General Real Estate Investing
Market News & Data
General Info
Real Estate Strategies
Landlording & Rental Properties
Real Estate Professionals
Financial, Tax, & Legal
Real Estate Classifieds
Reviews & Feedback
Updated about 5 years ago, 10/11/2019
Odds of Getting Low Ball Offers Accepted
Above is a chart summarizing all transaction history of:
- Properties sold in the MLS
- From 1997 through part of 2019
- Detached single family homes (no condos, townhomes or multi-family)
- Summarizing 6 different cities of data
It shows you a proxy for what the odds are of getting an above asking price, at asking price or "low ball" offer accepted and having it close based on actual data.
Of course, the specific property matters a lot, but this is a summary of all the data.
For example, in the chart above, only about 2.46% of all closed transactions we for 90% of list price or lower (in other words... you were able to get a 10% discount from list price even after the inspection and appraisal negotiations).
That's more than I thought it would be in all honesty but I suppose it depends on the price point too. big difference in 10% on a $100k home and 10% on a $500k home
@Aaron K. I did break this same data out by price range and, separately, for days on market for a blog post I wrote too. You're more likely to be able to get a lower offer accepted on higher priced stuff and stuff that has been sitting on the market longer (as I think many people would have expected).
Really lower offers on higher priced stuff surprises me I would have thought that $50k on a $500k home would be much harder to convince a seller of.
@Aaron K. I just sent you the blog post I am working on that that has the breakout by price band (and days on market) as well to show you how you are more likely to get a discount on higher priced stuff.
But, here's even a different chart (not included in the blog post that I just private messaged you) showing both the average discount and the median discount for just the last 12 months in just one real estate market (Fort Collins, Colorado) broken out by price band.
I wish there was another real estate agent or real estate investor in some of the other popular investor markets like Atlanta, Memphis, Detroit, Jacksonville, Miami, Dallas, Houston, Tampa, Orlando, Kansas City, etc that have similar data so we can see a wider range of what a "low ball" offer (inside the MLS) means in these other markets.
@James Orr I just closed on a property around 9% below MLS. This was also after a couple months of the price being lowered 2 or 3 times. Just outside Orlando. Nothing special here too. I sent out about 15 lowball offers in total and closed on this one. This is a major rehab though as well as sat on the market a couple months. That might skew the data. Like you said would be interesting to have that chart.
You may be misrepresenting low ball offers. The data you show is for all settlement prices, not offers, and does not appear to focus on low ball offers. I think it is reasonable to assume the original offers were lower than the settlement prices for a significant portion of your data set. You might want to adjust your theme of odds of getting low ball offers accepted to be more focused on settlement prices relative to asking prices.
Similarly, your story could be titled around the theme of the effect of asking for a higher price as the same data appears to support an analysis across the pricing spectrum. Further stratification by property type could also provide insights.
I think your story shows your leading theme better if you were able to show the original offer, settlement price and asking price. That would allow for analysis of how far off the original offer was from the asking price to see where they settled. I don't know of the MLS capturing offer data though.
@James Orr I sit for the state test today and will be joining a brokerage later this week. Send me a message of what info you are looking for and I will see what I can put together for you.
- Tyler Gibson
- [email protected]
- 407-590-9858
Is the data based on original list price (especially if it was listed higher, sat on market a long time, expired or withdrawn and re-listed at a lower price) versus sale price, or list price at time of contract versus sale price? Many homes that sell significantly lower than original list price go through 2-3 price reductions and several new listings before going under contract. They would appear they sold much closer to list price if you're using the list price after the reductions rather than original list price. I've seen firsthand where a home listed over $500K, sat on market for months, expired, relisted $475K, sat on market again, finally took a $425K offer, but listing firm withdrew old listing, then listed it as a New listing, $425K before accepting offer so it showed a full price sale, 2-3 days on market, when in fact it was sold at 85% of original list price after over 6 months on market. Not sure how your data accounts for those sales, and that is not an isolated case, just the latest one I'm aware of.
@Tim Bradley You wrote:
> @James Orr I just closed on a property around 9% below MLS.
Yes... we do see these in the data. They are just a small percentage of the transactions. The data shows how rare they are.
> This was also after a couple months of the price being lowered 2 or 3 times.
Yes, this data shows the discount/premium from the last list price (not the initial list price). I should also stress that list price does not automatically mean value (ARV). It could be listed way above ARV or way below to start.
> Just outside Orlando. Nothing special here too.
Thanks for sharing that.
> I sent out about 15 lowball offers in total and closed on this one.
How low where the others? And did you hand select ones that you thought might be more likely to accept?
> This is a major rehab though as well as sat on the market a couple months.
