Trading up: Implementing Algolia search to improve the trading card experience

September 04, 2019 0 Comments

Trading up: Implementing Algolia search to improve the trading card experience

 

 

Are you familiar with trading card games (TCG) like Yu-Gi-Oh!? The Yu-Gi-Oh! Trading Card Game is a Japanese collectible card game based on the Duel Monsters card game popularized from the manga franchise, Yu-Gi-Oh!. The goal of this trading card game is to gather multiple cards of the fictitious monsters and create powerful decks to challenge (and win against) other players’ cards.

With over 25 billion Yi-Gi-Oh! trading cards sold, the Yu-Gi-Oh! Trading Card Game is one of the most popular trading card games and has a strong following all around the world. Based on its origin, it is especially strong in Japan where players actively seek to trade cards with one another to improve their deck collection both in person and online.

To help players find cards and trade with one another online, ka-nabell is one of the most popular and long-established Yu-Gi-Oh! Trading Cards marketplaces in Japan. To deliver a great experience to those players actively in search of a prized card to add to their deck, ka-nabell knew it had to deliver an extremely fast search and discovery experience that allows for granular filtering functions that return highly relevant results so that players can find exactly what they want, quickly. Before introducing Algolia search, ka-nabell heavily relied on SQL queries. After implementing Algolia, ka-nabell is improving the customer experience.

We had an interview with ka-nabell engineers Hirotaka Koga and Toshiharu Nishiwaki who shared their experience with us.

Courtesy of ka-nabell engineers, Hirotaka Koga and Toshiharu Nishiwak
Courtesy of ka-nabell engineers, Hirotaka Koga and Toshiharu Nishiwak

Developing a better search experience

Hirotaka and Toshiharu said that ka-nabell was looking for a faster search solution. Then, they came across a site called SEARCHSTONE

With its ease of use to buy multiple cards with granular filtering such as Price, Category, Effects, and so on, they thought this search capability on Searchstone (powered by Algolia) is ideal for creating Trading Cards decks. They also were encouraged by the value they could get through conversion rate improvement as seen on Algolia’s website (E-commerce search solutions to accelerate conversions).

In addition, Hirotaka and Toshiharu  wanted to minimize the front-end development tasks using Algolia. Vue InstantSearch was a fit for them to build a faster and smoother user interface (UI). Hirotaka said that he “enjoyed coding to build Horizontally-Scrollable UI with Vue InstantSearch”. To insert and update data, they added some codes into existing system built by PHP. For batching, they wrote a Node.js code from scratch. 

Meeting the Language Challenge

The Japanese language has three alphabets called Hiragana, Katakana, and Kanji. To enable search in any and all of the possible alphabets (e.g., searching Katakana words with Hiragana), they added fields and converted characters before indexing. They also tailored the search experience by making searchable commonly used, special characters specific to gaming and trading cards such as ☆ and Y18. 

Turning Great Search into Great Results

After implementing Algolia for their project in less than one month, there already has been positive feedback from customers with comments like 

  • “Ka-nabell search is super useful.” 
  • “Real-Time! How much did they spend to build this?” 
  • “High quality search. Typo is fine.” 
  • “Super fast and useful. Totally different from before.”

In terms of improved conversion rate, Hirotaka and Toshiharu are going to track this over time with Algolia’s Analytics features.

The best is yet to come. Since this project was successful, they decided to introduce Algolia to their brand new service. It will be launched in September.

Future Objectives

Moving forward, ka-nabell has more planned with its Algolia implementation. Because of Algolia’s Search-as-a-Service platform, ka-nabell will be able to leverage its existing Algolia implementation and agilely take advantage of Algolia’s other capabilities including:

using Algolia’s Advanced Analytic to identify opportunities to optimize the search experience for users and improve conversion rates.

Expand beyond only Trading Cards search to other businesses they run. 


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