Key Takeaways<\/h2>\n\n- Break down ARR by customer, territory, and revenue stream to see where recurring income is concentrated.<\/li>\n
- Separate cancellations, contractions, and expansions to understand what is changing retention and recurring revenue.<\/li>\n
- Track new, expansion, contraction, and churned MRR to make net new MRR easier to interpret.<\/li>\n
- Define core KPIs consistently so teams can use churn, retention, CAC, LTV, and ARPU to guide decisions.<\/li>\n<\/ul>\n<\/div>\n\n
Table of Contents<\/h2>\n\n- What's Inside the SaaS Metrics Dashboard Template?<\/a><\/li>\n
- Automated churn, retention, and recurring-revenue calculations<\/a><\/li>\n
- MRR and net new MRR tracking<\/a><\/li>\n
- Core SaaS dashboard metrics and KPI definitions<\/a><\/li>\n
- Biz Infographs: PowerPoint Infographic Templates<\/a><\/li>\n<\/ul>\n<\/div>\n
What’s Inside the SaaS Metrics Dashboard Template?<\/h2>\n
A useful dashboard connects revenue, customer, engagement, and conversion measures. Start by deciding which questions and decisions the metrics need to support.<\/p>\n
Revenue and Conversion Metrics<\/h3>\n
Break ARR down by customer, territory, and revenue stream to see where recurring revenue is concentrated. Compare trial-to-paid conversion with customer acquisition cost (CAC), the average cost of acquiring a new customer, including marketing and sales spend. If conversion falls as CAC rises, for example, review both acquisition spending and trial performance. Include customer and engagement measures to help explain revenue and retention changes, rather than reporting totals alone.<\/p>\n
Dashboard Formats and Billing Views<\/h3>\n
Choose a Looker Studio, Tableau, or Power BI template based on its data connections and intended users. A hosted dashboard offers a ready-made environment, while a custom dashboard can reflect specific reporting needs. Template prices vary by format, features, and functionality, so compare what each includes rather than relying on a headline price. Spreadsheet-template libraries also offer free Excel or Google Sheets options. Check which metrics are included before using one.<\/p>\n
Keep customer-facing billing screens separate from internal finance dashboards. Customers need clear charges and subscription details. Internal teams may need revenue by customer, territory, and stream, along with contraction and account trends.<\/p>\n
Data Connections and Dashboard Setup<\/h3>\n
Build the dashboard in stages. Define each metric, connect billing records to subscription revenue, then align product analytics events with CRM customer records. Use consistent customer identifiers so trial, paid account, and product activity all point to the same account. Map event names to the features or actions they measure, then test a sample account across all three sources before relying on the totals.<\/p>\n
Set the refresh schedule to match the decisions the dashboard supports. Automated refreshes keep metrics current, rather than relying on last week\u2019s export. Check for mismatched date ranges, duplicate customer records, and unclear metric definitions, all of which can distort revenue or conversion trends. Review the dashboard with its intended users and refine the views they rely on.<\/p>\n
Automated churn, retention, and recurring-revenue calculations<\/h2>\n
Automated calculations show how subscriptions change as customers start, renew, expand, or cancel. Compare customer losses with revenue changes to understand what is driving recurring revenue.<\/p>\n
Churn and Retention Measures<\/h3>\n
Logo churn counts customers who cancel during a period. Gross revenue churn measures recurring revenue lost through cancellations and contraction. Net revenue retention starts with recurring revenue from existing customers, adds expansion, and accounts for losses. A retention dashboard that tracks cancellations, contractions, expansions, and MRR helps teams distinguish lost accounts from reduced subscription value.<\/p>\n
Keep the period and customer group consistent for each measure. For example, compare the same starting cohort across periods instead of mixing new subscriptions with established accounts. This makes churn and retention trends easier to interpret, while keeping acquisition activity visible as a separate source of growth.<\/p>\n
Churn, MRR, ARR, and Subscriber Tracking<\/h3>\n
Use charts to compare churn, MRR, and ARR over matching periods. MRR captures monthly subscription revenue; ARR expresses MRR on an annualized basis. Subscriber counts add context: a stable revenue line could hide cancellations offset by expansion from remaining accounts. Review revenue, subscriber counts, and churn together to determine whether changes came from new accounts, renewals, or existing customers.<\/p>\n