Yes, I did some other data analysis and studies that show you are more likely to get a lower offer accepted on properties that have been sitting.
> That might skew the data.
Yes. Definitely helps you get the lower offers accepted.
> Like you said would be interesting to have that chart.
Yes.
@James Mc Ree You wrote:
> You may be misrepresenting low ball offers.
As I said... it is a proxy. It shows the discount/premium of sold price compared to the last list price. Since offer prices are not published, this is the closest proxy we have for offer price.
> The data you show is for all settlement prices, not offers, and does not appear to focus on low ball offers.
Yes it shows settlement price (not offers) and it shows the entire data set. Part of that is low ball offers.
> I think it is reasonable to assume the original offers were lower than the settlement prices for a significant portion of your data set.
I would challenge that assumption. Having done hundreds of transactions personally... I recall just one where the price went up... most (and especially on distressed properties) the price is likely to go down during the inspection and appraisal negotiation.
Any other real estate brokers will large transaction histories seen a large percentage of their transactions close at a price that is higher than their offer price?
> You might want to adjust your theme of odds of getting low ball offers accepted to be more focused on settlement prices relative to asking prices.
It is settlement prices relative to asking prices, but my assumption is that these are highly correlated proxies of offer prices.
> Similarly, your story could be titled around the theme of the effect of asking for a higher price as the same data appears to support an analysis across the pricing spectrum.
Yes, the same data set suggests that you don't get all of your "full price" offers accepted.
> Further stratification by property type could also provide insights.
I have broken it out by price band and days on market already. I did a quick breakout of multi-family as well. I have not done a detailed break down of property type.
> I think your story shows your leading theme better if you were able to show the original offer, settlement price and asking price.
If only I had offer price. It is unpublished data. I only have list price and settlement price.
> That would allow for analysis of how far off the original offer was from the asking price to see where they settled. I don't know of the MLS capturing offer data though.
Yes. Agreed.
@Tyler Gibson You wrote:
> I sit for the state test today and will be joining a brokerage later this week. Send me a message of what info you are looking for and I will see what I can put together for you.
For this analysis, you just need to have sold price and list price to do similar analysis in Excel. If you happen to have that data, you could run it for your area and post the results to see how it compares.
@Lynn McGeein you wrote:
> Is the data based on original list price
Nope. It is the last list price prior to sale.
> (especially if it was listed higher, sat on market a long time, expired or withdrawn and re-listed at a lower price) versus sale price,
It already takes into account price drops. It would ignore all expired and withdrawn listings... as it only looks at ones that sold. If it got relisted then sold, it would use the last list price and the sold price for that transaction.
> or list price at time of contract versus sale price?
It is technically not even list price at time of contract... it is last list price.
> Many homes that sell significantly lower than original list price go through 2-3 price reductions
Yes... this is sold price/last list price.
It is important to re-emphasize that list price is not value (ARV). It is just what the seller and their representation listed the property at for sale. ARV could be higher or lower.
> and several new listings before going under contract.
Yes. Totally true.
> They would appear they sold much closer to list price if you're using the list price after the reductions rather than original list price.
Which I am... I am using the last list price... not the original list price.
> I've seen firsthand where a home listed over $500K, sat on market for months, expired, relisted $475K, sat on market again, finally took a $425K offer, but listing firm withdrew old listing, then listed it as a New listing, $425K before accepting offer so it showed a full price sale,
Yes. In that case, that would have shown as a $425K list price and a $425K sale price and would be in the 100% pile.
> 2-3 days on market, when in fact it was sold at 85% of original list price after over 6 months on market.
Yes. The data I am showing would not show it based on its original, fantasy-land list price in the previous listing. This is a better proxy for can you "low ball" based on the current list price (not what it was listed at before).
> Not sure how your data accounts for those sales, and that is not an isolated case, just the latest one I'm aware of.
I do see those too, but... and this is completely anecdotal... I don't think they're anywhere near 10% of the total market. My guess is maybe 1 in 25 or less where that happens. I don't have original list price and I especially don't have original list price for "recent" listings that would catch relisting properties. If I did, I could break those out as well.
You can't randomly offer. I would say 7 out of 10 of our, very low, offers are accepted. But we know exactly what kind of houses to target and where. Definitely art and a science to it.
Yes. Makes sense to me.
I believe the term is a "seller market".
While I can not quantify it and do not respond to these people. I regularly see investors trying to make offers that are below what someone else paid years ago on properties that are not distressed and in some cases have been improved. I have gotten offers on properties the first day of listing for 30% less than asking. If the property is on the market 90+ days, then it is somewhat more likely to go at a discount.
Thanks @Lesley Resnick. The data I shared above includes strong sellers markets AND the great depression period that was a buyer's market. So, it does include both.