What to Measure (Part 2)

10/02/2019 | by Katie Tackett | Market Analysis Real Estate Investments Uncategorized Vacation Rentals
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In part 1 of our series, we talked about the financial metrics in managing real estate.  In this part, we’ll talk about the core metrics that are more specific to the short-term rental market.

 There are two categories of core metrics that are very important in managing your rentals: Marketing and Revenue Management.  You must have a marketing strategy and metrics for managing your spend, but it’s also important to have a strategy on how you’re going to price your nightly rates based on market conditions and availability.



Love ‘em or Hate ‘em, you need the Channels

My personal opinion, not utilizing the channels to drive bookings is short-sighted, regardless of how large your business is or how long you’ve been in business.  The debate of channel independence is a topic of its own, but the important factor here is to understand the metrics you should use in determining the return from your advertising costs.

ROAS: Return on Ad Spend.  Advertising your properties is critical.  Fortunately, there are some simple and low-cost solutions to get you started.  To avoid the dispute over channel independence, I’m going to focus on metrics for measuring marketing performance.  Let’s start with some basic measurements and use those numbers to help guide us on the best methods.

Booking Conversion – it all comes down to getting the booking.  Many elements impact the booking decision, so we want to measure conversions throughout the funnel to determine where and why guests are making their decisions.  These are the four main elements of the booking conversion funnel:

  1. Search Engine Results Page (SERP) – where your property appears in search results
  2. Property Landing Page (PLP)  – the point where a guest lands on your property page
  3. Inquiry – the method a guest contacts you (email / text / phone / chat)
  4. Booking – the transaction that reserves the property

 Methods for obtaining these metrics vary from each channel and your website, but the data is generally available.  Capturing and regularly reporting on the data will require some effort, but the benefits are well worth the time.

 How to interpret the conversion data and what to do with it:

SERP > PLP – indicates the rate at which guests see a picture / description / nightly rate of your property within a search and decide to select your property page.  In general, a high conversion rate indicates adequate quality & price.

     Conversion Performance:

  • Poor Conversion Rate: 2%
  • Average Conversion Rate: 5%
  • Top Conversion Rate: 9%

PLP > Inquiry & Inquiry > Booking – with the popularity of Instant Booking, the volume of inquiries has reduced substantially.  In fact, in our business, these aren’t metrics we measure. Less than 5% of our bookings result from an inquiry. If your business model is built on the inquiry process, these two metrics will be critical

 PLP > Inquiry – indicates the rate at which a guest finds your property meets all of the qualifications and wants to either negotiate terms, validate availability or request a booking.  

     Conversion Performance:

  • Poor Conversion Rate: 5%
  • Average Conversion Rate: 10%
  • Top Conversion Rate: 25%

Inquiry > Booking – indicates the rate the booking is accepted by both the guest and owner/manager.  These rates are expected to be very high. A low rate is an indication a guest misunderstood the conditions or terms.

     Conversion Performance:

  • Poor Conversion Rate: 30%
  • Average Conversion Rate: 50%
  • Top Conversion Rate: 85%+


PLP > Booking – if your business model primarily operates from Instant Booking, this is the primary metric of interest.  The assumption is the guest clearly understands the conditions, terms, rates, and availability of your property. If any of these elements are unclear, the guest is likely to perform an inquiry before booking.  The rate of this metric varies greatly for a few reasons:

  • Unless your property has a very unique characteristic, if your PLP lacks clarity on conditions, terms, rates, and availability, the guest will most likely choose a different property.  In most seasons, there are many properties available and guests won’t exert much effort to inquire on your property…they simply move on.
  • Larger properties (3+ bedrooms) are favorites of large groups.  These groups exert more effort in reviewing properties to ensure it’s suitable for the entire party.  Often the PLP is shared and viewed among multiple members of the party before a booking is made. This would naturally produce a lower conversion rate.

     Conversion Performance:

  • Poor Conversion Rate: 1%
  • Average Conversion Rate: 8%
  • Top Conversion Rate: 25%

 Returning to the topic of ROAS.  Now that you have your booking data it’s important to understand this data and how the cost of advertising applies to each channel.  Just to clear up any confusion, if your website processes bookings it should be considered a channel. The method in which traffic is driven to each channel (SEO, SEM, Email, etc.) is a metric that should also be measured but requires much more explanation than can be covered on this post.

Measuring ROAS: this is a pretty simple concept, but the method will vary depending on the channel and cost factors.  The exercise in calculating ROAS will also expose a pretty interesting metric: cost per booking

ROAS = Booking Revenue / Advertising Cost

Booking Revenue: this should be a simple number for you to capture.  This should not include cleaning and hotel occupancy tax.  Revenue should only relate to nightly rates and additional fees (such as parking, hot tub, etc.)

