Price·Ref

Pricing Decision Support

Operator

Workspace

Mode

Evaluation (buy)

Cars under evaluation · loads attributes into the Buy desk (add new cars on the Evaluations page)

Reference Window

60 days · lookback from latest data

Reference cars seen within the selected window

Listing Status

Price off live listings (asking), sold cars (achieved), or both

Reference Sources

Which marketplaces feed the price reference

Hyperlocal

Local context

Nearer cars rank higher (proximity-weighted); pool stays city-wide so it's never empty

Buy Decision — What should we pay?

Decision-support · Buyer Desk · Real-time

Listings feed live

Refreshed —

Vehicle

Elite i20 · ASTA 1.2

Year

2015

Odometer

72,961 km

Fuel · Transmission

—

Owner

—

Registration

KA05MH1497

Reference set

75 cars · 4 sources

Recommended Max Buy Price

₹5,36,000 · Buy

Green Zone

Decision Zones — Buffer-Based Pricing Logic

Margin floor 8% · 1/3 buffer divisions

Stop · Walk Away

Caution · Negotiate

Buy · Within Margin

₹5,36,000 · Final PP

Floor

₹5,53,000

Yellow / Red

₹5,49,013

Green / Yellow

₹5,45,027

Target PP

₹5,41,040

Start PP

₹5,35,630

Pre-deal \cdot Decision support Post-deal \cdot Captured actuals

Worked example — how each comp is adjusted

click to expand

Market reference — what's selling, where

Raw range/avg · p65/p80 adjusted to subject · 60-day window

click to expand

Own

5 cars

Min₹5,65,000

Avg₹5,95,000

Max₹6,68,000

Days-to-sell38d

Competition

35 cars

Min₹5,00,000

65th pctile₹6,12,000

80th pctile₹6,25,000

Max₹6,95,000

S1

20 cars

Min₹5,00,000

Avg₹6,10,000

Max₹6,85,000

Listing age22d avg

Local Dealer

15 cars

Min₹5,40,000

Avg₹6,00,000

Max₹6,95,000

Days-to-sell31d

Settings · Assumptions

All values editable · re-prices live & saved

Access control

ForgePoint · per-tenant roles

Who can edit, view, or not see each settings feature for this tenant. Platform features default to Super-Admin-only; tenant features to Supervisor-edit, read-only for others.

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Buy parameters

Source: dealer policy

Target margin % — buy planning (of sale price) The margin you aim for when buying. Caps how much you'll pay → Benchmark / Stop PP. Can be higher than the Sell floor (buy with headroom).

Pool low percentile Lower bound — drives Benchmark Buy Price

Pool high percentile Upper bound — drives Stop PP (max buy)

Sell parameters

Source: dealer policy

Minimum margin % — sell floor (of sale price) The margin you won't sell below. Sets the lowest sell price → Stop SP. Can be lower than the Buy target above (accept a thinner deal to move stock).

Benchmark Sell Price uses the same pool high percentile configured under Buy parameters. Single pool drives both sides.

Approvals

Admin · supervisor gate

Require a supervisor passcode before an out-of-limit deal can be recorded — Buy where Final PP > Stop PP, or Sell where Final SP < Stop SP. Evaluators/Sales can't record these without supervisor sign-off.

Require supervisor approvalHard-blocks recording an over-limit deal until the passcode is entered

Supervisor passcodeThe code a supervisor enters to approve an over-limit deal. Change from the default.

Approval audit log · over-limit deals signed off (who / when / why)

Cost defaults

Source: Operator-set

Default refurb cost (₹) Overridden by Evaluator App estimate when available

Default other cost (₹) Transport, RTO, admin overhead

Reference window

Source: Operator-set

Default lookback (days) Starting window for reference data

Min sample size (cars) Below this, window auto-expands

Max auto-expansion (days) Cap; beyond this, manual review

Year window (± yrs) Reference cars filtered within ± this many model-years of the subject

Odometer band (± %) Reference cars filtered within ± this % of subject km

Match falloff (bandwidth) How fast a comp's Match % drops as it gets less similar overall. Match % = 1 / (1 + (distance/this)²), where distance combines trim + year + odometer + proximity. At a distance equal to this value, Match = 50%. Lower = only the very closest comps count (sharper, fewer cars, more volatile p65/p80); higher = more comps blend in (smoother). Affects ALL factors, not just location. Used by the proximity-weighted percentile that sets p65/p80 → Benchmark/Stop.

