Blog

Insights from the Koddi team on hotel price ads, meta, and more...
Designing event based applications with incron

Recently we wrote an article on leveraging AWS Lambda to create event based applications using S3. However what happens when you don’t have access to […]

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Creating Advertiser Value in Metasearch

It’s hard not to notice a lot of encouragement of a “race to the bottom” mentality in metasearch, and it’s not new. Some engines prioritize pricing over anything else. Others are prioritizing only deep discounts, often from the gray market.

Today there’s been a bit of a stir from an internal Google Now feature is encouraging rebooking on price drop. As a user, I love the idea of this feature. I already rely on Google Now, and would find a lot of value here. As an advertiser, I wouldn’t know exactly what to think.

Price is an important lever in any market, and there’s nothing inherently wrong with products and features that create price pressure. Balance here is important; we can’t expect healthy advertisers if all they ever get is more and more pressure.

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Quick & Easy Google Hotel Ads Optimizations

We’ve been very lucky to work with lots of smart partners over the last couple of years. In that time we’ve collected a handful of best practices that any Hotel Ads advertiser can implement. The four activities below only take a few minutes to put in place, but can each have a significant impact on your campaign performance by driving lower CPCs and higher volumes.

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Better Hotel Search, Direct Bookings, and Crowdsourcing on Google

This is a big week for hotel metasearch. In the last few days alone, we’ve spotted three really important experiments or updates that have the potential to cause big shifts in the hotel marketing world. Further, the velocity of these changes point to a Google Travel team that is serious about iteration. The quick evolutions and the growth we’re seeing really solidify Google’s position as a major player in the space.

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Reactive Applications with AWS Lambda

Sometimes you may find yourself requiring a CRON script to clean a file, or maybe you need to watch a directory of images to create preview thumbnails when they arrive on the server. Processes like these suffer from the same limitation; they require you to poll a script until you get a “successful” result.

This is problematic because it forces the developer to write redundancy checks in the code instead of just focusing on the core problem. Moreover, file watching utilities generally notify once the file is created, not when the file is finished writing. All of these problems must be accounted for, and result in more complexity, overhead, and development time.

This is where event driven programming can greatly reduce your development overhead. Part of that is maintaining a centralized data lake for all of your raw files. Data lakes generally maintain an event API for easy management and access of files within the lake. In our case, Amazon S3 is the data lake of choice and thanks to AWS Lambda we can hook into the S3 event API with minimal effort for simple use cases like cleaning files.

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Google Experiments with Amenity Data

It looks like Google is starting to do some more experiments on Hotel Ads. Recently, we spotted an experiment on localuniversal that prominently highlights hotel amenity data beneath the metasearch ad unit. As of now, the experiment appears to be showing for a small amount of traffic.

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Optimizing your Docker workflow

We create a lot of single responsibility services including fetching mail, downloading groups of files, cleaning data, importing data, and many others. This requires us to create new servers that need to be monitored and maintained so we use docker containers to normalize our process and work efficiently. From testing to staging to production, docker containers provide a simplistic way to create disposable server images.

The primary drawback is most docker images lack proper setup or are not designed for your network or architecture. Below are a list of recommendations that will make creating docker containers a less time consuming process.

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Game Theory in Online Ad Bidding

Although bidding for online advertisements seems like a mundane task, it actually reveals very complex strategic decisions made by the various bidders. Here we explore the game theory aspects of online ad bidding.

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Rate, Position, and Brand Preference in Metasearch

We like to run lots of experiments in and out of campaigns to test how users behave in metasearch and understand how we can help drive our clients more bookings at higher ROIs. In a recent experiment we set up a controlled metasearch environment and tracked how users responded to price, position, and advertiser-types.

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Moving One Billion Rows in MySQL (Amazon RDS)

So you may remember from our article in November of 2014 about our switch to Redshift, that Koddi uses Amazon Web Services (AWS) to power our platform. While we have moved some of our data to Redshift, we still have quite a bit in MySQL (RDS), and at the beginning of this year we needed to move our main database from one AWS account to another. The normal process when creating a copy of a database in RDS is to take a snapshot and spin up a new database from this snapshot. However, Amazon doesn’t allow you to share snapshots between accounts. This posed the question, how do we efficiently migrate over a billion rows of data?

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