Tipping Measurement Plan - Team Execution Guide

How to track the performance of our new tipping configuration using Square Dashboard. This guide covers weekly data collection, what to calculate, and when to take action.

Overview

We’re tracking 4 metrics weekly for the first month, then monthly ongoing:

1. Tip participation rate - what % of customers tip at all
2. Average tip per ticket - how much we’re earning per transaction
3. Button distribution - which tip option customers select most
4. Customer feedback - any complaints about the tip screen

Step 1: Weekly Data Export (Every Monday)

Pull the Transactions CSV

1. Log in to Square Dashboard at squareup.com/dashboard
2. Go to Reporting > Transactions
3. Set the date range to the previous week (Monday-Sunday)
4. Click the Export button (top right area)
5. Select “Transactions CSV” - this gives the most granular per-transaction data
6. Click the gear icon and select “Export all columns”
7. Click Start Export and save the CSV file
8. Name it with the date range: tips-week-of-YYYY-MM-DD.csv

Pull the Sales Summary

1. Go to Reporting > Reports > Sales Summary
2. Set the same date range
3. Note the Total Tips number shown on this page
4. Take a screenshot or write it down - this is your quick sanity check

Step 2: Calculate Metrics in a Spreadsheet

Open the Transactions CSV in Excel, Google Sheets, or Numbers.

Metric 1: Tip Participation Rate

What it tells you: What percentage of customers are tipping at all.

How to calculate:

1. Find the Tip column in the CSV (may be labeled “Tip Amount” or similar)
2. Count the total number of rows (= total transactions)
3. Count the rows where the Tip column is greater than $0 (= tipped transactions)
4. Participation rate = (tipped transactions / total transactions) x 100

Google Sheets formula (assuming Tip is in column F, data starts row 2, ends row 200):

Total transactions:    =COUNTA(A2:A200)
Tipped transactions:   =COUNTIF(F2:F200,">"&0)
Participation rate:    =COUNTIF(F2:F200,">"&0) / COUNTA(A2:A200)

Format the result as a percentage.

Target: 60%+ Red flag: Below 55% - the configuration may be too aggressive.

Metric 2: Average Tip Per Ticket

What it tells you: Overall tip revenue efficiency across ALL transactions (including non-tippers).

How to calculate:

1. Sum the entire Tip column (= total tip revenue)
2. Count total transactions
3. Avg tip/ticket = total tip revenue / total transactions

Google Sheets formula:

Avg tip/ticket:  =SUM(F2:F200) / COUNTA(A2:A200)

Target: $1.25+ Baseline (old system): $1.03 Projected: ~$1.36

Metric 3: Button Distribution

What it tells you: Which tip button customers select most. This tells us if the anchoring is working.

How to calculate:

1. Filter to only rows where Tip > $0 (tipped transactions only)
2. For under-$10 orders, count how many tips are exactly $1.00, $2.00, and $3.00
3. For over-$10 orders, check if tip amounts cluster around 18%, 20%, or 25% of the sale amount
4. Calculate the percentage of tippers selecting each option

Google Sheets approach for dollar-tier orders:

$1 tips:    =COUNTIF(F2:F200,1)
$2 tips:    =COUNTIF(F2:F200,2)
$3 tips:    =COUNTIF(F2:F200,3)
Custom:     (everything else that's > $0 and not $1/$2/$3)

What to look for: - $2 should be the most popular (45%+ of tippers) - this means the compromise effect is working - If $1 is the most popular (>35%), the anchoring isn’t shifting behavior - consider testing $1/$2/$4 - If $3 is surprisingly popular (>25%), we may have room to raise options further

Metric 4: Customer Feedback

What it tells you: Whether the tipping setup is hurting customer perception.

How to track:

1. Check Google Reviews weekly for any mention of “tip,” “tipping,” “pushy,” or “pressure”
2. Ask the team at the end of each shift: “Did anyone comment on the tipping screen today?”
3. Keep a simple log (even just a note on your phone):

Date       | Feedback                        | Positive/Negative
-----------|---------------------------------|------------------
2026-03-25 | "Customer asked why 25%"        | Negative
2026-03-27 | "Regular said she likes the $2" | Positive

Red flag: 3+ independent negative complaints within 2 weeks.

Step 3: Record in the Tracking Sheet

Create a simple Google Sheet or Excel file with one row per week:

Fill this in every Monday morning using the data from Steps 1-2.

Step 4: Decision Points

After 4 weeks of data, compare against these triggers:

Things are going well

Things need adjustment

Quick Reference: Where to Find Things in Square Dashboard

Optional: Baseline Period

If we want to isolate the impact of the new configuration from the POS migration itself, we can:

1. Set up Square with the OLD settings first ($1/$2/$3 under $8; 12%/15%/18% over $8)
2. Run for 1-2 weeks and collect data using the steps above
3. Switch to the new “Smart Anchor” configuration
4. Compare the two periods

This is optional but gives us cleaner before/after data.

Timeline