RevOps Analyst at a Series C startup
Build a daily pipeline pacing chart, created vs won across quarters
1. Trust
A single source of truth for the entire team.
Same question? Same answer.
equals.app
B9 Enter formula
A
B
C
D
E
F
G
H
1
Build Summary
2
3
ARR
May 2026
Jun 2026
Jul 2026
Aug 2026
4
Gross new
$197,402
$214,560
$237,402
$261,048
5
Expansion
$84,895
$96,220
$110,220
$124,600
6
Restart
$16,580
$21,240
$23,280
$26,540
7
Contraction
($23,702)
($22,569)
($25,874)
($24,180)
8
Churn
($88,640)
($84,405)
($92,820)
($97,405)
9
Net new
$186,535
$225,046
$252,208
$290,603
10
End of month
$3,197,027
$3,422,073
$3,674,281
$3,964,884
11
MoM growth
6.2%
7.0%
7.4%
7.9%
12
13
Customers
14
Gross new
36
41
45
52
15
Restart
9
6
12
9
16
Churned
(21)
(18)
(24)
(21)
17
Net new
24
29
33
40
18
End of month
537
566
599
639
19
MoM growth
4.7%
5.4%
5.8%
6.7%
20
21
22
23
24
A
B
C
D
E
F
G
H
1
Segment Breakdown
2
3
Segment
Net new ARR
% of total
4
Sales
$293,651
101.0%
5
Self-serve
($3,048)
-1.0%
6
Total
$290,603
100.0%
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Dashboard
Build Summary (Monthly)
Segment Breakdown
Build Summary (Weekly)
Build Components (Charts)
ARR Data (Day)
ARR Data
Leads
This workbook is a canonical source of truth for your team.
Approved by
Tony
Approval date
October 2025
Net New ARR analysis
What was our net new ARR last month?
Thought for 4s
Searched trusted workbooks
Queried ARR Build Analytics
Your net new ARR for August 2026 was $290,603 — the strongest month in the workbook, driven by expansion rather than new logos.
Breakdown by segment
Thought for 5s
Queried ARR Build Analytics
Added a Segment Breakdown sheet
Wrote the segment table
Split by segment for August 2026:
- Sales: $293,651
- Self-serve: -$3,048
- Total: $290,603
Sales carried the month; self-serve gave a little back through contraction rather than churn.
2. Build
Understand your pipeline, ARR, engagement, and more.
Build once, iterate for years.
Head of RevOps at an AI company
Which customers are dragging our AI margin into the red?
Founder at a Series A startup
Build a weekly ARR dashboard with the key metrics for our GTM meeting
3. Deploy
Wire your numbers into how your company operates.
A system, not an artifact.
Equals APP 7:00 AM
Here’s your daily Sales Pipeline overview.
Quarter-to-date
Opportunities
1,016
+14.5%
Won ($)
$2,560,520
+12.3%
Pipeline created
Eventually won Eventually lost Still open
$40M $30M $20M $10M $0
$9M
$12M
$14M
$17M
$19M
$22M
$28M
$30M
$37M
2023 Q1 2023 Q2 2023 Q3 2023 Q4 2024 Q1 2024 Q2 2024 Q3 2024 Q4 2025 Q1
Creation quarter
Brief your team
Scheduled Slack (or email) push keeps everyone updated in real time, freeing you from last-minute screenshot duty.
Accounts
Account name Account domain Total ARR
Cerved cerved.com $19,250.00
Alteryx alteryx.com $23,500.00
Tableau tableau.com $27,800.00
Databricks databricks.com $35,000.00
Snowflake snowflake.com $45,200.00
Hex hex.com $30,500.00
Domo domo.com $22,400.00
Updated 2 min ago from Equals
Update your CRM
Fix input errors, add missing details, and push calculated values into your CRM from Equals.
