What don’t you like about the ecommerce experience right now? Is it the lack of customer service and product experts? Perhaps it’s the frustration of being unable to physically touch, feel, or try on the product before purchasing. Or maybe it’s the hassle of returning items. Whatever the reason, it’s clear that traditional ecommerce has room for improvement, but that doesn’t detract from its massive potential.
The fact of the matter is that shoppers prefer a product expert and are still going to stores — only 17% of retail revenue is online. But there is so much room for growth here. So, what if there was a way to bridge the gap — to combine the convenience of online shopping with the personalization and expertise of in-store interactions?
That’s where conversational commerce comes in. With the power of generative AI (GenAI), modern shopping assistants can seamlessly help customers discover exactly what they need, whether it’s a specific product or information for a range of products they’re interested in researching.
Read on to learn more about the current challenges with product search, how conversational commerce addresses these issues, and how to differentiate between the various AI-powered solutions available.
The Problem With Product Search Today
Did you know that only about 3% of website visitors end up making a purchase? It seems like a pretty dismal number when we look at the percentages coming out of peak season times, like Black Friday and Cyber Monday, but this stat illustrates how different website visitors have varying needs, as well as the glass half-full outlook: the pure potential of ecommerce.
Now, some visitors to your website are “searchers,” who know exactly what they want and use specific keywords to search for those products. Others are “seekers,” who often have a vague idea of what they need but require guidance to complete their search.
Unfortunately, seekers are often left in the dark by ecommerce websites because they encounter:
- A lack of product expertise — Many seekers struggle with a lack of product expertise or having access to someone with it, hindering their ability to make informed purchasing decisions.
- Too many options — When consumers are bombarded with an overwhelming array of options, they can come down with analysis paralysis. This is when an abundance of choices — while seemingly beneficial — ends up feeling too daunting and consumers are unable to make a final decision.
- Limited product discoverability — Because seekers don’t know exactly what to search for, they need other ways to find the products they want. Many ecommerce sites don’t give consumers enough ways to “window browse” or receive tailored recommendations as one would from a salesperson in a physical store, which is a significant void in current online shopping experiences.
So how can you start addressing the experience gap for online shoppers (and in particular, the seekers)? The good news is that the rise of GenAI and conversational commerce has made it easier than ever to address these product search shortcomings.
Finding the Solution in AI and Conversational Commerce
While many of the problems with ecommerce websites and search bars could be attributed to growing pains in the past decade, that excuse can’t be used anymore. That’s because generative AI has come a long way. Large language models (LLMs), one of the most advanced and widely applicable types of generative technologies, are transforming search engines by enhancing their understanding and processing of queries. Moving beyond keyword-based searches, LLMs focus on parsing natural, conversational language to grasp the broader topics and themes that shoppers are interested in.
In combination with natural language processing, this results in conversational AI, which excels in understanding and processing user queries in a more human-like manner. This allows customers to describe their needs in their own words, moving beyond the limitations of traditional search bars that can be a hit or miss in interpreting customer intent. Conversational AI goes a step further by asking clarifying questions and refining search results more effectively. This approach reduces the friction associated with searching for products online and guides customers to the products they’re seeking, mimicking the personalized assistance received in a brick-and-mortar store.
By incorporating a conversational shopping agent into the customer journey, ecommerce sites can offer personalized advice and answer specific product-related questions in real time. These conversational agents can educate customers on product features, benefits, and other important details and close the knowledge gap for seekers. Furthermore, conversational shopping assistants can provide recommendations based on the customer’s needs, further enhancing their ability to make well-informed decisions and increasing opportunities for upselling. This personalized guidance is key to simplifying the decision-making process and reducing analysis paralysis, resulting in a much more enjoyable and efficient online shopping experience.
What Capabilities Should an AI Shopping Assistant Have?
Conversational commerce can potentially change search (and ecommerce as a whole!) as we know it today. Instead of relying solely on keywords and algorithms, conversational assistants understand the context of a customer’s query and provide relevant results based on that understanding. This means that customers can express their needs in natural language, using phrases they would use in everyday conversation instead of tailoring their thoughts to meet the requirements of the search bar.
So, what features should you look for before investing in an AI shopping assistant? Here are a few we’d keep an eye out for:
Drives Conversational Awareness
Conversational awareness allows AI shopping assistants to understand and respond to human conversation in a contextually appropriate manner. This involves being able to process the meaning of words, as well as grasp the nuances, intent, and subtleties of the overall conversation.
Delivers a Conversational Experience
Delivering a conversational experience is about crafting interactions that go beyond mere exchanges of words. It’s an art and science that combines understanding, engagement, and personalization to create a seamless journey for the customer. This comprehensive approach is about creating an enriching dialogue with deep product knowledge, insightful comparisons, and personalized recommendations.
