How to Get a Fuller Picture of Your Competitors Room Rates

Not all room rates are created equal. As travellers, we understand this. Yet, when rate shopping as revenue managers, we can sometimes overlook this fundamental fact. If we see a competitor’s rate drop, we instinctively consider the same for our own rates. But is it always justified?

NB: This is an article from OTA Insight

With a reputable rate shopper, data should be rich, accurate, up-to-date, and well-structured. And we trust the data to show us the truth, so the instinct is understandable: data can reveal the truth. But only if it comes from an apples-to-apples comparison.

Without this direct comparison, insights are skewed and possibly erroneous. So, to leverage insights beyond raw rates, let’s review the key room rate qualities that fill in the picture of your competitors’ rates – and how your rates fit in.

Do your tools provide you with this insight?

Variables of a room rate.

It’s dangerous to react to room rate information without adequate context. A variety of qualities affect a room rate. It’s the blend of these qualities that define a room’s price for a particular search.

In pursuit of a clear and accurate comparison, the goal is to visualise each individual room in the way that a potential guest sees it during their research process. If guests can see these details when they individually check out each deal on Brand.com, OTAs and metasearch engines, so should you as a revenue manager.

Getting granular

Here are some qualities that will influence a room’s price, often significantly:

  • Rate type: For a meaningful comparison, you need to know whether a given room displays the best flexible rate or the lowest rate (with reduced flexibility).
  • Length of stay: From one night up to 30, the rate per room per day reveals how pricing evolves for longer stays. Different hotels’ LOS discounting strategies can vary widely, as demonstrated in this exclusive report, so access to this information when comparing your prices to your compset’s is valuable.
  • Room type: Premium, standard, suite, etc. Room type is one of the most significant factors to affect its rate.
  • Brand.com rate types: Rate types for hotels’ own websites, which show how different hotels tier their rates – whether public, member-only, AAA, senior, AARP, government, military, etc. – can help you refine your strategy when competing for direct business.

Since these qualities influence a room’s price, you want as many of them as possible when doing a comparative analysis of one hotel’s rates against another’s. Without this information, comparisons are fraught with inaccuracy; responding by altering your rates could be dangerous. For example, The price difference between Best Available Rate and Best Flexible Rate is usually meaningful, so comparative analysis must always compare two similar rate types. That’s why thorough room-type mapping is the foundation for effective revenue management.

An even fuller picture

The qualities outlined above will help you create a meaningful picture. But what if you’re interested in how your and your competitors’ rates compare to variable such as the following?

  • Lowest rate as compared to best flexible rate
  • Member only as compared to non-member, drawn from your site and your competitors’ Brand.com sites
  • Whether bed and breakfast is included
  • Rates for earlier days, specifically yesterday, three and seven days ago, and the same day of the week that time last year
  • Length of stay discount variations

When a user selects one of these options from a rate shopper that provides this level of granularity, additional data comes into view. This data would be the percentage differences both for your property and for your competitors’ for all the dates in view.

With lowest rate, for example, the number might be “-10%“, meaning that your lowest rate is 10% less than the rate for the best flex rate, which remains in view; similar percentages are shown for your competitors.

Of course, rate shoppers often offer some of this information but compiling it yourself without access to “compare to” functionality would be very time-consuming.

Room-type mapping

Now that we have a firm grasp of the qualities that make up a room rate, we have an idea of how each can be used as a litmus test against competitors’ rates.

Next, we must look at ensuring a consistent view into how your unique room type mix fares against your compset.

We mentioned room type earlier. But to achieve the desired results consistently, invest in technology that offers room-type mapping. Without this, you might not be comparing like with like. This is the process of breaking down your own room types, as well as competitors’, and then mapping them against how a hotel merchandises its inventory.

Mapping ensures accurate rate shopping with an apples-to-apples comparison of competitor rates. It’s well worth the time saved in identifying which room description belongs to which category. It’s not easy to remember whether a River View King Deluxe room is the same room type as a River View Double room, especially when comparing across dozens of room types in a given compset.

Take the time to carefully map room types across each of your competitive sets. With the ability to craft multiple compsets, you’re able to have more granular control and increased visibility over how to sort your competitors into buckets that work best. Some revenue managers find success with compsets filtered by room types, and not just personas or geographies. This helps account for hotels with similar room types but may not fit cleanly in a demographic or location-based competitive set.

A good system should be able to automatically classify room types into the correct room categories by identifying keywords in their names. For example, any room type containing the word “suite” would automatically be placed in the “suite” category, reducing manual work and uncertainty for hoteliers. Ideally, pre-defined room categories would also be deleted in favour of ones you create that better fit your compset.

room-type-mapping

Mapping room types across a comp set helps save time and increases accuracy. OTA Insight’s rate shopper automatically maps room types per competitive set and allows for manual editing.

Benchmarking Brand.com directly

Another lever in rate shopping is benchmarking your site directly against your competitors’ sites. This is when a revenue manager compares rates across your Brand.com and those in your comp set rather than prices as displayed on third-party channels like OTAs.

In this method, rate types for direct bookings are compared directly: public, AAA, senior, government, AARP, etc, as well as Best Available Rate (non-refundable) or Best Flex Rate with cancellation. Each of these rate types designates a different discount profile controlled by an individual property, and can impact how guests compare one hotel to another.

If a revenue manager ignores these specific rate types, and their impact on pricing at Brand.com, there’s potential for massive misalignment. For example, if a potential guest searches for a mid-scale property with a senior discount and sees a dramatically lower rate when comparing two properties, the lower rate will win. The cause of this discrepancy could be a revenue management mistake, where a rate was shopped incorrectly against the wrong rate type.

If your revenue management process doesn’t include shopping rate types across your comp set’s direct channels, discrepancies can creep in. That’s why it’s important to create separate habits around monitoring rate types at the room level on direct channels, across each of your competitive sets, to gain visibility into competitor pricing.

Mixing the ingredients to achieve results

Each of the above room rate qualities is a standalone data point that affects whether and how you adjust your rates in response to competitors. Each combination paints a different picture, which can alter your room pricing strategy. These qualities can also be mixed and matched to create a unique framework for understanding the competitive landscape.

This is where behavioural facets, such as a guest’s length of stay, also come into play. As an example, let’s take a luxury resort in the Bahamas. The property’s guest mix skews heavily towards leisure and special events like weddings. There’s some price sensitivity, but many guests are investing in their only vacation of the year. The average stay is five nights. The property wants to extend this to six nights, so the revenue manager creates a filter that only analyses competitor rates of stays longer than six days. Now, the manager can see what package types, rates, and room types are being offered at what price for stays longer than six days. This information is then used to execute a digital marketing campaign that positions the hotel compatibility for stays of that length among similar segments.

Mixing and matching filters creates limitless opportunities for rate-driven marketing, as well as a more nuanced approach to rate-setting and traditional revenue management. When setting your own hotel’s Best Available Rate, effective filtering helps determine your property’s value compared to its competitive set. Yet, without accurate room mapping, your rate shopper will paint the wrong picture when looking at your rates in relation to your competitors’.

Since potential guests see extensive details for each room under consideration, hotels must work diligently to ensure competitive and thoughtful pricing across Brand.com, OTA and metasearch. Successful rate management can be intimidating; with the right tools, it’s possible to not only manage rates as table stakes but to up the ante with skilled rate shopping.

Read more articles from OTA Insight