No publishable AOV benchmark
Explore category insights and their sources below.
Automotive Parts & Accessories223 / 552
Madgicx Research & Labs
Engine & Mechanical Parts
Diagnosis before parts selection and explicit parts condition.
MADGICX / LABSINDUSTRY RESEARCH
Research only
Scope & method
Within Automotive Parts & Accessories
More in this industry. 7
Questions, answered.AOV, context & using this research7 answers
In this category
Why avoid a one-symptom engine-part claim?
The FTC lists several engine symptoms and recommends diagnosis before repair. A part ad can ask for vehicle and diagnostic details without presenting one generic component as the certain fix.
How can a starter offer avoid overclaiming?
FTC guidance says an apparent starter fault may instead involve a battery or connection. Creative can show a diagnostic sequence and reserve the actual parts recommendation for inspection.
What does a parts-condition label clarify?
The FTC separates new, remanufactured and salvage parts. A listing can state the actual condition and included components, while any fit or warranty terms require the seller’s own evidence.
Why show labor separately from a component?
The FTC says a repair estimate identifies parts and anticipated labor charges. An ad can direct buyers to an itemized quote rather than suggest a component price equals a completed repair.
Category research
Is an AOV benchmark available for this category?
No publishable AOV benchmark is available.
The exact category cohort does not support a publishable AOV aggregate. Parent and sibling benchmarks are not substituted.
Use this research
Can I download this industry research?
The exports section provides this edition in Markdown and JSON, along with a research index. This private draft is not licensed for public redistribution.
How should I cite a finding from this page?
When reuse is permitted, credit Madgicx Research & Labs and link to the exact source. Keep its snapshot date and scope. This private draft is not licensed for public redistribution.
Keep exploring
Connected industries.
Research scope
Small print.
Clear boundaries.
Evidence scope
Benchmark status reviewed 11 October 2026.
The exact category cohort does not support a publishable AOV aggregate.
Median and middle 50% of account-level average order values. Each account value is purchase ROAS multiplied by cost per purchase in USD. Successful classifications, including manual corrections, with positive finite spend, purchases, ROAS and cost per purchase. Accounts are counted once with equal weight. Quartiles use linear interpolation. Root cohorts include direct root classifications and their child categories; exact-child cohorts exclude parent and sibling categories. The source selects the highest-spend coverage row per account among snapshots dated within the preceding 30 days; the underlying reporting period is not supplied. This is a dated aggregate advertising-data snapshot, not business-wide AOV or a census. Parent and sibling benchmarks are never substituted.
Category scope
Individually authored category research. The brand directory is deferred for this private draft. Taxonomy membership does not establish benchmark coverage.
Exports & citation detailsMarkdown · JSON · Embed
When reuse is permitted, credit Madgicx Research & Labs and link to the exact source. Keep its snapshot date and scope. This private draft is not licensed for public redistribution.