Categories: Market Research

Auto Collision Estimating Software Market Research, Analysis, Growth, Trends, Developments And Forecast 2033

Overview and Scope
Auto collision estimating software is a specialized computer program used by professionals in the automotive repair industry to estimate the cost of repairs for vehicles involved in collisions or accidents. The software solutions typically incorporate databases of parts, labor costs, and repair procedures, allowing estimators to input details about the damage to a vehicle and generate accurate repair estimates quickly.Sizing and Forecast
The auto collision estimating software market size has grown rapidly in recent years. It will grow from $2.06 billion in 2023 to $2.33 billion in 2024 at a compound annual growth rate (CAGR) of 12.9%.  The growth in the historic period can be attributed to increased collision rates, stringent regulatory compliance, growing complexity in vehicle technology, rising consumer expectations, insurance industry evolution.
To access more details regarding this report, visit the link:
https://www.thebusinessresearchcompany.com/report/auto-collision-estimating-software-global-market-reportSegmentation & Regional Insights
The auto collision estimating software market covered in this report is segmented –
1) By Type: Cloud-based Auto Collision Estimating Software, On-premise Auto Collision Estimating Software
2) By Deployment Model: SaaS (Software as a Service), Traditional Software
3) By Application: Small and Medium Enterprises (SMEs), Large Enterprises
4) By End-users: Independent Auto Repair Shops, Dealerships, Fleet Management Companies, Insurance Companies

North America was the largest region in the auto collision estimation software market in 2023. The regions covered in the auto collision estimating software market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

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Major Driver Impacting Market Growth
The increase in road accidents is expected to propel the growth of the auto collision estimating software market going forward. Road accidents, or traffic accidents, refer to incidents involving vehicles, pedestrians, cyclists, or other road users on public roads or highways that result in damage, injury, or loss of life. Auto collision estimating software is used in the aftermath of road accidents, streamlining repairs, claims, and overall efficiency by analyzing photos, vehicle information, and damage details to generate repair estimates quickly and accurately. For instance, in May 2023, according to the Government Digital Service, a UK-based government body, the number of fatalities on UK roads increased by 8.7% from 1,558 in 2021 to 1,695 in 2022. Therefore, the increase in road accidents is driving the growth of the auto collision estimating software market.

Key Industry Players
Major companies operating in the auto collision estimating software market report are Intuit Inc., Snap-On Inc., ABRA Auto Body & Glass LP, Solera Holdings Inc., CCC Intelligent Solutions Inc., Enlyte Group LLC, AudaExplore, Alldata LLC, Shopmonkey Inc., Solera Inc., Auto Data Direct Inc., Comp-Est, Bodyshop Solutions Ltd., Auto Data Solutions Inc., Web-Est , R.O. Writer, MobiTech International Inc., Nexsyis Collision, Bodyshop Booster, DamageiD, Fastrack Autobody Ltd., Audatex , Estify Inc., Repair Shopr, SMART Estimator Ltd.

The auto collision estimating software market report table of contents includes:

1. Executive Summary
2. Auto Collision Estimating Software Market Characteristics
3. Auto Collision Estimating Software Market Trends And Strategies
4. Auto Collision Estimating Software Market – Macro Economic Scenario
5. Global Auto Collision Estimating Software Market Size and Growth
……………
32. Global Auto Collision Estimating Software Market Competitive Benchmarking
33. Global Auto Collision Estimating Software Market Competitive Dashboard
34. Key Mergers And Acquisitions In The Auto Collision Estimating Software Market
35. Auto Collision Estimating Software Market Future Outlook and Potential Analysis
36. Appendix

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