Automation Ideas Portal
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Benchmarking is a crucial aspect of the strategic thinking within the Commercial team and the business as a whole. At the moment, the amount of data that we have on price changes over time is very limited and tedious to gather. The automation of this process would enable the business to make more precise decisions and be able to confidently rely on the data.
Price benchmarking is one of the key metrics that are continuously monitored in the Commercial team. This includes prices of hotel rooms, flight fares and total packages. For the individual components, this is usually compared against our own prices on Phenix. For example, "how does the price of 5 nights at Ikos Dassia in the Deluxe Room All-Inclusive compare from a 2019 booking to what Phenix marks it at right now". To to this, we get hotel components from past bookings from F2019, F2022, or whatever year we want to benchmark against, and replicate the same component on Phenix on a nett rate basis. We then log all the prices on a workbook, from which we extract the data to make the final analysis. It currently takes, on average, 25 minutes to match 10 hotel rooms. This is due to Phenix wait times, some hotel rooms not matching YoY, and other problems that we might come across. Considering that we want to have a good amount of data to base our analysis on, we are limited to benchmark only on a few destinations.
We also benchmark flight fares. This can be done in two ways, manually benchmarking similar to hotel rooms, or categorizing flights from current and past years to compare against each other. The first works similarly to the hotel benchmarking and takes on average 20 minutes to match 10 flights. The second option lets us have a bigger pool of data with anywhere from 1000 to 2500 matches, depending on the month. The problem with the second option is that flights are compared by booking month, airline, route and departure month. In months like December where there is a big difference in prices from one day to another, this can produce some unprecise data. This method only takes 30 minutes to complete and brings back ~2000 flights.
The last type of price benchmarking we conduct is Package Competitor Benchmarking. This involves creating a package on Phenix and replicating it on the websites of competitor Tour Operators to keep track of how Travel Counsellors compares to the rest of the market for different destinations. This process can take a full-days work to get 12 packages benchmarked. Although the data we currently have is good for referencing, it doesn't allow us to precisely see how we compare in the market in a per destination basis.
Ideally, automating these processes would give us access to a dataset created by the system from where we could directly extract the benchmarked prices. This would allow us to make detailed reports of how prices have changed over time per departure period and destination for bookings made in a specific date range.