Bloom
AI Usage Analytics
Ask
AI Gross Margin
54.2%
+2.1pp MoM
Inference cost
$184k
+2.4% MoM
Cost per active user
$8.40
93% out of target ($9.00)
Cache hit rate
71%
+6pts from previous month
Feature usage
Calls (#) Cost ($)
How does the margin look like per customer?
Worked for 5s
4 customers are operating below 0% margin. Combined, $14.2k MRR generating $19.8k in inference cost. Estimated $66k annual margin drag if unaddressed.
Customer MRR Inference Margin
Halcyon $2,400 $6,820 -184%
Northwind $1,600 $4,310 -169%
Meridian $4,400 $5,940 -35%
Cedar & Finch $1,800 $2,090 -16%
See all
Would you like to investigate usage for these customers in more detail?
Ask dashboard
Ask follow-up questions on any dashboard and get answers backed by the same trusted spreadsheet logic.
Pipeline creation has grown from $9M to $37M since 2023 Q1, with $17M still open.
Pipeline created
Eventually won Eventually lost Still open
$40M $30M $20M $10M $0
$9M
$12M
$14M
$17M
$19M
$22M
$28M
$30M
$37M
2023 Q1 2023 Q2 2023 Q3 2023 Q4 2024 Q1 2024 Q2 2024 Q3 2024 Q4 2025 Q1
Creation quarter
Embed in Notion
Drop live charts and tables into Notion, Coda, or any wiki—always in sync with the source.
Records Methodology
Data from 2 hr ago
Pulled Salesforce opportunity records into Opportunities sheet Sourced from the Salesforce Equals Production connector via the opportunities_clean view.
Built Days in Stage detail rows joining opportunity and stage data Combines opportunity IDs, stage names, and days-in-stage metrics into one row per opportunity/stage.
Counted unique opportunities reaching “7_Closed Won” per month For each monthly column, counts distinct opportunities whose stage matches “7_Closed Won” and whose days-in-stage value meets or exceeds the threshold from column C.
Summed the monthly counts into the quarter-to-date total Adds the quarter’s columns in row 13 to produce the 85 Closed Won opportunities shown, and the same window a quarter back for the comparison.
Verify any number
Click into any figure to see the formula behind it and the query it came from—all the way back to the source row.
Q1 pipeline review
How much pipeline did we create this quarter?
Thought for 4s
Searched trusted workbooks
Queried Pipeline Analytics
$37M in 2025 Q1 — up 23.3% on last quarter’s $30M, and the strongest quarter in the workbook.
Which segments drove the increase?
Analyze with agents
Any agent connects over MCP to analyze the metrics your team trusts—not numbers it invented.
4. Foundations
Equals syncs your team’s tools to a managed warehouse.
No data stack or team required.
AI
Build dashboards and models. Answer questions about your business.
Spreadsheet
A calculation layer that’s easy to audit, trust, and collaborate on.
Warehouse
All your GTM data synced and cleaned in a Snowflake instance we run for you.
AI
Build dashboards and models. Answer questions about your business.
Spreadsheet
A calculation layer that’s easy to audit, trust, and collaborate on.
Warehouse
All your GTM data synced and cleaned in a Snowflake instance we run for you.
5. Testimonials
How serious teams use AI to deliver trusted answers to their companies.
“You guys cooked with this one. This is better for viewing data than anything Salesforce has built—it answers real business questions and makes the data easy to act on.”
Connor Nowinski
VP Finance, 11x
“Questions like ‘pipeline by AE and deal type’ used to mean long Slack threads. Now I ask a question and get an answer in minutes—no SQL, no back-and-forth.”
Joe Ryan
CRO, Expo
“Equals cut our data preparation and analysis time by over 90%, shifting our team’s focus from data wrangling to insights and strategy.”
Dean Anderson
Strategy + Ops, Thanx
“A big part of my job is fielding daily data requests. What used to take an hour now takes about 10 minutes, and all I need to do is give Equals a few clarifying prompts.”
Katie Taylor-Kramme
Operations, Atticus
Stop vibe-coding your numbers.
Start trusting them.