Separate opportunities into new subscriptions, renewals, expansion, and churn risks. Record the account, current status, and expected revenue change for each. Then compare actual results with the opportunity view to see which changes delivered recurring revenue and which remained projections.<\/p>\n
For consistent calculations, one example model normalizes active subscriptions at month-end, divides annual contracts by 12, and excludes one-off fees. It records discounted contracts at the amount customers actually pay. Clear definitions help teams monitor trends without confusing billing adjustments with subscription performance. Use charts to visualize recurring-revenue trends<\/a> across these measures.<\/p>\n<\/p>\n
![\"SaaS](\"https:\/\/www.bizinfograph.com\/blog\/wp-content\/uploads\/2026\/11\/infographic_1793517247_gGYGsHw5-scaled.jpg\")
<\/div>\n<\/p>\n
MRR and net new MRR tracking<\/h2>\n
Monthly recurring revenue (MRR) gives teams a consistent view of subscription income. Net new MRR explains how that total changed, separating new business from changes in existing accounts. Track the two together: MRR shows the current position, while net new MRR reveals the movement behind it.<\/p>\n
Calculate net new MRR from four components: new subscriptions, expansion, contraction, and churn. Add MRR from new accounts and upgrades, then subtract revenue reductions and cancellations. The result shows whether growth came from acquisition or existing customers. It also helps teams investigate whether a decline reflects lost subscribers or smaller subscriptions.<\/p>\n
For example, an illustrative company recorded $714,209 in MRR in October 2024. In September 2026, its MRR was $1,209,761. Those snapshots show the recurring-revenue totals for each month; a net new MRR view would reveal the additions and losses between them. Avoid reading the totals alone as a complete account of growth.<\/p>\n
ARR offers an annualized view for planning, while MRR supports month-to-month analytics. In October 2024, the example company reported $8.6 million in ARR and 493 customers. Comparing customer count with revenue helps reveal whether account growth and recurring income are moving together. Keep the reporting period and underlying customer group consistent to make those trends meaningful.<\/p>\n
For reliable SaaS metrics tracking, define how billing changes appear in the numbers before comparing periods. A native integration can bring subscription and customer records into one reporting flow. A spreadsheet import can also work if teams map fields consistently. Match customer identifiers across billing and CRM records, then check unusual changes against account activity.<\/p>\n
Display MRR, net new MRR, ARR, and subscriber counts side by side. Add lifetime customer context when it supports a decision, but keep it distinct from current-period revenue. This layout helps founders and finance teams identify whether a change came from acquisition, expansion, contraction, or churn, then focus follow-up analysis on the relevant accounts.<\/p>\n
Core SaaS dashboard metrics and KPI definitions<\/h2>\n
A useful KPI dashboard clarifies each measure before teams act on it. Define the time period, customer group, and calculation behind every metric, then compare like with like. Monthly reporting shows operating changes, while annual views support broader planning. Consistent definitions across reports matter more than the platform.<\/p>\n
Use these core definitions to connect acquisition, customer value, and revenue performance:<\/p>\n
\n- Churn rate:<\/strong> the percentage of customers who cancel during a given period. Compare the same customer group and period to interpret changes.<\/li>\n
- Customer retention rate:<\/strong> the percentage of customers kept over a given period. Read it beside churn to understand customer movement.<\/li>\n
- Lifetime value (LTV):<\/strong> estimated net revenue a customer generates over the full length of their relationship with a business.<\/li>\n
- LTV:CAC ratio:<\/strong> compares lifetime value with customer acquisition cost. Use consistent customer and cost definitions for a meaningful comparison.<\/li>\n
- Average revenue per user (ARPU):<\/strong> total revenue divided by the number of customers. State which revenue period the calculation uses.<\/li>\n<\/ul>\n
