Days-On-Market Intelligence

Use time-to-sale automotive market data to refine pricing strategy and prioritize high-turn inventory efficiently. Understand how long vehicles take to sell and act before aging impacts profitability.

The Challenge

Clients lack visibility into which vehicles remain listed too long, impacting cash flow and profitability. Without insight into time-to-sale patterns, inventory issues surface only after costs accumulate. This leads to delayed pricing decisions and inefficient inventory management.

How it works

From listing duration data to inventory decisions

  • Access days on market data

    Collect listing duration, pricing, and activity data using Market Value API, Market Data Feed, and Market Listings API

  • Analyze time to sale patterns

    Evaluate listing age, segment trends, and pricing changes across comparable vehicles

  • Apply inventory prioritization

    Adjust pricing and inventory actions based on time-to-sale performance.

Key capabilities

Core capabilities for analyzing time-to-sale behavior

Days on market tracking

Measure how long vehicles remain active in listings

Time to sale analysis

Evaluate how quickly vehicles convert across segments

Pricing and aging correlation

Link pricing changes to listing duration patterns

Inventory prioritization insight

Identify which vehicles require pricing or merchandising action

Data signals

Key indicators used to evaluate time-to-sale performance

  • Listing age duration

    Length of time vehicles remain actively listed

  • Pricing change timing

    When price adjustments occur during listing lifecycle

  • Market exit events

    Signals indicating vehicle sale or listing removal

  • Segment aging benchmarks

    Expected time to sale across vehicle categories

  • Time-to-sale patterns

    Observed conversion timing across comparable vehicles

Practical Example

A dealership reviews days-on-market trends across compact SUVs and identifies several units exceeding expected time-to-sale despite stable pricing. Based on this insight, the team prioritizes pricing adjustments on aging units while maintaining pricing on faster-moving vehicles, improving turnover without unnecessary discounting.