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How accurate is your distribution data? 5 steps for hoteliers investigating data quality

How accurate is your distribution data? 5 steps for hoteliers investigating data quality

Hotel technology is transforming how hotels optimise their distribution health – providing a fast and seamless way of delivering responsive pricing and maximising net REVPAR. But, in the ever-changing digital world hotels operate in, even the most reliable distribution intelligence software should be checked.

Bad data leads to bad decisions, so it's imperative the data you are seeing is accurate. Often rates can differ according to point of sale (PoS), the time of day, and the channel displaying the rates, so ensuring your intelligence solution data is accurate, is paramount. How often do your teams check the quality of the data that your business is reliant on? Have you ever questioned whether you should have complete faith in your solution?

This article provides you with 5 steps that will help you check the quality of your data, and get to the heart of any rate parity issues.

  1. When you first come across something you suspect is an issue, for example, your distribution intelligence solution is saying you are out of parity, investigating why this may be the case is recommended. If a link is provided to the original site the rate was taken from, click it and compare the rates presented in your distribution intelligence solution to the one presented on the OTA.
  2. Make sure you’ve selected the correct hotel and entered the correct check-in and check-out dates as well as the correct number of guests to match the original shop displayed on your intelligence tool.
  3. It’s recommended to conduct this process on 5-10 shops in order to make sure that the issue wasn’t a glitch or one-off issue.
  4. If the rate doesn’t match this, a deeper investigation is required:
  • Understand what PoS the shop was taken from. Most solution providers will show or tell you where the shop was conducted. This is important as OTAs tend to show different rates based on the IP address of their visitor. One reason for discrepancies can be that you are investigating the shop from a different PoS to where it was taken from.

i. You can change PoS using a free VPN add-on chrome for OTAs, and with this, investigate if the rates you are seeing on OTAs or meta sites are changing according to the PoS.

ii. Understand if the rate presented includes all taxes and fares, as on metasearch engines there are different rules per country, for example in Germany, the Netherlands and the UK, the rates are tax inclusive while in Thailand, Vietnam & Israel as examples, you will only see the base rate, exclusive of other taxes.


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On many OTAs it also depends on the country so you should read the fine print or make a test booking to find out what taxes are inclusive in the rate displayed.

  • In some cases, the reason for seeing a different rate maybe because they are coming from a third party i.e. a wholesaler. If your distribution intelligence solution is obtaining their rates via an API that does not include third party rates you will not see them, hence the rates being different. Here are several ways to identify a third-party rate on various OTAs:

i. On Expedia, you can identify wholesalers rates clearly by clicking on ‘more details’. A pop-up will appear with room details explaining if it is a 3rd-party rate.



ii.On Booking.com the rate appears a few seconds after the room rates appear on the page and it will state “Booking.basic” or “Marketplace”, note they are constantly running A/B tests, so this might change.

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iii. For Ctrip you can identify third party rates easily as only brand.com rates will have two blue characters next to the price, meaning ‘quick confirmation’ the rest will be coming from wholesalers.

iv. On Trip.com you can easily establish which are the 3rd party rates as the site explains the rate displayed is provided by a partner, meaning it will be a wholesaler rate.



5. If you have a screenshot of the original shop with a timestamp you can use this while investigating your data issues. When comparing a screenshot from an OTA or metasearch engine (MSE), are you presented with the rates of both shops and the % price difference on one screen in order to simplify the investigation? If so, you can use your screenshots as evidence of undercutting to provide to your OTA partner, or third party channel so they can rectify the issue.

To make it easier for our customers FornovaDI screenshots provide all the evidence needed to make a case. This includes the hotel name, check-in/out date, PoS, timestamp and rate difference compared to your brand.com rate. With all this information they can use the screenshots when contacting the offending OTA or meta site to show the out of parity rates.



As hotel chains become ever more adept at optimising their data use to deliver top and bottom-line results, the need for teams to understand and identify potential integrity risks increases. Finding a distribution intelligence technology partner that has an in-depth understanding of your business and who will work together with you to protect the quality of your data is crucial. A robust platform, regularly checked by your teams and the provider will ensure you turn data into intelligence – optimising revenue on every room, every time.

To find out more about how Fornova Distribution Intelligence helps hotels turn data into intelligence, get in touch!








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