Conversion metrics add context to these measures. Trial-to-paid conversion shows how effectively trials become paid subscriptions; customer acquisition cost is the average cost of acquiring a new customer, including marketing and sales spend. Read them together to assess acquisition quality, not just signup volume. For instance, rising signups alongside weaker conversion can change how teams interpret acquisition activity.<\/p>\n
Benchmarks provide context, not automatic targets. According to High Alpha\u2019s 2025 benchmarks, SaaS companies with $5 million to $20 million ARR had median growth of 31%, net revenue retention of 103%, and software gross margin of 80%. SaaS Capital\u2019s 2025 retention study found median net revenue retention of 101% among private B2B SaaS companies. The populations differ, so keep each benchmark\u2019s scope visible.<\/p>\n
Table of Contents<\/h2>\n\n- What's Inside the SaaS Metrics Dashboard Template?<\/a><\/li>\n
- Automated churn, retention, and recurring-revenue calculations<\/a><\/li>\n
- MRR and net new MRR tracking<\/a><\/li>\n
- Core SaaS dashboard metrics and KPI definitions<\/a><\/li>\n
- Biz Infographs: PowerPoint Infographic Templates<\/a><\/li>\n<\/ul>\n<\/div>\n
What’s Inside the SaaS Metrics Dashboard Template?<\/h2>\n
A useful dashboard connects revenue, customer, engagement, and conversion measures. Start by deciding which questions and decisions the metrics need to support.<\/p>\n
Revenue and Conversion Metrics<\/h3>\n
Break ARR down by customer, territory, and revenue stream to see where recurring revenue is concentrated. Compare trial-to-paid conversion with customer acquisition cost (CAC), the average cost of acquiring a new customer, including marketing and sales spend. If conversion falls as CAC rises, for example, review both acquisition spending and trial performance. Include customer and engagement measures to help explain revenue and retention changes, rather than reporting totals alone.<\/p>\n
Dashboard Formats and Billing Views<\/h3>\n
Choose a Looker Studio, Tableau, or Power BI template based on its data connections and intended users. A hosted dashboard offers a ready-made environment, while a custom dashboard can reflect specific reporting needs. Template prices vary by format, features, and functionality, so compare what each includes rather than relying on a headline price. Spreadsheet-template libraries also offer free Excel or Google Sheets options. Check which metrics are included before using one.<\/p>\n
Keep customer-facing billing screens separate from internal finance dashboards. Customers need clear charges and subscription details. Internal teams may need revenue by customer, territory, and stream, along with contraction and account trends.<\/p>\n
Data Connections and Dashboard Setup<\/h3>\n
Build the dashboard in stages. Define each metric, connect billing records to subscription revenue, then align product analytics events with CRM customer records. Use consistent customer identifiers so trial, paid account, and product activity all point to the same account. Map event names to the features or actions they measure, then test a sample account across all three sources before relying on the totals.<\/p>\n
Set the refresh schedule to match the decisions the dashboard supports. Automated refreshes keep metrics current, rather than relying on last week\u2019s export. Check for mismatched date ranges, duplicate customer records, and unclear metric definitions, all of which can distort revenue or conversion trends. Review the dashboard with its intended users and refine the views they rely on.<\/p>\n
Automated churn, retention, and recurring-revenue calculations<\/h2>\n
Automated calculations show how subscriptions change as customers start, renew, expand, or cancel. Compare customer losses with revenue changes to understand what is driving recurring revenue.<\/p>\n
Churn and Retention Measures<\/h3>\n
Logo churn counts customers who cancel during a period. Gross revenue churn measures recurring revenue lost through cancellations and contraction. Net revenue retention starts with recurring revenue from existing customers, adds expansion, and accounts for losses. A retention dashboard that tracks cancellations, contractions, expansions, and MRR helps teams distinguish lost accounts from reduced subscription value.<\/p>\n
Keep the period and customer group consistent for each measure. For example, compare the same starting cohort across periods instead of mixing new subscriptions with established accounts. This makes churn and retention trends easier to interpret, while keeping acquisition activity visible as a separate source of growth.<\/p>\n
