Product Views: how many times a room/rate has been displayed (Part #2)
We looked at possible scenarios, now let’s come to Google Analytics and how the report should ideally be built up.
- Product List Views: for a given period it shows how many times a product has been displayed, based on customers’ booking search criteria. It’s not uncommon to have the Best Available Rate (or Daily Rate) as the rate with the highest number of views, because more likely DR rate is the less restrictive one.
- Product Penetration: it’s the most important information here, in percentage it represents how appealing a product is, the calculation is done dividing the number of booking by the number of Product List Views… the higher the better. Product Penetration needs to be set up as a Calculated Metric.
- Product Price Displayed: it’s a “nice-to-have” but not really essential, it is anyway needed to calculate the “Average Product Price Displayed”. In here, it gives an order of magnitude of how big volume each product could generate. It is simply a sum of each product price for every time it has been displayed.
- Average Product Price Displayed: combining it with the Product Penetration, this is definitely one of the most important information in our hands. In terms of budget, it gives a pretty clear idea of how much customers are willing to spend for that specific room, at those specific conditions (cancellation and guarantee policies) and conditions (minimum length of stay, minimum advance booking days, etc.). The more we get used to look throughout this information, the more we will become sensitive on the right price we should offer this product. Average Product Price Displayed is also a Calculated Metric, given by dividing the Product Price Displayed by the number of Product List Views.
- Product Revenue: Revenue generated from each product.
- Average Price: Average Daily Rate for each product.
- Unique Purchases: Number of reservations.
- Quantity: Number of nights booked.
- Average Quantity: Average number of nights booked.
- Average Booking Window: time that elapses between the booking date and the arrival date, on average. We’ve seen in the previous post (Part #1) how this information may give a very useful indication as to why a product, despite its attractiveness, may not be displayed very often.
As always, the bigger the amount of data is, the more reliable the reports are. Looking at such a report on a daily basis doesn’t make a lot of sense. Weekly or, even better monthly, it is the right time-frame you should consider. And clearly, the more time you have such tracking in place, the more chances you have to compare different periods and better understands how your revenue actions are affecting your performances.