Exemplifies Tone Influence and Verbiage Control
Tone influence and verbiage control refer to the ability of a shopping assistant to adapt its language and tone based on the context of the interaction, the perceived mood or preferences of the customer, and your unique brand. This includes choosing words and constructing sentences that are appropriate for the situation (i.e., formal vs. informal) and adjusting the tone to be empathetic, authoritative, friendly, or neutral as needed to mirror the in-store experience.
Capable of Historical Conversational Context
Retaining historical conversational context means preserving the thread and details of past interactions within ongoing conversations. This capability allows shopping assistants to reference previous dialogue, understand the progression of the conversation, and provide coherent and contextually relevant responses over time.
Contains Conversational Data Storage (Per Person)
Conversational data storage allows businesses to tailor their communication and recommendations to each customer on a 1:1 basis by keeping track of individual interactions, preferences, and purchase history. In turn, this helps practitioners leverage conversational shopping assistants to create a seamless experience for the customer, making shoppers feel valued and understood.
Includes Conversational Performance Analytics
Conversational performance analytics play a major role in understanding and optimizing the effectiveness of conversational commerce strategies. By analyzing metrics such as response times, conversion rates, and customer satisfaction scores, businesses can identify strengths and areas for improvement in their approach.
Upholds GDPR Compliance
Ensuring GDPR compliance in conversational commerce is essential for protecting customer data and maintaining trust. GDPR compliance means that all conversational interactions, data storage, and analytics practices adhere to strict data protection regulations, including obtaining explicit consent for data collection and processing, providing data access and erasure options, and ensuring data security.
What Sets Bloomreach Clarity Apart From the Rest?
As you explore options for integrating conversational commerce technology into your ecommerce strategy, it’s vital to identify features that align with your business needs and enhance customer engagement — and of course, increase revenue and return on investment.
Here’s why Bloomreach’s conversational shopping assistant, Clarity, is different from any other option you’ll find on the market.
It Engages Customers at the Right Time
The conversational product you choose should differentiate itself by engaging customers at pivotal moments in their shopping journey. By identifying key actions — like cart abandonment or extended browsing on a particular product page — Clarity initiates timely conversations to guide customers forward. This approach offers personalized support when customers are most receptive and encourages them to complete their purchases. By addressing hesitations and providing needed information at critical points in their journey, Clarity enhances the shopping experiences and boosts revenue for your business.
It’s Customizable to Your Business
Your brand is unique, and your AI shopping assistant should reflect that. Bloomreach Clarity is designed to understand your business nuances and tailor its tone, responses, and conversational flow to mirror your brand’s voice and objectives. This level of customization ensures that interactions are not only helpful but also reinforce your brand’s identity — something that’s becoming increasingly important in the ecommerce space.
It Truly Personalizes the Shopping Experience and Recommendations
Personalization is the cornerstone of effective marketing. An AI shopping assistant should go beyond generic recommendations to offer truly personalized shopping experiences. Leveraging technologies like Bloomreach’s customer data engine allows Clarity to understand individual customer preferences, browsing habits, and purchase history. This deep, unique insight enables the delivery of highly relevant product recommendations, enhancing the shopping experience and boosting conversion rates.
It Delivers a Seamless Shopping Experience
When it comes to ecommerce, most of us know that reengaging customers at crucial moments can significantly impact sales and loyalty. Your AI shopping assistant should be adept at initiating meaningful conversations at key points in the customer journey. Whether it’s addressing hesitations before a purchase, offering assistance in finding products, or providing after-sales support, Bloomreach Clarity easily integrates into any part of the shopping experience.
It Has Unparalleled Ecommerce Expertise
If you’re investing in conversational commerce, your brand should benefit from its ecommerce expertise. Don’t overlook a solution that offers out-of-the-box functionality — Clarity, for example, comes equipped with what we call “day zero learnings.” Bloomreach’s day zero learnings offer a rich understanding of consumer behavior and product knowledge — gatherer over our 15+ years in the ecommerce industry — to ensure that Clarity is effective from the moment it’s deployed.
It Has Rich Insights and Analytics
To continually refine and optimize the shopping experience, real-time analytics are essential to your AI shopping assistant. Thankfully, Bloomreach Clarity provides comprehensive insights into customer interactions, preferences, and the driving forces behind their decisions. This data is invaluable for making informed adjustments to your strategy, ensuring your offerings remain aligned with customer needs and market trends.
Bloomreach Clarity Is the Future of Ecommerce
Choosing the right AI shopping assistant for your ecommerce strategy is about finding a balance between customization, personalization, seamless integration, industry expertise, and actionable insights. By prioritizing these capabilities you can transform the shopping experience on your website, driving customer engagement, brand loyalty, and revenue for your business. As ecommerce continues to evolve, leveraging AI in this way won’t just be an option — it’ll be essential to staying competitive and meeting the ever-increasing expectations of savvy online shoppers.
Are you ready to unlock the future of personalized shopping with Bloomreach Clarity? Join the waitlist today to transform your customer conversations and drive confident purchases. Now’s the time to harness the power of GenAI to understand and engage your shoppers like never before.