Churn, MRR, ARR, and Subscriber Tracking<\/h3>\n
Use charts to compare churn, MRR, and ARR over matching periods. MRR captures monthly subscription revenue; ARR expresses MRR on an annualized basis. Subscriber counts add context: a stable revenue line could hide cancellations offset by expansion from remaining accounts. Review revenue, subscriber counts, and churn together to determine whether changes came from new accounts, renewals, or existing customers.<\/p>\n
Separate opportunities into new subscriptions, renewals, expansion, and churn risks. Record the account, current status, and expected revenue change for each. Then compare actual results with the opportunity view to see which changes delivered recurring revenue and which remained projections.<\/p>\n
For consistent calculations, one example model normalizes active subscriptions at month-end, divides annual contracts by 12, and excludes one-off fees. It records discounted contracts at the amount customers actually pay. Clear definitions help teams monitor trends without confusing billing adjustments with subscription performance. Use charts to visualize recurring-revenue trends<\/a> across these measures.<\/p>\n<\/p>\n
<\/div>\n<\/p>\n
MRR and net new MRR tracking<\/h2>\n
Monthly recurring revenue (MRR) gives teams a consistent view of subscription income. Net new MRR explains how that total changed, separating new business from changes in existing accounts. Track the two together: MRR shows the current position, while net new MRR reveals the movement behind it.<\/p>\n
Calculate net new MRR from four components: new subscriptions, expansion, contraction, and churn. Add MRR from new accounts and upgrades, then subtract revenue reductions and cancellations. The result shows whether growth came from acquisition or existing customers. It also helps teams investigate whether a decline reflects lost subscribers or smaller subscriptions.<\/p>\n
For example, an illustrative company recorded $714,209 in MRR in October 2024. In September 2026, its MRR was $1,209,761. Those snapshots show the recurring-revenue totals for each month; a net new MRR view would reveal the additions and losses between them. Avoid reading the totals alone as a complete account of growth.<\/p>\n
ARR offers an annualized view for planning, while MRR supports month-to-month analytics. In October 2024, the example company reported $8.6 million in ARR and 493 customers. Comparing customer count with revenue helps reveal whether account growth and recurring income are moving together. Keep the reporting period and underlying customer group consistent to make those trends meaningful.<\/p>\n
For reliable SaaS metrics tracking, define how billing changes appear in the numbers before comparing periods. A native integration can bring subscription and customer records into one reporting flow. A spreadsheet import can also work if teams map fields consistently. Match customer identifiers across billing and CRM records, then check unusual changes against account activity.<\/p>\n
Display MRR, net new MRR, ARR, and subscriber counts side by side. Add lifetime customer context when it supports a decision, but keep it distinct from current-period revenue. This layout helps founders and finance teams identify whether a change came from acquisition, expansion, contraction, or churn, then focus follow-up analysis on the relevant accounts.<\/p>\n
Core SaaS dashboard metrics and KPI definitions<\/h2>\n
A useful KPI dashboard clarifies each measure before teams act on it. Define the time period, customer group, and calculation behind every metric, then compare like with like. Monthly reporting shows operating changes, while annual views support broader planning. Consistent definitions across reports matter more than the platform.<\/p>\n
Use these core definitions to connect acquisition, customer value, and revenue performance:<\/p>\n
\n- Churn rate:<\/strong> the percentage of customers who cancel during a given period. Compare the same customer group and period to interpret changes.<\/li>\n
- Customer retention rate:<\/strong> the percentage of customers kept over a given period. Read it beside churn to understand customer movement.<\/li>\n
- Lifetime value (LTV):<\/strong> estimated net revenue a customer generates over the full length of their relationship with a business.<\/li>\n
- LTV:CAC ratio:<\/strong> compares lifetime value with customer acquisition cost. Use consistent customer and cost definitions for a meaningful comparison.<\/li>\n
