. To see how close you are to a target, use gauges. They work like a car’s speedometer: you set the goal when you set up the chart, and the needle moves toward it as the value grows.

CRM Pipeline Value Gauge Chart Example — A speedometer-style gauge chart displays a sales pipeline value of approximately $2,500,000, with color zones ranging from light blue through orange to red indicating performance thresholds up to $3,000,000. This visual helps CRM users understand how to read and interpret gauge charts used to track revenue or pipeline targets within Insightly dashboards.

CRM Pipeline Value Gauge Chart Example

Distributions. To see how deals break down by lead source, or how many opportunities are open in each category, use vertical bar charts or scatter plots. A distribution shows how things break down by a category or label.

Opportunity Pipeline Activity by Forecast Month — A bar chart compares the count of closed, won, and opened opportunities for March and February 2018, showing March had 7 closed and 7 won opportunities while 9 were opened, and February had 3 closed and 4 opened. This helps users understand how to interpret pipeline trend data within Insightly’s reporting features.

Opportunity Pipeline Activity by Forecast Month

Compositions. To show a breakdown of a total, such as new versus repeat customers or acquisition spend by lead source, use a pie chart or its cousin the donut chart. A funnel chart also works here and is well suited to showing the number of items or total value in each stage of an Insightly pipeline. You don’t even need a numerical value; a glance at each slice gives the big picture.

Pie Chart of Opportunity Pipeline by Status — A pie chart breaks down sales opportunities into five statuses: Won, Open, Suspended, Lost, and Abandoned, with Won taking the largest share. This helps CRM users understand how to interpret pipeline reporting visuals within Insightly.

Pie Chart of Opportunity Pipeline by Status

 Opportunity Pipeline Status Distribution Chart — A donut chart breaks down sales opportunities into five status categories: Abandoned, Lost, Open, Suspended, and Won. This visualization helps CRM users quickly assess the proportion of deals in each stage, making it easier to evaluate overall pipeline health and sales team performance.

Opportunity Pipeline Status Distribution Chart

 Sales Pipeline Funnel Chart by Stage — A funnel chart breaks down the sales pipeline into four stages—Prospecting ($1.30M, 53%), Qualification ($0.80M, 34%), Needs Analysis ($0.10M, 5%), and Negotiation ($0.10M, 6%)—showing how deal value narrows as opportunities progress. This helps users understand how Insightly visualizes pipeline distribution and where the majority of their revenue opportunities currently sit.

Sales Pipeline Funnel Chart by Stage

Compositions along a trendline. To see monthly sales broken down by category, use stacked bar charts. They combine a bar graph and a pie chart, letting you see trends as well as the composition of each data point.

Comparison of three or more quantitative variables. To map survey results across several questions, use radar charts. They plot three or more values in a pattern that looks like a spiderweb, and you can compare one radar chart against another to see how close you are to your goal for each data point.

ℹ️ When the chart type is bar, column, range bar, range column, bubble, donut, pie, candlestick, ohlc (high low), or waterfall, you can define the chart’s color scheme. In Chart Properties, use Series Colors to choose from available color themes. Color settings are retained when cards are saved and when the chart type changes. If series are added after custom colors are chosen, Insightly assigns custom colors to the added series, and color settings are also carried over when a card is cloned.

Calculated fields for cards

A calculated field derives a new value from data you already hold, so a card can plot something that isn’t stored directly. This new field is saved to your Values list and can be used in your charts. For example, Average Order Value uses the formula SUM("Sale"/"Orders").

Dashboard calculated fields use T-SQL (Transact-SQL). If you aren’t familiar with SQL or haven’t built similar formulas in Excel, consider getting help from someone who is. This is a different feature from record-level custom calculated fields; to create a calculated field that appears in your records, see the Custom Fields guide instead.

To create a calculated field:

  1. From the dashboard card edit page, click Add Calculated Field.
  2. Enter a name for the field. When you save it, the name appears in the Categories or Values list with an equals sign (=) in front of it.
  3. Enter a formula in the Formula field. You can build a formula by double-clicking any item in the Dataset or Functions lists, typing directly in the field, or copying and pasting a provided formula. Select any function to see its description, examples, and a link to more information.
  4. Click Save And Close. Your new field appears in the Categories or Values list with an equals sign in front of it.

Sample calculations

  • Opportunities Won: SUM(CASE WHEN "Current State" = 'WON' THEN 1 ELSE 0 END)
  • Total Opportunities: COUNT("Record ID")
  • YoY Calculated Field: FORMAT(CONVERT(datetime, "Lead Created"), 'yyyy')
  • Win Rate (Opportunities Won / Total Opportunities): CAST(SUM(CASE WHEN "Current State" = 'WON' THEN 1 ELSE 0 END) AS DECIMAL(10,2)) / CAST(COUNT("Record ID") AS DECIMAL(10,2))
  • Change dates to Month, Year format: FORMAT(CONVERT(datetime, "Lead Created"), 'yyyy/MM')
  • Change dates to Month, Day, Year format: FORMAT(CONVERT(DATETIME, "Opportunity Created"), 'MM/dd/yyyy')

When performing a division, convert both the numerator and denominator to decimals first, using either CONVERT or CAST, for example CAST(COUNT("Record ID") AS DECIMAL(10,2)).

Creating a Calculated Field Named Win Rate — The screenshot shows a “Calculated Field” dialog box in Insightly CRM, where a user has typed “Win Rate” as the field name and is about to enter a formula. This is relevant for users who want to create custom calculated fields to automatically compute metrics like sales win rates within their CRM.

1 Creating a Calculated Field Named Win Rate

 Calculated Field Formula Builder in Insightly CRM — The image shows the interface for creating a calculated field named “Win Rate,” with a blank formula editor and two panels listing available dataset fields and functions such as ABS, AVG, CASE, and CONCAT. This would help users understand how to build custom calculated fields by combining existing data fields with built-in functions.

2 Calculated Field Formula Builder in Insightly CRM
CASE Function Selected in Formula Builder — The image shows a formula builder interface with the CASE function highlighted, displaying its description, an example, and syntax on the right panel. This helps users understand how to use the CASE function to match values and return corresponding results when building custom formulas in Insightly CRM.

3 CASE Function Selected in Formula Builder

 Calculated Field Added to Values List — The image shows a VALUES panel listing numeric fields such as Bid Amount, Expected Revenue, and Probability, with a custom calculated field called “Win Rate” selected at the bottom. This illustrates how a newly created calculated field appears alongside standard fields, helping users confirm their field was successfully added.

4 Calculated Field Added to Values List

Related to

Related articles

Powered by Zendesk