For most dealer groups, collecting Customer Satisfaction Index data is a necessary part of operations. OEMs require it, leadership tracks it, and bonus programs are often tied to it. But the way many dealer groups still collect that data — manually, across multiple brand portals, by hand — is quietly costing them far more than they realize.
The price tag isn’t just time. It’s accuracy, opportunity, and the decisions that never get made because the data arrived too late or too messy to act on.
What Manual CSI Collection Actually Looks Like
Manual CSI collection typically means someone on your team — often a manager or admin — logs into each OEM portal separately, downloads or screenshots scores, and then consolidates everything into a spreadsheet. If your dealer group carries multiple brands, that process gets repeated for every single one.
Then come the questions: Are you comparing the same timeframe across brands? Are the metric definitions consistent? Did someone pull last month’s numbers instead of this month’s? Is the spreadsheet the most current version?
By the time the data is clean enough to share with leadership, days or even weeks may have passed. The window to act on a low score or catch a service issue before it compounds is often already gone.
The Real Costs to Calculate
When dealer groups evaluate manual vs. automated data collection, they tend to undercount the true cost. Here’s a framework for calculating it more honestly:
- Labor hours per week: How many hours does your team spend logging into portals, downloading data, and building reports? Multiply that by your fully loaded hourly cost for whoever is doing it.
- Error correction time: How often does someone catch a discrepancy, trace it back, and fix it? Each correction cycle is untracked labor.
- Reporting lag: How many days pass between when a score is generated and when leadership sees it? Every day of lag is a day decisions are being made without current information.
- Missed recovery windows: When a low CSI score surfaces three weeks after the customer interaction, recovery is nearly impossible. What’s the estimated lifetime value of a customer who churns because no one followed up in time?
- Manager time diverted from coaching: If your service or sales managers are spending hours each month compiling data instead of acting on it, that’s a coaching and performance cost.
Add those up across your full dealer group and the number gets significant quickly.
Why the Problem Compounds Across Multi-Brand Groups
For single-point dealers, manual collection is inconvenient. For dealer groups carrying five, ten, or twenty brands, it becomes operationally unsustainable.
Each OEM structures its satisfaction data differently. Timeframes, metric definitions, scoring scales, and portal interfaces vary from brand to brand. Trying to create an apples-to-apples comparison manually across Ford, Toyota, Honda, and Stellantis brands in the same spreadsheet requires a level of normalization that introduces its own risk of error.
The result is a reporting process that’s both labor-intensive and inherently inconsistent — which means the insights leadership is acting on may not be as reliable as they appear.
What Automation Changes
An automated data aggregation solution like Oxlo’s ASAP eliminates the manual portal-by-portal process entirely. Data is collected, normalized, and delivered in a consistent format across all brands and timeframes — without anyone on your team having to log in, download, or clean anything.
That shifts the work from data collection to data use. Instead of asking “did we pull this month’s numbers yet,” your team is asking “what does this month’s numbers tell us, and what are we doing about it.”
The labor hours come back. The reporting lag disappears. And the recovery windows that manual processes miss become opportunities to actually retain customers.
Calculating Your ROI
If you want a quick estimate of what manual collection is costing your dealer group, start here:
- Count the hours spent per week on portal logins, downloads, and consolidation
- Multiply by your team’s hourly cost
- Estimate how many hours per month go toward error correction and version control
- Identify your average reporting lag in days
- Estimate the number of low scores per month that could trigger a service recovery — and how many of those are acted on in time
The gap between what you’re spending and what you’re getting is your baseline ROI case for automation. For most dealer groups of meaningful scale, it’s not a close call.