Or you do a screen scrape of Edmunds, as well as all the respective manufactures sites. Compile it all into a searchable database so that you can come to the conclusion that Rick from Ohio got a better Volvo deal than you because…he’s a nurse, who served in the military, recently graduated from college, has a Penfed account, costco membership, attended a ude event and subscribes to equestrian monthly.
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Easier than searching through the forums 
We Americans like to be spoon fed thanks!
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Then go in marketplace grab a broker calculator and raise it up to 13-14% off and start the 2-3 month trek of beating sales reps up until the pass you to the manager and he gives in.
I’m trying not to sound sarcastic, but have you ever seen a consumer retail automotive lease agreement with a non-disclosure clause?
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No. I have not.
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sounds like a load of garbage unless there’s an explicit NDA
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The whole point is that if the current data is inaccurate/invalid, then LH already provides invalid lease deals
The only difference would be that the current invalid data is presented in a thread instead of in a spreadsheet.
I didn’t expect to come back to 70 replies, but I think @mllcb42 nails it here.
Having a database/spreadsheet of deals would be way more accessible and search friendly than having the 
thread of that data (albeit with some nice pictures), valid data or not
Ensuring data validity and upkeep are probably the top issues here, as @michael and @littleviolette mentioned, but again, as Matt mentioned, that doesn’t mean that this database wouldn’t be extremely beneficial to the consumer
Hell, I will be the first one to volunteer as tribute to start converting the current trophy garage manually into a spreadsheet until we get the resources to implement a more efficient process.
More data is always good to me
Keep in mind there are 2 of them and the original one has 2,000 posts 
Plus, Trophy Garage is not about best deals and many posts don’t have all info.
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I gotta ask how would the database be beneficial. What would someone gain from seeing historical leasing data on say a 3 series BMW for example?
Seeing the trend line on things like MF, RV, and even rebates, while not entirely indicative of future numbers, is a good way to gauge whether deals are generally improving, getting worse, or staying flat. I, for example, plotted the BMW MF from the leasing Wiki over the last 3 years and it’s quite helpful to see the graph as compared to numbers on a page:
As a general trend, we can say that the rent charge on any given BMW lease has been declining since 2018, meaning deals have gotten better from a rent charge perspective. Will they continue to get better? Perhaps, but maybe not. This is obviously more difficult with brands that use different MF for individual cars, but I digress…
Take this question that comes up often: “do you think deals will improve? Should I buy this 2020 330 now or wait until Jan 2021?” You could always tell him “no one can see the future get lost🔮” or you could point him to a graph that says “I don’t know what the future programs hold but incentives on most 2020 models have remained level since August and MF is at a three year low so there’s a higher likelihood that deals will get worse or stay the same, not better …make sense?
In my opinion, more data would likely help brokers/dealer in explaining to customers exactly how and why the deal they want you to match from 2 months ago is not replicable, assuming the usual “no thanks” doesn’t suffice to begin with, no?
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As a broker, I would never want to point to historical data to set a false expectations and have someone wait to get a vehicle, especially in my case if they lost lease to lease like we did this month. This proves further it’s a huge time suck, because it’s irrelevant in every interaction, which is why people say…”Your guess is as good as mine”.
If it’s something you want to do have at it but I just see it as a waste when there are far better ways to enhance the site.
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Look I’m just a data guy, and I’m always trying to find ways to use data (messy or not) to help solve problems or improve things. As a general idea, I think compiling more data in a streamlined, organized datable is more valuable than having that data buried in threads. That’s my main basis of support on this idea. I understand the point that you and many other brokers are trying to make, and so I’ll open it back up and see what other have to say about this.
And @Ursus I spent like 20 minutes trying to come up with a clever david-vs-goliath / 300-Battle-of-Thermopylae-esque meme as a response but failed miserably. Wish I was like @RustyDaemon…
Honestly, I think it is way too complex the more you get into it and provides less and less value.
I see what you’re saying and respect the big picture. I believe for the amount of work it would take to make this happen, would not be worth it for the end result. I’m not a data guy, though.
