Technology has a significant influence on organizational performance. The World Wide Web (WWW) contains vast information that helps companies improve market share, increase customer retention, deter fraud, and attain high operational efficiency. Search engines facilitate information retrieval from the WWW (Ajayi, & Elegbeleye, 2014). Organizations use different metrics to evaluate search engine efficiency while results provide a basis or formulation for important strategies. eBay is a multinational e-commerce company operating in the B2C marketplace and selling a wide range of products. Consumers rely on eBay’s search engine to explore millions of listings to find desired products. EBay’s has an innovative search engine that meets its business needs and its continuous improvement will result in greater business success.
Type of Search Engine
Besides various types of search technologies, eBay uses a hybrid search engine known as Cassini. Effective information search is a significant problem for large e-commerce companies, such as eBay due to volatility of the inventory, wide information scale, and data quality. Customers access diverse information when searching EBay’s website, including available items, product description, prices, visual image, and auctions that undoubtedly influence their purchasing decisions. Therefore, eBay created Cassini to improve customers search experience on its website to generate high sales revenue.
Several defining characteristics of eBay’s Cassini search engine are available. Firstly, Cassini has an algorithmic system known as the best match that helps consumers to find relevant product based on their previous activities and queries on the website (Blake, Nosko, & Tadelis, 2016). Secondly, Cassini technology uses web crawler to search through customers’ queries through hundreds of web pages to find the best results (Trotman, Degenhardt & Kallumadi, 2017). eBay’s searches are conducted over data sets of active products that are on sale and items whose sale process has been completed depending on the sent query. Finally, Cassini has a replication system that preserves consumers’ data to provide consistent services 24 hours despite system breakdowns in some areas. Therefore, eBay’s search engine operations revolve around consumers wants.
Benefits of Search Engine
EBay’s Cassini has many advantages compared to other search engines operated within organizations. Firstly, Cassini enhances customers experience on EBay’s website resulting in high satisfaction rates. The platform processes customers’ queries at high speed and uses random shards to search for data systematically. Consequently, customers only wait for a few seconds to obtain information on the website. Moreover, Cassini’s best match algorithm increases the relevancy of product searches, making eBay number online retailer destination for consumers (Blake, Nosko, & Tadelis, 2016). Consumers are not only attracted to EBay’s products but also its efficiency in service delivery.
Secondly, eBay’s search engine increases product visibility. Searches on eBay’s website produce millions of listings under different product categories and listings from varying sellers. Relevant information is displayed on the website allowing customers to view basic product features (Yang et al., 2017). Consumers click on desired products and are taken to a new page for specifications, where detailed product characteristics, including design specifications, are discussed in detail. Based on the search results, consumers can either decide to order an item or cancel and return to the first page to continue the process. As a result, eBay’s consumers can make informed decisions since the platform is interactive and informative.
Finally, eBay’s efficient search engine increases customers’ traffic. eBay connects millions of sellers and buyers through an online platform facilitating local, national, and international trade. Due to eBay’s popularity and reputation in the market place, customers have many expectations regarding the website’s functionality (Jain, 2013). eBay maintains these outlooks by using an indexing feature in the search engine to search through listings and generate search results for consumers. It is worth noting that eBay’s searches rarely lead to no results. Instead the company presents a selection of relevant products that customers can choose. The information about eBay’s search engine has become a powerful advertisement for the company.
Metrics to Evaluate Search Engine
eBay can apply various parameters to evaluate its search engine’s performance and to identify its strengths and weaknesses. Precision is the first method of search engine assessment; it involves using different scales and scores to gauge relevancy of search results. Factors considered in precision evaluation include search completeness and relevance of generated returns. Many ranking scales can be used to measure search engine precision. For example, users can be asked whether the search information was highly relevant, somewhat relevant, or irrelevant (Ajayi, & Elegbeleye, 2014). Precision scales are customizable depending on organizations’ needs, target consumers, and gathered information used to make critical decisions. Since eBay has diversified sellers and customers, customization of precision measures is a suitable approach to evaluate its search engine.
Web analytics is another vital metric for evaluating search engines. Digital analytics focus on investigating customers’ activities on a website and their influence on organizational performance. eBay has access to commercially available web analytics tools that measure different outcomes, including Click Tracks, Core Metrics, Google Analytics, and SAS Web Analytics Web trends (Efraim, Volonino, & Wood, 2013). Through the web analytics software, eBay will collect statistical and comprehensive information about its customers and use it to enhance its competitive advantage.
Human relevance judgment is a useful measuring search engine performance. The metric evaluates search engine from users’ perspectives, which provides information that reveal effectiveness. Human relevance judgment is a subjective measure that requires formulation of questions that are posed to users (Ajayi, & Elegbeleye, 2014). Therefore, human relevance judgment increases organization’s understanding of customers, and findings are used to identify improvement areas and chart way forward for business expansion.
Business Areas to Expand Using Search Engines
Although eBay’s search engine has many strengths, several weaknesses are evident, which require prompt improvement. Cassini is customer oriented as focus is on meeting their needs, and sellers are expected to comply with these needs. Although eBay strives to collect and store comprehensive customer information, same effort is not applied for sellers. Undoubtedly, capturing and indexing information of the seller would make it easier to generate searches through the best search algorithm (Trotman, Degenhardt & Kallumadi, 2017). Sellers will feel appreciated and involved in eBay’s processes; thus, their probability to migrate to other online platforms will significantly reduce.
Additionally, eBay should focus on developing effective feedback scores to identify potential areas of improvement. Customers’ perception of sellers and company operations influence their decisions. Despite eBay’s efforts to conquer new markets, continuous improvement is essential in light of constant changing demographic factors. As a result, the company will continue to dominate the market.
Search engine technology is at the core of eBay’s success. Creation of Cassini was a breaking point for eBay, which improved customers’ experience. Search process ensures provision of relevant data, enhanced customer satisfaction, product visibility, and increased customer traffic. Measures of precision, web analytics, and human judgment are viable metrics for evaluating Cassini’s performance and creating a platform for more improvements.