A hiring pipeline tracker does for recruiting what a CRM does for sales: it shows you where every candidate is, how they're moving through stages, and where you're losing people. Most teams track this in a mix of ATS notes, email threads, and spreadsheets that don't talk to each other. This guide shows you how to build the spreadsheet version properly.
Your Candidate Log
Start with one flat table — one row per candidate per role. Columns: candidate name, role, recruiter, source (LinkedIn, referral, job board, etc.), current stage (Applied, Phone Screen, Interview, Offer, Hired, Rejected), stage date, and notes.
Keep the stage list consistent. Use a dropdown validation so everyone enters the same stage labels. Go to Data, Data validation, List of items, and enter your stages separated by commas. Apply to the Stage column.
Pipeline Summary by Stage
Build a pivot table from your candidate log. Add Stage to Rows, add Candidate Name to Values (set to COUNTA), and add Role to Columns if you want to see pipeline broken down by open position.
This gives you a count of candidates at each stage across all roles, or per role if you use columns. Sort stages manually so they appear in order (Applied, Phone Screen, Interview, Offer, Hired).
Conversion Rates Between Stages
The most useful thing a pipeline tracker can show you is where candidates are falling off. Calculate conversion rates between stages:
=B4/B3
Where B3 is the count at an earlier stage (e.g., Applied) and B4 is the count at the next stage (e.g., Phone Screen). Format as percentage. Build a small table of these ratios next to your pivot table.
If you're converting 80% of phone screens to interviews but only 20% of applications to phone screens, your application-to-screen filter is very tight — which might be intentional or might mean your job descriptions are attracting the wrong candidates.
Time-to-Stage Analysis
Add a Days in Stage column to your candidate log:
=IF(G2="", TODAY()-F2, G2-F2)
Where F2 is the date the candidate entered the current stage and G2 is the date they moved to the next stage (blank if still in current stage). This tells you how long candidates are sitting at each stage.
Average days by stage using AVERAGEIF:
=AVERAGEIF(D:D, "Interview", H:H)
Where D is the Stage column and H is Days in Stage. If interview scheduling is taking 14 days on average, that's a bottleneck worth fixing.
Tracking Source Quality
Add Source to your pivot table rows alongside Stage. This shows you which sources are producing candidates who make it furthest in the process. A source that sends 50 applicants but no hires is costing you screening time. A source that sends 10 applicants and produces 3 hires is worth doubling down on.
The Easy Way: Using SheetXAI in Google Sheets
Example 1: You're building from your existing candidate data.
"I have a candidate log on Sheet 1 with columns for name, role, recruiter, source, stage, and date. Build a pipeline summary showing candidate counts by stage, conversion rates between stages, and average days per stage."
SheetXAI reads your data, builds the stage summary, calculates the conversion rates, and adds the time-in-stage analysis.
Example 2: Your data lives in your ATS.
"Pull open requisition candidates from our ATS and build a hiring pipeline tracker showing candidates by stage and role, with conversion rates and source quality analysis."
SheetXAI connects to your ATS, pulls the pipeline data, and builds the full tracker.
Try SheetXAI free and see what it builds for you.
Published May 2026. See also: How to Build a Headcount Tracker in Excel, How to Build a Sales Pipeline Tracker in Google Sheets, and Google Sheets AI Guide.
