Read-Optimized, Eventually-Consistent Data Stores: In Practice

Jean-Philippe Daigle posted October 15, 2019
This is Part 2 of a series on how TripAdvisor uses event-driven architecture. In Part 1, we introduced basic concepts and trade-offs; now we’ll dig into two different real-world use cases: followee feed-building and member profile search. Both of these use cases rely on maintaining an eventually-consistent, non-authoritative view of data managed by other services for the purposes of fast querying. Followee / Follower Model The Travel Feed on TripAdvisor is a collection of recent…
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Toward CQRS: Read-Optimized Data Stores, the Join Problem, and Event Collaboration

Jean-Philippe Daigle posted October 8, 2019
This is Part 1 of a series on how TripAdvisor uses event-driven architecture and read-optimized data stores to orchestrate complex work across a complex fleet of microservices. TripAdvisor runs a constellation of microservices, several of which operate as the source of authoritative truth for one small part of the business' overall data model. Services marshall, through their public API, access and update requests for the data they manage. The Join Problem With…
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Improving SEM Landing Page Quality for our Experiences Business

Andrew Correia posted September 27, 2019
In the world of SEM, short for search engine marketing, advertisers bid to have their ads placed at the top of a search engine’s results page. TripAdvisor, like most companies, is an active player in this space; if someone is searching Google or Bing or any other search engine for something that we have, we want to make sure it’s known that we have it by getting our listing as…
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Revamping systems – The Agile way

Irena Shaigorodsky posted July 26, 2019
When revamping a system using a waterfall methodology, legacy systems are modified while new systems are built. At feature parity, they need to run in parallel for a reasonable amount of time to ensure that the new system can genuinely replace the existing one. Using an agile rewrite, we can start seeing wins sooner — kind of like rebuilding an airplane piece-by-piece while still in flight. The decision to rewrite…
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Query Understanding At TripAdvisor

Robert Hall posted July 11, 2019
Search is an important tool for navigating TripAdvisor.  The current implementation requires the user to specify a search query and optionally a “geo-scope” which prioritizes results which are within the specified country or city.  On the search result page we display a relevance ranked list of locations and other content, like forum posts, users, travel guides etc. This approach has a few problems, the first of which is that users…
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What makes B2B Product Management harder than B2C Product Management?

Mahesh Chayel posted May 21, 2019
Though in theory, the supply side of a two-sided marketplace sounds like the twin sister of demand, a lot changes in the way Product Managers need to approach Product Management on the supply (i.e. B2B) side. I also want to call out that in this article, we would be looking at B2C as a non-paid product e.g. TripAdvisor. Most of the fundamentals of product management remain the same at B2B…
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Image Quality Assessment and why TripAdvisor cares about it

Imri Sofer posted April 30, 2019
TripAdvisor has embarked on a mission: To make every image on our website amazing. This is not an easy task. We have 1 million points-of-interests (POIs) on our website, from the Grand Canyon to Hoover Dam, and more than 200,000 bookable experiences, from speed-boat rentals in Miami to goat yoga in Snohomish, WA (yep, we have it!). As you can imagine, sifting through the tens of millions of images our…
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Reducing A/B test measurement variance by 30%+

Victor Lei posted April 11, 2019
As a data-driven company, A/B testing is a powerful tool that is leveraged at TripAdvisor in order to ensure we are making decisions which are driving real incremental change. A key challenge is that getting sufficient sensitivity for these tests can be difficult due to the high variation observed in some metrics. Decreasing measurement variance is especially important given the size and popularity of TripAdvisor where even a very small…
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Personalized Recommendations for Experiences Using Deep Learning

Peimeng Sui posted March 26, 2019
As the world’s largest travel site, TripAdvisor provides a platform for billions of users to research, book, and review their trips across the world. Our Experiences business provides travelers a collection of over 160,000 bookable experiences, from canoe rentals in the Everglades to entrance ticket to the Eiffel tower. The fast-growing user and product spaces pose a significant challenge for us: how to match users with experiences that are relevant…
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Reducing Code Using Kotlin

Greg Milette posted February 5, 2018
This post was co-authored by Greg Milette and Ian Stewart  TripAdvisor has a great mobile app for vacation rental owners. Recently we made it even better by converting 33% of its code to Kotlin. One of the benefits we are seeing while doing this conversion is a reduction in code size. Having less code is good for reducing errors and lowering maintenance costs. Therefore, we care a lot that Kotlin promises…
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