Offer evidence guide
How to use sold prices when making an offer
Sold prices can help you prepare a more evidence-led conversation before making an offer. The goal is not to calculate a perfect offer. The goal is to understand whether the asking price is above, near or below recent local sold-price evidence.
A simple evidence workflow
1. Check the listing location
Start with the full postcode where possible. If evidence is limited, compare the postcode area, town and district.
2. Compare asking price with median
Median sold price is often a better first benchmark than average when local sales include unusual high-value transactions.
3. Inspect transaction depth
A strong sample gives more useful evidence. A low-sample postcode should be treated as a prompt to look wider.
4. Keep caveats visible
Sold-price records do not adjust for condition, bedrooms, extensions, lease terms, plot size or seller urgency.
What to include in your evidence notes
- Location checked: postcode, postcode area, town or district.
- Asking price: the listing price you are comparing.
- Local median and average: include both if available.
- Sample size: transaction count and sample quality.
- Latest data window: UK House Prices currently labels the data window as June 2026.
- Limits: note that the data is historical and not a valuation.
Do not turn sold prices into a false precision offer
A local median can support a question such as whether an asking price is above local sold-price evidence. It should not be presented as a precise amount that someone must offer or accept.
Frequently asked questions
Can sold prices tell me what offer to make?
No. Sold prices provide historical local evidence. They can support a negotiation discussion, but they do not determine the right offer for a specific property.
Should I use postcode, town or district data?
Start as local as possible, then zoom out. A postcode can be useful if the sample is strong; town or district data can add context when postcode evidence is limited.
What should I check before citing sold prices?
Check the median, average, transaction count, latest data date and whether the sample may be affected by unusual or non-standard sales.