Today’s direct-to-consumer (D2C) brands are finding themselves in a race to meet rapidly evolving customer expectations. For these brands to succeed, capitalizing on how customers search for and discover products is no longer a matter of constant adjustments and optimization. Technology has arrived to completely revolutionize how brands can better understand customer intent, present the right products at the right time (and even in the desired tone of voice) and leapfrog competition.
This is where natural language search (NLS) technology can be a game changer for brands.
Brands Are On The Back Foot When It Comes to Building Owned Experiences And Their Websites
We’re speaking to some amazing and successful brands every day to better understand how we can help redefine their owned experience using our technology. It’s clear to us, brands are experiencing several challenges, particularly in how they manage their owned platforms and websites and especially, how they capitalize on site search functionality to enable highly converting product discovery:
- Current brand website search functionality is underperforming: Many brand websites struggle to create search experiences that are intuitive and satisfying for users. As a result, they miss out on substantial revenue opportunities. 15% of Total Visitors Used On-Site Search, But These Visitors Accounted for 45% of All Revenue, according to AddSearch. Brands are leaving money on the table by not investing in better search functionality.
- Quickly evolving customer behavior: Shoppers today expect efficient, conversational, and intelligent search (customers are not Boolean query experts!). Brands are falling behind and are struggling to evolve past search experiences implemented decades ago. 90% of U.S. consumers say that a good search function is critical to their loyalty (Google Cloud). And 84% of customers want to solve their own problems using search (AddSearch). Without a robust search, customers are heading elsewhere to find that magical item.
- Overwhelming product catalogs: As brands scale, their product catalogs and inventory grow exponentially, which makes managing and making these easily searchable a monumental task. 70% of desktop e-commerce search implementations fail to deliver results effectively, frustrating both customers and brands alike (Baymard Institute).
- AI-driven expectations: The demand for AI-enhanced shopping experiences is rapidly rising. 88% of Gen Z and 77% of Millennials believe AI can enhance the discovery process and help them find products faster (Harris Poll). However, many brands are hesitant to test or deploy AI that can potentially help drive growth in their business. (Hopefully this post helps with that a little).
How Is This Impacting Brands?
These pain points are materializing in tangible ways across brands ecommerce experiences:
- Increased bounce rates: Poor search experiences lead to high bounce rates and missed conversion opportunities. Consumers are abandoning websites that cannot meet their needs, within a matter of seconds. Bounce rates are averaging 40% with 190 seconds average session time (Cart.com).
- Customer churn: Brands without seamless search functionality are losing customers to competitors with more sophisticated and intuitive solutions (61% of consumers will start a search to buy on Amazon.com - eMarketer)
- Missed sales opportunities: Brands with large product catalogs struggle to showcase relevant items to customers, which not only impacts conversion, but can also result in missed cross-sell and upsell opportunities.
- Competitive disadvantage: Companies leveraging AI are set to outperform those that are slow to adopt new technologies. There’s an emerging gap for more agile brands to win over modern customers who wish to adopt this technology, whether as part of existing experiences, or as part of something completely new. Nearly all - 99% - of major retail executives believe there will be a spike in technology investments in the next year (Wakefield Research).
Why Brands Must Act Now And Create Better Search Experiences
In an era of instant gratification, brands cannot afford to fall behind. Enhancing a search experience is critical for several reasons:
- Customer retention: As consumers increasingly value speed and relevancy, brands without optimized search functionality are at risk. 75% of online shoppers will not return to a site if they have a poor search experience, and frustrating search experiences will result in a customer churn rate of 68%, according to Forrester.
- Revenue impact: Optimized natural language search can significantly increase conversion rates by understanding shopper intent and delivering highly relevant results. Brands that invest in these technologies now will see a higher return in average order values and increased customer loyalty. Customers who use search result in an average conversion rate of 2.4% versus 1.7% for customers who don't, often a 50% increase (eConsultancy).
- Future-proofing: AI is no longer a “future” technology—it's already here. Brands that wait too long to implement or prepare their product data for AI-enhanced search will be left behind.
How Natural Language Search Is Set To Change Brand Experiences Today
In an ideal world, brands should be aiming to:
- Deliver personalized search experiences: Customers want search interactions that feel natural and cater to their unique preferences. This means integrating natural language search (NLS) technology that helps users find exactly what they’re looking for, understanding specific terms or use cases, and then capitalizing on an engagement with a customer that continues to enhance their product discovery experience.
- Simplify product discovery: With potentially massive product inventories, it's crucial for brands to streamline how users find products. Product walls and grids with excessive filter options simply don’t cut it anymore. Natural language search can help by interpreting complex queries, understanding context, and providing the most relevant results for customers.
- Leverage AI strategically: AI isn’t just a buzzword; it’s a tool that can transform ecommerce by providing contextually aware, smart, and anticipatory search experiences. By analyzing customer behavior in real-time, brands can tailor product suggestions to individual preferences, increasing engagement and sales.
- Learn even more about the customer. Until now, brands have relied on optimizing experiences against basic search terms or excessive product filters. Only 7% of companies report learning from site search data according to eConsultancy, and using that data in other areas of their business. In the future, brands will be able to analyze complex conversations with customers to identify deeper insights, helping them further optimize the experience, and cater to fluid customer demands.
How Commotion Is Leading the Charge with Natural Language Search Experiences
Commotion is designed to address these pain points directly, helping brands leapfrog competitors by easily building experiences powered by AI and natural language search.
With Commotion, brands can:
- Create intelligent, conversational search experiences: Commotion enables brands to build cutting-edge search capabilities that understand user intent, delivering faster and more accurate results. These can replace existing search journeys, and be triggered from a number of different experiences across your site or app to launch more conversational, and contextual interfaces. Our Enterprise tool gives brands the ability to expand upon templated experiences and easily and efficiently deploy them without burdening internal technology and developer teams.
- Streamline product catalog management: Commotion’s data refinement technology helps brands optimize product catalogs and product data of all sizes, ensuring products are correctly tagged, and users find what they need quickly and easily. Additionally, we’re helping brands attach customer behavior to product data for advanced capabilities. For example, identifying how or why people search for specific products in your catalog and what terms or use cases they describe in context of each product.
- Integrate advanced AI capabilities: Commotion builds custom AI and large language models (LLMs) to drive personalized product discovery, tailored to each shopper’s behavior and preferences. By combining natural language search with additional customer signals (such as engagement, clicks, views etc) Commotion can help brands truly personalize conversational experiences beyond just search results, integrating with support, chat or even more content focused experiences such as shoppable video.
- Access deeper, more meaningful customer insights. Combining natural language search with expansive product catalogs and layering customer signals as they shop and browse, enables brands to not only provide more personalized experiences in real-time, but also gather and manipulate this data to drive deeper customer insights.
Now’s The Time For Brands To Leapfrog Ahead Using AI-Powered Natural Language Search
Natural language search is not a luxury—it’s a necessity for brands that want to stay competitive. As customers continue to demand more intuitive and responsive ecommerce experiences, brands that fail to act, risk excess inventory, increased cart abandonments, and ultimately, a poor online experience.
Brands may also stand to lose the opportunity to forge a new type of engagement.
In a similar way to how social media revolutionized communication between brands and customers, we believe AI and Natural Language Search will once again impact the opportunity for brands to build new types of customer relationships within their owned platforms.
At Commotion, we’re helping brands create more contextual and personalized ecommerce experiences, and natural language search is just one part of our unified technology.
Get in touch for a demo of Commotion's Natural Language Search experience.