Advertising Cost: this may be a little more complicated depending on the channel.  Here are some factors to take into consideration:

  • Subscription model: this will likely only be the monthly or yearly cost of the subscription
  • Booking Fee model: this will be the percentage of each booking processed (this booking fee is usually applied to the entire amount, which includes cleaning and taxes).
  • Advertising model: this will likely be the operating costs for directing traffic to your website.  Examples are email, pay-per-click or other forms of advertising.

An example of calculating ROAS (using a subscription model)

  •   Avg Booking Revenue per Door: $36k (avg ~70 bookings per year)
  •   Advertising Cost per Door: $600 (~ $8.50 per booking)
  •   ROAS: 60:1 (1.6% of booking revenue)

You can see the added value here in capturing the average cost per booking or cost relative to the percentage of booking revenue.  The ROAS is great in comparing the productivity between each channel. Understanding these other metrics is valuable in determining if the cost outweighs the income being recognized.

The Next Big Adventure: Revenue Management

Hopefully, that wasn’t too painful.  As of this writing, these next sets of metrics are still slow to be adopted by the STR community.  One of the reasons I enjoy this market is because of the huge opportunity to distinguish yourself from the competition.  Revenue Management is one of those opportunities. Many owners/managers have different rates for weekdays, weekends, seasons and holidays, but the rates are fixed and aren’t adjusted based on demand.  With some effort and possibly leveraging some market data, you can adjust your rates and subsequently improve your sort ranking on the channels. Ultimately, you’ll present your property with a rate that is best suited to balance the highest rate and occupancy.

Warning: this won’t be easy.  I recommend taking a simplistic approach at first, building upon your knowledge and toolset over time.

Lead-Time (number of days leading up to the night of stay):  generally speaking, the closer to the night of stay, the lower the rate you would present.  With more advanced data and reporting, you may determine this is the point when you want to increase your rate based on the booking curve (explained further below).

Occupancy (nights available to rent within a given period): this can be viewed looking specifically at your property or across your competition.  You should have a target occupancy rate that will vary depending on the season (example: peak season occupancy should be 90%, where off-season may be 25%).  

Demand (number of guests competing to book properties): this can be a very difficult metric to capture and fluctuates greatly based on season, weather, economy, and lead-time to booking.  This metric is the most complicated to capture but also the most valuable since it’s a core element to determining the booking curve.

Booking Curve (historical quantity of bookings taking place relative to the period before stay date): this is an advanced metric that indicates when the peak number of guests will be booking for a specific date in the future.  Example: if I have availability for Labor Day weekend, Booking Curve may indicate an increase in booking demand for that weekend starting in early June, the highest volume of guests (peak) taking place in early July, and a reduction in demand starting in mid-August.

Average Rate (nightly rate your competition is advertising for a specific date): two elements are important here: 1) identifying your competition; 2) calculating the average rate.  

There’s no specific logic for measuring these 5 metrics and establishing a rate.  Hotels have become very scientific in balancing these metrics and producing rates, sometimes changing rates multiple times a day.  Realistically, this logic is constantly evolving and taking into consideration factors never considered before. Example: In 2016, San Francisco hosted the Super Bowl.  Hotels and STR hosts were expecting to capture very high nightly rates from guests visiting the city. What they didn’t anticipate were the thousands of people that created an Airbnb listing just weeks before the Super Bowl, making their houses available for that weekend.  The surprise increase in supply deflated the hopes of many and kept rates surprisingly low.

 Don’t let this discourage you.  Revenue Management can increase your booking revenue by 20% or more, capturing the highest rates during peak season and striking the right balance with rates in the shoulder and off-season.  These metrics take time to develop and can get expensive if you’re leveraging market data. My advice is to take it slow, test & learn.

How do I know if any of this is working?

There are 3 metrics to indicate productivity.  Any of these by themselves only tell part of the story, so reviewing all 3 together is very important.

Average Daily Rate (average rate charged for nights booked over a period): this rate will vary by season and should be measured each month and for the overall year.  ADR is a great way to compare the same property year-over-year or across competitive properties.

Occupancy: same metric as stated above.  It’s important to include this metric in combination with ADR.  A high ADR with low Occupancy or low ADR with high Occupancy are indications your rates are not balanced.

RevPar (revenue per available room): this is a hotel metric but can be adapted to STRs.  This is an extremely valuable metric in understanding how properties are competing with each other or how a set of properties is performing year-over-year.  An ADR or Occupancy that is out of balance will become evident when looking at RevPar compared to last year or other comparable properties.

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