Analytics benchmarks that matter: from days-in-inventory to churn

Mismatched definitions across rooftops (individual dealership locations) are the single biggest reason group-level dashboards mislead.

Inventory velocity: days' supply and days-in-inventory

Days' supply answers: at the current sales rate, how many days until we sell out?

Formula:

Worked example. A dealer holds 300 new units and sold 150 last month (30 days):

Days-in-inventory is different: how long a *specific* car has physically sat on the lot. Days' supply is a forward-looking ratio; days-in-inventory is a backward-looking age. Confusing the two is a classic dashboard error.

Benchmarks (US, as of late 2025, industry estimates): new-vehicle days' supply commonly runs in the 50 to 70 day range for a healthy market, though it swings hard by brand and segment. During the 2021 to 2022 chip shortage it collapsed below 30. European figures are harder to standardize because the market skews toward build-to-order, especially in Germany, so days' supply is a less dominant metric there than in the US stock-heavy model.

Cox Automotive publishes regular US data-drivendata-drivenAn approach where decisions are systematically informed by data analysis rather than intuition alone.View full definition → commentary worth bookmarking: Cox Automotive market insights.

Rule of thumb: below 30 days signals shortage and lost sales; above 90 signals overstock, aging units, and floorplan carrying cost pressure.

Service quality: fixed-first-visit rate

Fixed-first-visit (FFV), also called first-time-fix, measures the share of repair jobs resolved on the first visit without a comeback for the same issue.

Why it matters as data: it is a leading indicator of both customer satisfactioncustomer satisfactionCustomer Satisfaction Score, a direct measure of satisfaction captured right after a specific interaction or experience, usually on a short rating scale.View full definition → and warranty cost. A low FFV means repeat visits, wasted technician hours, and inflated warranty claims that OEMs scrutinize.

The measurement trap: what counts as a "comeback"? If a customer returns in 7 days it is clearly a repeat. At 30 days it may be a new fault. Fix the window in your definition and apply it identically across every rooftop, or your comparison is noise. There is no single public sector benchmark for FFV; targets are usually set internally by OEMs, often in the high 80s to low 90s percent range as an aspirational floor. Treat any external FFV number with suspicion unless the window and scope are stated.

Service retention: keeping the customer in the service bay

Service retention measures how many vehicle owners keep coming back for maintenance rather than defecting to independent shops or chains.

A common definition:

The words "eligible" and "period" carry all the weight. Do you count a 6-year-old car whose owner uses a local independent shop? Rolling 12-month windows are standard. Longer windows flatter the number.

Retention is where the money is. Service and parts generate a large and stable share of dealership gross profit, and a retained service customer is far likelier to buy their next vehicle from you. That is why OEM dashboards track it obsessively.

Data sources to reconcile:

• DMS repair orders (who actually visited).
• OEM warranty and telematics data (who *should* be due for service).
• CRMCRMCustomer Relationship Management: software and strategy to manage and analyse customer interactions throughout their lifecycle.View full definition → (who you contacted).

The gap between "due for service" and "actually visited" is your defection signal.

Customer loyaltyCustomer loyaltyYour customers' propensity to repeatedly purchase from you and resist competitive offers, driven by satisfaction, habit, trust, and switching costs.View full definition →: NPSNPSNet Promoter Score (NPS) measures customer loyalty by asking how likely customers are to recommend a brand, then subtracting detractors from promoters.View full definition → and churn

Net Promoter Score (NPS) asks one question: "How likely are you to recommend us, 0 to 10?" Promoters score 9 to 10, passives 7 to 8, detractors 0 to 6.

Worked example. Of 200 survey responses: 120 promoters (60%), 40 passives (20%), 40 detractors (20%):

NPSNPSNet Promoter Score (NPS) measures customer loyalty by asking how likely customers are to recommend a brand, then subtracting detractors from promoters.View full definition → ranges from -100 to +100. Automotive NPSNPSNet Promoter Score (NPS) measures customer loyalty by asking how likely customers are to recommend a brand, then subtracting detractors from promoters.View full definition → varies widely by brand; premium and EV-native brands often post notably higher scores than mass-market brands, but published cross-brand figures are inconsistent and methodology-dependent, so treat any headline NPSNPSNet Promoter Score (NPS) measures customer loyalty by asking how likely customers are to recommend a brand, then subtracting detractors from promoters.View full definition → as an estimate tied to a specific survey.

Churn is the mirror image, and in automotive it comes in two flavors:

1. Service churn: owner stops using your service bay (visible in DMS gaps).

2. Brand churn (defection): at trade-in or lease-end, the customer switches brands. This is captured in conquest and defection data, often sourced from registration datasets (for example S&P Global Mobility registration data in the US and Europe).

Bringing it together: a benchmark scorecard

The mistake is watching each metric alone. They interact:

• Low FFV drives down service retention (annoyed customers leave).
• Falling service retention predicts higher brand churn at the next purchase.
• NPSNPSNet Promoter Score (NPS) measures customer loyalty by asking how likely customers are to recommend a brand, then subtracting detractors from promoters.View full definition → often trails all of the above by months, so it confirms rather than predicts.

A useful discipline: for every benchmark on your executive dashboard, store three fields alongside the value: source system, definition version, and as-of date. Without those, a green number and a red number are not comparable.

Simple governance snippet for a metric definition registry:

This tiny file is what stops two rooftops from reporting "retention" that means two different things.

Reading benchmarks honestly

Three cautions before you present any of these numbers upward.

Segment before you compare. A pickup truck franchise and a luxury EV showroom have structurally different days' supply and service patterns. Blending them hides the story.

US and Europe differ structurally. The US stock model produces meaningful days' supply figures; much of Europe's build-to-order flow makes that metric less central and less comparable. Do not port a US benchmark onto a German dashboard without adjustment.

Beware survivorship in retention and NPS. Customers who already left do not answer your survey. A rising NPSNPSNet Promoter Score (NPS) measures customer loyalty by asking how likely customers are to recommend a brand, then subtracting detractors from promoters.View full definition → can simply mean your detractors churned out of the sample. Cross-check NPSNPSNet Promoter Score (NPS) measures customer loyalty by asking how likely customers are to recommend a brand, then subtracting detractors from promoters.View full definition → against churn data, never in isolation.

Key takeaways

• Days' supply (around 50 to 70 days is a common US healthy range, late 2025 estimate) is a ratio, not an age. Do not confuse it with days-in-inventory, which measures how long one specific car has sat.
• Fixed-first-visit rate is meaningless without a fixed comeback window. Set the window once, apply it to every rooftop, and store the definition version.
• Service retention is the profit anchor and the earliest defection signal. The gap between "due for service" (OEM data) and "actually visited" (DMS) is your churn early warning.
• NPS confirms, churn predicts. Cross-check NPSNPSNet Promoter Score (NPS) measures customer loyalty by asking how likely customers are to recommend a brand, then subtracting detractors from promoters.View full definition → against registration-based defection data to avoid survivorship bias.
• Every dashboard number needs source, definition version, and as-of date attached, or your cross-location comparisons are noise.