- Average revenue per user (ARPU):<\/strong> total revenue divided by the number of customers. State which revenue period the calculation uses.<\/li>\n<\/ul>\n
Conversion metrics add context to these measures. Trial-to-paid conversion shows how effectively trials become paid subscriptions; customer acquisition cost is the average cost of acquiring a new customer, including marketing and sales spend. Read them together to assess acquisition quality, not just signup volume. For instance, rising signups alongside weaker conversion can change how teams interpret acquisition activity.<\/p>\n
Benchmarks provide context, not automatic targets. According to High Alpha\u2019s 2025 benchmarks, SaaS companies with $5 million to $20 million ARR had median growth of 31%, net revenue retention of 103%, and software gross margin of 80%. SaaS Capital\u2019s 2025 retention study found median net revenue retention of 101% among private B2B SaaS companies. The populations differ, so keep each benchmark\u2019s scope visible.<\/p>\n
What’s Inside the SaaS Metrics Dashboard Template?<\/h2>\n
A useful dashboard connects revenue, customer, engagement, and conversion measures. Start by deciding which questions and decisions the metrics need to support.<\/p>\n
Revenue and Conversion Metrics<\/h3>\n
Break ARR down by customer, territory, and revenue stream to see where recurring revenue is concentrated. Compare trial-to-paid conversion with customer acquisition cost (CAC), the average cost of acquiring a new customer, including marketing and sales spend. If conversion falls as CAC rises, for example, review both acquisition spending and trial performance. Include customer and engagement measures to help explain revenue and retention changes, rather than reporting totals alone.<\/p>\n
Dashboard Formats and Billing Views<\/h3>\n
Choose a Looker Studio, Tableau, or Power BI template based on its data connections and intended users. A hosted dashboard offers a ready-made environment, while a custom dashboard can reflect specific reporting needs. Template prices vary by format, features, and functionality, so compare what each includes rather than relying on a headline price. Spreadsheet-template libraries also offer free Excel or Google Sheets options. Check which metrics are included before using one.<\/p>\n
Keep customer-facing billing screens separate from internal finance dashboards. Customers need clear charges and subscription details. Internal teams may need revenue by customer, territory, and stream, along with contraction and account trends.<\/p>\n
Data Connections and Dashboard Setup<\/h3>\n
Build the dashboard in stages. Define each metric, connect billing records to subscription revenue, then align product analytics events with CRM customer records. Use consistent customer identifiers so trial, paid account, and product activity all point to the same account. Map event names to the features or actions they measure, then test a sample account across all three sources before relying on the totals.<\/p>\n
Set the refresh schedule to match the decisions the dashboard supports. Automated refreshes keep metrics current, rather than relying on last week\u2019s export. Check for mismatched date ranges, duplicate customer records, and unclear metric definitions, all of which can distort revenue or conversion trends. Review the dashboard with its intended users and refine the views they rely on.<\/p>\n
Automated churn, retention, and recurring-revenue calculations<\/h2>\n
Automated calculations show how subscriptions change as customers start, renew, expand, or cancel. Compare customer losses with revenue changes to understand what is driving recurring revenue.<\/p>\n
Churn and Retention Measures<\/h3>\n
Logo churn counts customers who cancel during a period. Gross revenue churn measures recurring revenue lost through cancellations and contraction. Net revenue retention starts with recurring revenue from existing customers, adds expansion, and accounts for losses. A retention dashboard that tracks cancellations, contractions, expansions, and MRR helps teams distinguish lost accounts from reduced subscription value.<\/p>\n
Keep the period and customer group consistent for each measure. For example, compare the same starting cohort across periods instead of mixing new subscriptions with established accounts. This makes churn and retention trends easier to interpret, while keeping acquisition activity visible as a separate source of growth.<\/p>\n
Churn, MRR, ARR, and Subscriber Tracking<\/h3>\n