BMW is only one brand. The MF is only one piece of a recipe to make the pie.
If the MF is high but rebates are high and RVs are high, the end result can be better than if the MF were to be low and the rebates and RVs are low.
Also, BMW has the same MF for all models and trims. That’s not the case w Volvo, Lexus, Toyota, Audi…you get where I’m going with this. Some brands use multiple banks. Rebates would be incredibly difficult to track because they’re not broken out in contracts line by line with a description.
The graph you show above is pretty straightforward for BMW, but imagine trending this for another brand that doesnt carry the same MF across the board. Ooooooof
Also, and respectfully, I don’t think it’s relevant…
People who like data like data. But, that graph isn’t really telling us anything about today and now. It’s not indicating whether now is a good time to buy or 3 months from now…
If I need a car, I generally need it now. I’m not shopping for a car today and saying, “OK…based on historical data I’m going to wait 4 months.”
And, if I need a car in 4 months, I’m not going to buy it early because then the “savings” of getting it early are wiped out by 4 additional payments.
At the end of the day, the most beneficial thing for me when shopping a brand I have never shopped for is understanding what is an acceptable % off pre incentive for the car. This is the hardest piece imo to know for a consumer without coming off like a dreamer to a dealer. Today, the only way I know is through past deals or broker sites. This is already very helpful and I am good with the way it is. I just feel with all these nooblets around, having a floating list that shows good/ok/bad % pre incentive on make and models and year would be extremely helpful. Everything else changes month to month generally.
We often say things like 7-11% is broker status, 5-7% is ok, 0 to 3% is poor etc… generalizing of course
Imagine a page these nooblets can go and it lists all the year, make, model and has a general guideline of what tiers of % preincentive is considered unicorn/good/ok/bad. This alone would be beneficial and help a consumer know before any other variable they are receiving something competitive. Of course they will then need to refer to leasing 101 and understand the rest of the variables
And that’s information your never going to know until you step out and chase the deal. It’s pretty simple to see that most brands the goal is 10% if you hit 11-12% expect a MF bump. Subaru in the northeast your never going to see 10% off. So not only will this data need to be done on vehicles but specific regions. I work with big data and the car manufactures keep the dealerships in the dark on all of this…so to think we can trend it is not likely.
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The info you are referring to is based on experience which 90% of these members do not have. What you provided would be valuable and adding by region would be another attribute worth including.
They join ask generalized questions we point them to Edmunds and ask them to start to crawl, they come back with a crazy quote…now we teach them to take the first step…your data is for people who are running. Once your running you don’t need any data outside of what is possible that month. In the time I have been responding to this thread I have helped two people outside this site learn to negotiate a deal in a few simple text messages. Didn’t cost them anything more then the initiative to learn, and push back on the dealer. No graphs, no historical data, only incentives and desire to learn. Give a man a fish feed him for a day, teach him to fish…he won’t ask dumb fishing questions anymore.
The most important number is the discount on the car BEFORE any rebates and incentives, if we can have a historical sheet of each car, then it will much easier for anyone to hack a deal.
To a point.
Once you have quality data (which was my first point), you have to understand a lot about it before you use it for decision support, which is what you are proposing.
Let’s assume I have 3 years of BMW deals, and it’s April of 2020. None of the historical data is going to stay on trend, so you either need to wait for new data, or you have to test your hypothesis in the market.
Otherwise you still get nonsense like
And @mllcb42 will ask what they saw when they searched shared deals and the marketplace (they didn’t).
But we can also suggest they search this new db of deals, that is neither statistically significant nor a representative cross-section (it’s basically the extremes of the range for all US lease deals in a month), and still draw the wrong conclusions.
Nobody wants all the data, they want:
Min(pre-incentive discount), and the deals where you don’t care about the sausage making but the payment is insanely-low to free, which requires a lot more logic.
I think the concept is interesting, but it’s not trivial, it doesn’t have a clear customer who would derive direct benefit in an MVP, assuming you solved for both data volume (enough deals to be useful/meaningful) and data quality.
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