At Koddi, we get excited about being able to gain the most granular insights into our metasearch campaigns bookings, so the more data we are given, the better we are able to optimize. One publisher, in particular, has taken this feedback and gone above and beyond in providing granular data for our clicks. Kayak recently launched an updated version of BOB (called BOB V2), and it came with incredibly precise insights into where your clicks are coming from and an increased ability to bid with multipliers on these various levers.
BOB V1
The original BOB format provided the baseline level of information surrounding your click data that you would expect. You were able to see which hotel was clicked on, and where (country) that click came from, and the device type. This allowed Kayak advertisers to set their bids at a hotel, device, and user country level. This was great but left many wanting for more. This is where Kayak’s BOB V2 came into play.
BOB V2: What’s New?
With the release of BOB V2 came a staggering increase in the amount of visibility advertisers received to where their clicks came from, as well as bidding multipliers for this new information. Outlined below are the new values that can be dynamically passed in your deep link structure to garner insightful information about which users are clicking on your advertisements, and better yet, all of these parameters can have a bid multiplier set on them to increase or decrease your CPC.
- Hotel ID (set as either a percentage of the daily rate or a fixed base CPC)
- User Country (multiplier value)
- Device Type (multiplier value)
- Days to Book (multiplier value)
- Stay Length (multiplier value)
- Saturday Stay? (multiplier value)
Days to Book
One of the more interesting additions to BOB V2 is giving insights to advertisers surrounding how far in advance your users are searching for their stay and giving advertisers the ability to set multipliers based on how far in advance the user is searching. Days to Book is an integer value that represents how many days in the future the check-in date the user was searching for is. This provides an interesting lever for advertisers to bid on. Some example use cases for this multiplier lever:
