Effective site search functionality is essential to delivering a seamless user experience. Yet, users often use abbreviations, symbols, and slang in their search queries, posing a unique challenge for online retailers.
Understanding and catering to these linguistic nuances can drastically enhance the ecommerce search experience.
This article will explore how users utilize abbreviations, symbols, and slang in their searches and discuss strategies to improve site search for a more intuitive and user-friendly ecommerce experience.
The Language of Ecommerce Search
Abbreviations, symbols, and slang play a significant role in ecommerce search. Shoppers frequently use abbreviations to expedite their search process, such as “HD” for “high definition” or “ASAP” for “as soon as possible.” Symbols, such as “$” for prices or “&” for conjunctions, are also commonly used.
Additionally, shoppers often use slang terms or colloquial expressions when searching for specific products or deals. Recognizing and interpreting these linguistic shortcuts is essential for online retailers to deliver accurate and relevant search results [1].
Understanding User Behavior
To enhance site search, it’s essential to understand how users utilize abbreviations, symbols, and slang in their queries. Analyzing user search data can provide valuable information about specific terms and language patterns.
Identify frequently used abbreviations, commonly employed symbols, and popular slang terms to tailor the search functionality accordingly.
By understanding user behavior, ecommerce websites can better align their search algorithms with the language preferences of their target audience [2].
Improving Site Search for Better User Experience
What key functionalities should you expect from a seamless site search that handles all jargon language?
Autocomplete and Suggestive Search:
Implement an intelligent autocomplete feature that suggests abbreviations, symbols, and slang terms as users type their queries. This real-time assistance can guide shoppers and help them find what they are looking for more efficiently [3].
Understand Search Queries with NLP:
Train the search algorithm to recognize abbreviations, symbols, and slang and map them to their corresponding forms or relevant product attributes. Usually, natural language processing (NLP) is the feature behind it.
It ensures that search results include relevant matches, even if users enter shorthand or abstract terms [4].
Language Variations and Synonyms:
Account for different variations of abbreviations, symbols, and slang terms. For instance, recognizing that “2U” and “to you” have the same meaning enables the search functionality to provide accurate results for both variations [5].
To achieve this, look for an AI-powered site search solution like LupaSearch.
Customer Feedback and Iterative Improvements:
Regularly seek user feedback to gain insights into any abbreviations, symbols, or slang terms that may be missing or misinterpreted by the search functionality. You can find this information in the Reports, Stats, and Analytics section in your site search.
Continuously refine and update the search algorithm to better align with user expectations [6].
Vector Search:
Augment text-based search with vector search (also called visual search) capabilities. In some search engines like LupaSearch, users can upload images of products they need, eliminating the need for text-based queries and potential abbreviation or slang-related challenges [7].
Voice Search:
Integrate voice search functionality to cater to users who prefer spoken queries. Ensure that the search algorithm recognizes and interprets abbreviations, symbols, and slang used in voice commands accurately [8].
Conclusion
Ecommerce businesses must recognize the significance of abbreviations, symbols, and slang in user search behavior and proactively address this linguistic challenge.
By implementing intelligent search features, leveraging advanced technologies, and staying attuned to evolving language trends, online retailers can create a more intuitive and user-friendly search experience.
A robust and accurate site search like LupaSearch satisfies customer needs and builds trust, enhances brand loyalty, and drives business growth in the competitive ecommerce landscape.
If you are ready to build a better user experience that drives conversions, book a free demo with the LupaSearch team. We will be more than happy to work for your business success.
References
Tsagkias, M., King, T. H., Kallumadi, S., Murdock, V., & de Rijke, M. (2020). Challenges and research opportunities in eCommerce search and recommendations. ACM SIGIR Forum, 54, 1-23.
Jansen, B., & Molina, P. R. (2006). The effectiveness of Web search engines for retrieving relevant ecommerce links. Inf. Process. Manag., 42, 1075-1098.
Almeida, T. A., Silva, T. P., Santos, I., & Hidalgo, J. M. G. (2016). Text normalization and semantic indexing to enhance Instant Messaging and SMS spam filtering. Knowl. Based Syst., 108, 25-32.
Vandelle, G. (2005). Automatic text processing to enhance product search for on-line shopping. Proceedings of the 14th International World Wide Web Conference.
Sharma, S., Mahajan, S., & Rana, V. (2018). A semantic framework for ecommerce search engine optimization. International Journal of Information Technology, 11, 31-36.
Kim, H., Suh, K.-S., & Lee, U.-K. (2013). Effects of collaborative online shopping on shopping experience through social and relational perspectives. Inf. Manag., 50, 169-180.
Trotman, A., Kallumadi, S., & Dagenhardt, J. (2020). Introduction to special issue on eCommerce search and recommendation. Information Retrieval Journal, 23, 115-116.
Harris, L. R. (2005). B2B Marketers Integrate Precision Search to Boost Profitabilityand Increase Satisfaction Across the eCommerce Value Chain. The Journal of Internet Banking and Commerce, 10, 1-4.