Friction is the enemy of customer experience. It may seem harsh but according to a PWC report, 1 in 3 customers will leave a brand they love after just one bad experience. With the stakes this high, there is little room for error when it comes to delivering customer experiences and aiding in a consumer's journey to their desired goal.
When it comes to ensuring a seamless personalized experience and removing friction wherever possible, the role of search can’t be understated. While a significant amount of time is spent doing research, consumers naturally turn to search to take control of their journey.
In general, 63% of consumers turn to search engines as their primary starting point when they want to learn about a new business, product, or service.
By marrying personalization and search together, brands are able to present the most relevant information to visitors based on their preferences while also being able to promote site content or products for greater visibility.
81%
of customers prefer companies that offer a personalized experience
70%
say a personalized experience in which the employee knows who they are and their history with the company is important
What is personalized search?
Personalized search is a dynamic approach to information retrieval that tailors search engine results to the unique preferences and behaviors of individual users. Unlike traditional, one-size-fits-all search experiences, personalized search leverages data analytics and machine learning search algorithms to understand user interactions, browsing history, and preferences.
By analyzing these factors, personalized search engines can deliver highly relevant, personalized search results, ensuring that users find the information they are looking for more efficiently.
This optimization extends beyond mere keyword matching, taking into account the context of the user's queries and providing a more nuanced and personalized browsing experience.
Whether it's presenting tailored product recommendations, adjusting language preferences, or adapting content based on regional interests, personalized search is a sophisticated technology designed to enhance user satisfaction and engagement in the ever-evolving digital landscape.
Top benefits of personalized search
1. Relevant results, faster
The primary advantage of personalized search is the ability to deliver the most relevant results quickly. And fast search results lead to increased searcher satisfaction. When users can access the information they are seeking promptly, they are more likely to have a positive experience and view the platform or search engine favorably.
By analyzing a user's past searches, clicks, and engagement patterns, the search engine can understand their preferences and present results that are more likely to match their interests. This not only saves time but also enhances the overall user experience by reducing the need for users to sift through irrelevant information.
2. Improved user engagement
Personalized search considers a user's past search history, interactions, and preferences. Therefore, by presenting results that align with the user's interests, the likelihood of finding relevant content increases.
This fosters a sense of customer engagement, making users feel understood and valued. When a search engine consistently delivers content that aligns with users' interests, they are more likely to spend time exploring the provided results. This increased engagement can lead to higher satisfaction, improved customer loyalty, and a greater likelihood of higher conversion rates.
3. Enhanced customer retention
A McKinsey & Company report revealed that 78% of consumers are more likely to make repeat purchases from companies that can provide personalization. When a user’s search offers the opportunity for them to achieve their desired outcome with ease, they are more likely to return.
This consistent experience with your brand can strengthen the long-term relationship between the user and the platform. By creating a tailored experience, personalized search becomes a key factor in retaining customers, ultimately contributing to the sustained success of the platform or business.
4. Tailored recommendations
For e-commerce websites, personalized search is not confined to textual queries. It also analyzes a user's previous search queries, product views, clicks, and purchase history. All this data collection provides insights into the user's preferences, interests, and user intent, forming the basis for personalized recommendations.
Additionally, search personalization utilizes cross-selling and upselling strategies. Cross-selling suggests complementary products that go well with what the user is already interested in, while upselling recommends higher-end or upgraded versions of products the user has shown interest in or engagement.
Furthermore, personalized search segments users into specific groups based on demographics, geographic location, shared characteristics, and behaviors. This segmentation allows the system to create targeted product recommendations for each customer segment, ensuring that suggestions are relevant to the specific needs and tastes of different user groups.
5. Adaptable content delivery
Different users have different needs, and personalized search allows for adaptable, personalized content delivery. Whether it's adjusting language preferences, region-specific content, or highlighting trending topics based on user behavior, personalized search ensures that the content presented is not just relevant but also contextually appropriate.
6. Data-driven insights
Personalized search generates a wealth of personal data regarding user behavior, individual preferences, and trends. Leveraging this user data provides businesses with invaluable insights into customer needs and expectations. By analyzing these patterns, organizations can fine-tune their content strategy, digital marketing efforts, and personalized product offerings to better align with the evolving demands of their audience.
7. Continuous refinement through machine learning
One of the key strengths of personalized search lies in its ability to evolve over time. Machine learning algorithms power these systems, allowing them to continuously learn from user interactions and adapt to changing preferences. This AI-driven process ensures that the personalized search experience becomes increasingly accurate and attuned to individual users.
8. Positive impact on ranking factors
While traditional search engine ranking factors focus on general criteria applicable to a broad audience, personalized search takes user-specific information into account. Personalized search considers user engagement signals such as click-through rates, dwell time, low bounce rate, and interaction with search results.
If a user consistently engages positively with specific content, personalized search algorithms may rank that content higher for that particular user, tailoring the results to individual preferences.
Get started today
As search is such a critical component of customer experience today, integrating advanced search functionality can significantly reduce friction for customers and aid in finding information.
Sitecore Search, the AI-powered search engine that provides customers with highly relevant search results, allows companies to easily deliver faceted site search experiences. Improve their ranking results and turn the most valuable visitors into customers who learn, convert, and buy – all while reducing friction. With strong personalization features, Search employs artificial intelligence to predict the search intent of users.