Who is the Company

A global leader in purification equipment manufacturing for the food, beverage, chemical, and medical industries.

The Challenge

Despite having manufacturing as its core business, the company wanted to be ahead of the curve and create value for its customers by providing better digital experiences. The company had already taken steps in that direction and was using AEM for its B2B web content. They replaced the native AEM site search with Apache Solr to provide a better search experience to their customers. Although the performance was ‘satisfactory’ for the company’s needs, they sought for a search engine that could accommodate all the variations expected by their customers like:

  • Intelligent suggestions
  • Natural language support
  • Global language support
  • High-traffic scalability
  • Synonym support
  • Typo tolerance

In brief, the company was looking for a search solution that could be integrated into the AEM system and offered: 

  • High performance:The company’s current solution performed quite well. At a minimum, the new solution was expected to match the current performance.
  • Full commercial capabilities: The new search component had to offer the full range of commercial search capabilities. Expanded capabilities were essential to the company as customers were sometimes frustrated with the current search results, representing a potential loss of business.
  • Personalized and engaging customer experiences: The company sought customized experiences for customers by suggesting products that are tailored to their requirements and engage their interests.

The Solution

After careful consideration, our CMS team selected Algolia, a proven high-performance search engine to provide Search-as-a-Service (SaaS). It was extremely easy to work with and it began delivering value immediately.

It provided many critical out-of-the-box capabilities, including:

  • Global language support
  • Typo tolerance
  • Highlighting and snipping
  • Faceting
  • Synonyms
  • Advanced language processing
  • Geo awareness
  • Multiple sorting strategies
  • Grouping and de-duplication
  • Personalization

Our team created several AEM components that enabled content authors to configure multiple aspects of search behavior specific to the content. One of the most important components our team developed receives data from Algolia search and displays results for one or more query parameters. The AEM component is configurable by content authors to control search filter results.

Our team developed an AEM component Helper class that contained Algolia’s basic key configuration. When the search page loaded, it invoked the AEM component. It sends customer search data via an AJAX POST request to Algolia, which returns an array of JSON objects pertinent to user actions and personalization.

Key aspects of our solution included:

  • Improved site search response: Even though Solr provided a search response in two seconds on average, Algolia easily beat that time. Site search response time went down to under one second for most searches.
  • Gained fully commercial capabilities: Algolia provided essential capabilities such as synonym support, geo-awareness, and typo toleration, immediately improving the quality of the search results provided to customers.
  • Allowed customizable control over search results: The integration enables content authors to impose behavior from AEM into the Algolia search results, leading to better customer experiences.

Business Impact

  • Faster performance leads to increased customer satisfaction: Poor search performance is one of the biggest problems B2B manufacturers face. Quick search results lead to greater customer satisfaction.
  • Higher quality search results improve product sales: Customers who receive accurate and appropriate search results make faster purchase decisions. Precise search results also help reduce the number of product returns.
  • Better personalization helps retain customers: The ability to control contextual search result behavior allows the company to precisely tailor search results to each customer. This, in turn, increases the chance that customers return to purchase additional products.

Technologies Used

Adobe Experience Manager: Cloud-based platform that provides a personalized customer experience across multiple digital media channels
Apache Solr: Java-based enterprise search platform
Algolia: AI-based hosted search and discovery service

Related Capabilities

Utilize Actionable Insights from Multiple Data Hubs to Gain More Customers and Boost Sales

Unlock the power of the data insights buried deep within your diverse systems across the organization. We empower businesses to effectively collect, beautifully visualize, critically analyze, and intelligently interpret data to support organizational goals. Our team ensures good returns on the big data technology investments with the effective use of the latest data and analytics tools.

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