Transforming eCommerce Search: Packaging Price and Algolia

An efficient and user-friendly search system is essential for eCommerce success. One solution that has been making waves in the industry on that front is Algolia, a powerful SaaS-based search and discovery engine. In this blog post, we'll explore how Algolia revolutionized the search experience for Packaging Price — one of IronPlane’s clients — why the implementation was essential, the notable outcomes, and other valuable lessons that eCommerce businesses can learn from this implementation.

What is Algolia Search?

Algolia is a robust and versatile search and discovery platform that helps websites and applications provide lightning-fast and highly relevant search results to their users. It excels in delivering real-time search capabilities, offering features that extend beyond traditional search tools — including query suggestions, personalized recommendations, and layered navigation and filters. These features enable businesses to transform the way users explore and find products or information on their platforms.

Why Implement Algolia for Packaging Price?

To understand why Packaging Price decided to implement Algolia, let's start with the initial requirements and goals. The journey began with a thorough discovery phase, during which IronPlane identified the pain points the client wanted to address and what features they were particularly interested in.

  1. Discovery Phase: The process began with discovery and scoping tickets, which laid the foundation for selecting Algolia. Packaging Price was primarily focused on increased site functionality, which included features and capabilities such as intelligent search, product recommendations, and more.
  2. First Round of Research: Packaging Price's initial attempt to implement a similar tool,, faced challenges. This experience provided valuable insights into the selection process and the decision-making behind choosing Algolia.

Algolia Implementation Highlights

The implementation of Algolia at Packaging Price wasn't without its challenges. The initial feature implemented for the minimum viable product (MVP) was "instant search." However, Algolia brought more to the table, enhancing the user experience in several ways — let’s cover some of the most notable ones.

Empty State Suggestions

Algolia introduced an empty state dropdown that offers popular products, categories, and search terms to users before they even begin typing their query. This feature speeds up the search and exploration process by highlighting top-selling or most-searched products right from the moment the user engages with the search bar.

Personalized Recommendations (Future Phase)

In the future, Packaging Price plans to implement personalized recommendations — a solution possible with the use of Algolia’s personalization engine. When a customer is logged into their account, the empty state will contain suggestions that are most relevant to them. These could include past purchases, compatible products based on their order history, or favorites list.

Diverse Query Suggestions

Algolia's query suggestions feature automatically offers a variety of possible completed searches once a user starts typing in the search bar. Users can choose from a set of dimensions, go directly to a specific product page, or select similar queries that other users often search for.

Layered Navigation & Filters

Before Algolia, Packaging Price didn't have a way for users to narrow their search results using relevant filters. With a catalog consisting of hundreds of similar products differing in attributes like dimensions or color, the ability to filter search results precisely was essential. Now, customers can filter results by specific dimensions or product categories, making it easier for them to find the exact product they need faster.

Algolia Implementation Outcomes

The implementation of Algolia has resulted in significant improvements in Packaging Price's eCommerce performance. Since its launch in April 2023, the following key performance indicators (KPIs) have been achieved:

  • Over 11,400 users have interacted with Algolia search.
  • More than 64,000 searches have been performed.
  • The "no results rate" is under 3.5%, meaning fewer than 3.5% of searches return no results.
  • Search results have an impressive 12.01% click-through rate (CTR).
  • The conversion rate (purchases occurring after a user interacts with Algolia search) stands at 12.65%.
  • Users overwhelmingly click on the first search result in the list, demonstrating excellent relevance in sorting.

Key Takeaways for Other eCommerce Businesses

Packaging Price's journey with Algolia offers valuable lessons for other eCommerce businesses, specifically when it comes to search:

  1. Prioritize User Experience: Invest in search solutions that enhance the user experience by offering features like personalized recommendations, diverse query suggestions, and easy-to-use filters.
  2. Implement Continuous Improvement: Understand that implementation may come with challenges. We are still working with Packaging Price on implementing even more advanced features, but the benefits of Algolia are already evident.
  3. Make Data-Driven Decisions: Utilize data and analytics to measure the success of your search implementation. The impressive KPIs achieved by Packaging Price demonstrate the power of data-driven decisions.
  4. Relevance is Key: The fact that users overwhelmingly click on the first search result highlights the importance of delivering highly relevant search results to customers.

Algolia has transformed the search experience for Packaging Price, and this success story serves as an inspiration for other eCommerce businesses looking to enhance their search capabilities and boost their overall site performance.

Learn More: Read the full Packaging Price case study

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