They say they have an algorithm that can detect owner bookings and pull those out but I am skeptical of how well that could really work.The advantage is that they offer data for the whole year so you can see seasonality instead of having to completely guess how things will look in summer based on winter bookings, and they have multiple years of data so you can see what things look like in a normal year.In the end I think it's important to look at both AirDNA and calendars. 

I figured I would ask a bit more about what they have to offer, and she replied:"I pulled your property on our pricing algorithm and it looks like it would make an annual revenue of $26,157 with an average daily rate of $154, and an occupancy rate of 47%.

Hey @Steve Miklashevskiy, like any algorithm, outliers will skew results.

For entry level investors it can be tough to find properties that are listed before they get picked up by institutional investors with sophisticated tools and algorithms. 

The algorithms have a hard time taking into account renovations as you mentioned.

I’ve seen quite a few websites that haven’t invested in SEO, but are still ranking high for specific keywords and getting traffic because they’re consistently putting out high quality content.This is absolutely something you can do yourself - it just takes a while to really learn the basics of SEO, and then a little while longer to get up to date with best practices because almost every training resource will be out of date (Google updates their algorithm SO frequently).

I asked my insurance agent how filing a claim would affect my rate and she was completely useless, basically saying that nobody knows how my rate would be affected because it is determined by a computerized algorithm.

Which BTW might not be the worst idea, if you have a cookie cutter property on a street that is fairly uniform the algorithm is often pretty good.Part two is the appraisals on cash out refi's are typically VERY conservative.

Computer algorithms can't measure that.

This is a direct quote from PRnewswire: ‘The complaint filed alleges that, throughout the Class Period, Defendants failed to disclose to investors that: (1) the algorithm used by the Company to make offers for homes could not accurately adjust to changing house prices across different market conditions and economic cycles; (2) as a result, the Company was at an increased risk of sustaining significant and repeated losses due to residential real estate pricing fluctuations; (3) accordingly, Defendants overstated the purported benefits and competitive advantages of the algorithm; and (5) as a result, Defendants' positive statements about the Company's business, operations, and prospects were materially misleading and/or lacked a reasonable basis at all relevant times.’