Use charts to compare churn, MRR, and ARR over matching periods. MRR captures monthly subscription revenue; ARR expresses MRR on an annualized basis. Subscriber counts add context: a stable revenue line could hide cancellations offset by expansion from remaining accounts. Review revenue, subscriber counts, and churn together to determine whether changes came from new accounts, renewals, or existing customers.<\/p>\n
Separate opportunities into new subscriptions, renewals, expansion, and churn risks. Record the account, current status, and expected revenue change for each. Then compare actual results with the opportunity view to see which changes delivered recurring revenue and which remained projections.<\/p>\n
For consistent calculations, one example model normalizes active subscriptions at month-end, divides annual contracts by 12, and excludes one-off fees. It records discounted contracts at the amount customers actually pay. Clear definitions help teams monitor trends without confusing billing adjustments with subscription performance. Use charts to visualize recurring-revenue trends<\/a> across these measures.<\/p>\n <\/p>\n <\/p>\n Monthly recurring revenue (MRR) gives teams a consistent view of subscription income. Net new MRR explains how that total changed, separating new business from changes in existing accounts. Track the two together: MRR shows the current position, while net new MRR reveals the movement behind it.<\/p>\n Calculate net new MRR from four components: new subscriptions, expansion, contraction, and churn. Add MRR from new accounts and upgrades, then subtract revenue reductions and cancellations. The result shows whether growth came from acquisition or existing customers. It also helps teams investigate whether a decline reflects lost subscribers or smaller subscriptions.<\/p>\n For example, an illustrative company recorded $714,209 in MRR in October 2024. In September 2026, its MRR was $1,209,761. Those snapshots show the recurring-revenue totals for each month; a net new MRR view would reveal the additions and losses between them. Avoid reading the totals alone as a complete account of growth.<\/p>\n ARR offers an annualized view for planning, while MRR supports month-to-month analytics. In October 2024, the example company reported $8.6 million in ARR and 493 customers. Comparing customer count with revenue helps reveal whether account growth and recurring income are moving together. Keep the reporting period and underlying customer group consistent to make those trends meaningful.<\/p>\n For reliable SaaS metrics tracking, define how billing changes appear in the numbers before comparing periods. A native integration can bring subscription and customer records into one reporting flow. A spreadsheet import can also work if teams map fields consistently. Match customer identifiers across billing and CRM records, then check unusual changes against account activity.<\/p>\n Display MRR, net new MRR, ARR, and subscriber counts side by side. Add lifetime customer context when it supports a decision, but keep it distinct from current-period revenue. This layout helps founders and finance teams identify whether a change came from acquisition, expansion, contraction, or churn, then focus follow-up analysis on the relevant accounts.<\/p>\n A useful KPI dashboard clarifies each measure before teams act on it. Define the time period, customer group, and calculation behind every metric, then compare like with like. Monthly reporting shows operating changes, while annual views support broader planning. Consistent definitions across reports matter more than the platform.<\/p>\n Use these core definitions to connect acquisition, customer value, and revenue performance:<\/p>\n Conversion metrics add context to these measures. Trial-to-paid conversion shows how effectively trials become paid subscriptions; customer acquisition cost is the average cost of acquiring a new customer, including marketing and sales spend. Read them together to assess acquisition quality, not just signup volume. For instance, rising signups alongside weaker conversion can change how teams interpret acquisition activity.<\/p>\n Benchmarks provide context, not automatic targets. According to High Alpha\u2019s 2025 benchmarks, SaaS companies with $5 million to $20 million ARR had median growth of 31%, net revenue retention of 103%, and software gross margin of 80%. SaaS Capital\u2019s 2025 retention study found median net revenue retention of 101% among private B2B SaaS companies. The populations differ, so keep each benchmark\u2019s scope visible.<\/p>\n<\/div>\nMRR and net new MRR tracking<\/h2>\n
Core SaaS dashboard metrics and KPI definitions<\/h2>\n
\n