Audit display cap (N) How many nearest comps to list in the audit table (display only — every matched comp is weighted into the price)

Ranking priority

Higher weight = higher priority

How strongly each factor pulls the comparable set toward the subject. Make & Model are always required (hard filter). Defaults: Trim 12 > Proximity 5 > Year 1 = Odometer 1 = Owner 1.

Trim weightPenalty for a different variant (graded by token overlap)

Year weightPer model-year of difference

Odometer weightPer 10,000 km of difference (capped at 3 units)

Proximity weightMax pull from location (lowest by default — a tiebreaker)

Owner weightPer owner-number of difference (1st vs 2nd…, capped at 3). Skipped when the owner count is unknown on either car.

Same-trim pricingPrice from same-/near-trim comps only; broaden to all trims only when fewer than the Min sample exist. Prevents off-trim cars (which aren't price-adjusted) from biasing p65/p80.

Trim identity matchExclude comps whose variant (e.g. SX vs E) or engine displacement (1.2 vs 1.4) conflicts with the subject. Absent tokens never exclude. Variant vocabulary is editable in trim_config.json.

Fuel matchExclude comps whose fuel (Petrol / Diesel / CNG…) differs from the subject. Blank/unknown fuel is never excluded.

Transmission matchExclude comps whose transmission (Manual vs Automatic; AMT/CVT/DCT count as Automatic) differs from the subject. Blank/unknown is never excluded.

Depreciation table

Source: IRDAI / Industry / OEM

Marginal % drop per year (entered as %). ₹/km coefficient applies after first 30,000 km. Sprint 2 fits these from dealer transaction history.

Segment	Y1	Y2	Y3	Y4	Y5	Y6+	₹/km

Live preview: changes apply to the decision card and worked example as you edit. Static recommendations on the card (Final PP, Margin %, etc.) are placeholders in this mockup — in production they recompute from these settings + live listings data.

How it works · FAQ

Methodology & glossary — reference only

How the zones are set

Buffer logic, not regression

The buy decision band runs from the Benchmark (low end, the 65th percentile of pooled adjusted sell prices minus your margin and costs) to the Stop PP (high end, the 80th percentile minus margin and costs). The gap between them is the buffer, split into thirds: Green safe — buy here; Yellow buy with caution; Red margin at risk — renegotiate or walk. Below Benchmark = excellent buy; above Stop = walk away. The Sell side mirrors it: from Stop SP (your margin floor) up to Benchmark SP (the market reference).

How the reference is adjusted

IRDAI → Industry → OEM → Dealer-fitted

Every comparable car is depreciation-adjusted to the subject's exact age and odometer before pricing, using a layered coefficient table (editable under Settings → Depreciation). Comps are then ranked by closeness — make/model (required) > trim > year > odometer > proximity — and each contributes to the percentile weighted by how close it is, so near, same-spec, recent cars count most.

Glossary

Benchmark / Start PP — the recommended buy price (pooled p65 − margin − costs).

Stop PP — the highest defensible buy price (pooled p80 − margin − costs).

Benchmark SP / Stop SP — sell-side market reference and your margin floor.

Margin — gross % of selling price on both buy and sell sides (consistent basis).

Adj. to subject — a comp's price after depreciation-adjusting to the subject's age/km.

Proximity — distance from the subject's area; nearer comps rank higher (lowest-priority tiebreaker).

Listing status — price off live listings (asking), sold cars (achieved), or both.

Effective N — the proximity-weighted equivalent number of comps behind the price.

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Listing published

Queueing to marketplace channels…

OLX S1 S2 CarWale Own Store