Crafting personalized search experiences is the future.
No longer can you offer standard product suggestions and make your ecommerce business thrive.
As e-commerce expands, so do shopper expectations, prompting a shift to more sophisticated personalization methods.
Is the industry relying too much on basic recommendations and search functions for personalization? Let’s explore.
Why Are Standard Recommendations in Ecommerce Search Not Enough?
The industry’s reliance on basic recommendation and search functions, while foundational, has led to predictability and over-reliance, resulting in a repetitive user experience [1].
It doesn’t sound right, does it?
Today’s online shoppers desire an immersive experience that acknowledges their evolving preferences. Therefore, as a growth-seeking ecommerce business, you can’t offer a one-size-fits-all search approach and expect positive returns.
That’s not how it works.
You must offer a fully personalized search experience, getting into the core of each search query and user background.
How to Adopt a Personalized Search Experience? Non-standard practices
Focusing solely on recommendations and search functionalities may cause businesses to overlook subtle behavioral cues, missing out on potential sales and engagement opportunities [2].
To address these challenges, adopting advanced personalization techniques becomes essential.
Here are some of the non-standard practices to achieve that:
1. Adaptive Landing Pages
Landing pages that adjust to user preferences and behavior can significantly enhance the user journey, a principle rooted in the personalization ranking techniques discussed by Aslanyan et al. [1].
2. Interactive Content and AI-Driven Engagement
Engaging users with interactive content, such as quizzes and 360-degree product views, along with deploying AI-driven chatbots, creates a seamless shopping experience [3].
3. Targeted Email Marketing and Personalized Discounts
Utilizing data analytics tools to dissect user behaviors can lead to more effective targeted email marketing campaigns and personalized discounts, offering insights into user preferences and improving the shopping experience [4].
4. AR Try-Ons
Augmented Reality (AR) try-ons in the fashion and cosmetics sectors have been shown to bridge the gap between virtual and physical shopping, encouraging purchases by allowing users to virtually “try on” products [5].
What Truly Matters: Search Personalization
Search results personalization is at the core of modern e-commerce business success.
Adopting leading e-commerce search solutions like LupaSearch allows you to meet the demands of modern customers. Personalization fosters a sense of connection and understanding between consumers and your brand.
In this case, LupaSearch recommends only the most user-relevant products. It generates a user profile by analyzing previous user search interactions. This way, you can deliver tailored offerings aligned with individual preferences, including gender, brands, product categories, price range, and other criteria.
Yet, make sure to transparently disclose personal information-gathering practices. Ethical data collection not only enhances user trust but also provides a treasure trove of insights for businesses to tailor experiences more effectively [6].
Challenges and Concerns
Navigating the fine line between personalization and intrusion is crucial.
Excessive personalization may lead to discomfort and potential loss of trust, highlighting the importance of respecting user privacy and ensuring consistency across platforms [5].
Conclusion
As the e-commerce landscape evolves, so should personalization strategies. By diversifying techniques and focusing on user-centricity, businesses can create memorable shopping experiences that respect user privacy and continuously innovate.
Incorporating advanced personalization techniques, underpinned by ethical data practices and a deep understanding of user behavior, will enable e-commerce platforms to meet and exceed the sophisticated expectations of today’s online shoppers.
Ready to scale your business and capture the hearts and wallets of your customers?
Book a free demo with LupaSearch, and let’s discuss your business growth opportunities.
References
Aslanyan, G., Mandal, A., Senthil Kumar, P., Jaiswal, A., & Kannadasan, M. (2019). Personalized Ranking in eCommerce Search. Companion Proceedings of the Web Conference 2020. https://arxiv.org/abs/1905.00052v1
Xiao, B., & Benbasat, I. (2018). An empirical examination of the influence of biased personalized product recommendations on consumdecision-makingaking outcomes. Decis. Support Syst., 110, 46-57. doi: 10.1016/j.dss.2018.03.005. https://www.sciencedirect.com/science/article/abs/pii/S0167923618300514?via%3Dihub
Agarwal, P., Vempati, S., & Borar, S. (2018). Personalizing Similar Product Recommendations in Fashion E-commerce. ArXiv, doi: 10.48550/arXiv.1806.11371. https://arxiv.org/abs/1806.11371.
Wen, H. (2021). Development of personalized online systems for web search, recommendations, and e-commerce. . doi: 10.32920/ryerson.14655801.v1. (Wen, 2021). https://rshare.library.torontomu.ca/articles/thesis/Development_of_personalized_online_systems_for_web_search_recommendations_and_e-commerce/14655801/1.
Yoganarasimhan, H. (2017). Search Personalization Using Machine Learning. Marketing Science eJournal. doi: 10.2139/ssrn.2590020. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2590020 .
Chen, H. (2018). Personalized recommendation system of e-commerce based on big data analysis. Journal of Interdisciplinary Mathematics, 21, 1243 - 1247. doi: 10.1080/09720502.2018.1495599. https://www.tandfonline.com/doi/abs/10.1080/09720502.2018.1495599.