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Go beyond a regular ecommerce chatbot: Lead the future of online retail with AI in 2024

Sarah Fox
Content Producer
Customer Experience | 12 min read

Investing in a powerful AI-first strategy for ecommerce is a non-negotiable. It’s a key customer experience driver, and 94% of customers are more likely to buy from a brand that delivers a great customer experience.

Before you start searching for ecommerce chatbots on Google, take a pause — we’ve got news for you: The market is riddled with subpar scripted chatbots that can do more harm than good.

Luckily, we can help you find the best chatbot for your ecommerce website. Spoiler: it’s not just a chatbot. Here’s how an AI agent can give you an edge over competitors.

Ecommerce chatbot, or something better?

An ecommerce chatbot is an application that answers customer’s questions, suggests products, and requests feedback. Ecommerce chatbots can be scripted, like we mentioned above, or it can be more — much more.

Scripted bots follow predefined conversation flows, while generative bots (or AI Agents) use reasoning — AI and natural language processing (NLP) — to understand, respond, and take action on customer queries and solve complex problems.

Scripted chatbots are an ancient concept. They’re no longer relevant. You need an AI agent to deliver the kind of service modern customers expect . Wonder why? Because modern customers want fast responses, and you can’t deliver fast responses at scale without an AI agent.

A study by Jay Baer confirms that 67% of customers believe speed is as important as price. During an interview , Baer even said speed is the most important element of customer service — 50% of customers won’t spend money with a business that takes longer to respond than they expect.

Let’s be very clear: Responding quickly to customers doesn’t differentiate you. It’s a basic customer expectation. Quick responses merely put you in the race. To win, you need more than just speed from your AI agent.

Why do you need an AI agent for ecommerce?

AI is a necessity, not a “nice to have.” Some of your competitors might have already implemented AI across their stores to improve customer experiences. The key here is to go a step further than your competitors by using an AI agent that uses cutting-edge tech to deliver personalized and immersive customer experiences.

By 2027, chatbots will become the primary customer service channel for roughly a quarter of organizations.

- Gartner

Here’s how AI agents help improve customer experience and streamline customer service processes:

  • Customer support: Your customers want quick answers. They hate waiting in line while your agents deal with other customers. There are two ways to deal with a busy service desk: hire more agents or use an AI agent. Hiring more agents is expensive and not scalable, while an AI agent can scale as you grow and has a fixed cost.
  • Personalized experience: AI agents analyze customer preferences and behavior to find and suggest relevant products. This helps deliver a personalized experience to shoppers and visitors, which improves your store’s conversion rate.
  • Streamline purchases: AI agents help customers throughout the buying journey, from placing an order to requesting a refund. Your customers can interact with an AI agent just as they would with a salesperson in your store. For example, your customers can request product recommendations, place an order, and complete the payment.
  • Insights on customer preferences: AI agents collect valuable data when interacting with customers. For instance, an AI agent can help identify why a product isn’t selling well based on questions customers ask about that product. Maybe your customers prefer cruelty-free or toxin-free products — you can tell this is true when too many customers ask if your products are cruelty or toxin-free. Once you know why a product isn’t selling, you can either remove it from the store or modify it to meet your customers’ expectations.
  • Allows agents to focus on strategic tasks: AI agents can field almost all customer inquiries. Order status, refund requests, and questions directly related to your product — AI agents can tackle all of them. Deploying an AI agent frees up your customer service team to focus on things that require human touch, like monitoring and guiding the AI agent to improve Automated Resolution (AR).

AI use cases for ecommerce

An AI agent can:

  • Help customers place, modify, track, and cancel orders
  • Provide accurate answers when customers need help
  • Collect feedback
  • Suggest relevant products to cross-sell and upsell
  • Integrates with other tools, enabling automation

But that’s not what we’re going to discuss here. Our goal here is to help you stay ahead of the curve, so we’ll focus on innovative use cases.

AI agents as shopping assistants

A salesperson can’t help your customers buy products like in a brick-and-mortar store. But you can assist the customer virtually using an AI agent. Imagine this conversation between an AI agent and a customer:

Add an option that allows customers to rate these recommendations. The AI agent can use this as feedback to understand customer preferences.

This highly personalized assistance differentiates your customer experience and improves conversions.

Visual search

Visual search allows customers to search for products using images. It reshapes a customer’s shopping experience and makes it easier for a customer to communicate their needs.

Suppose you sell lamps. A customer is looking for a lamp with a specific design but doesn’t know how to describe it when using the search bar. The customer does have an image of that lamp, though. If your AI agent supports visual search, the customer can upload the image and request the AI agent to search for lamps with a similar design.

Manually finding a similar lamp can take hours. The customer would have to search through your entire inventory. In all likelihood, the customer might skip the purchase. Visual search reduces the time to a few seconds. Customers who would’ve left without a purchase might just go ahead and place an order, thanks to your AI agent’s visual search functionality.

With visual and voice search rapidly increasing in popularity, enterprises should experiment to identify the best ways to capitalize on this shift. Early responders will see an increase in conversation rates, revenue, new customers, and customer satisfaction.

- Gartner

Proactively engage customers

Notice how, when you visit some websites, a chatbot pops up asking if you need help with something? That’s an attempt to engage customers proactively. It’s an excellent way to deliver a personalized user experience, save time, and discover products your customers haven’t considered yet.

Picture this. You sell shoes. One of the customers has been frequently visiting the men’s shoes section but hasn’t made a purchase. When the customer revisits your website, the chatbot sends a personalized message: “Hey there! Noticed you’ve been exploring our men’s collection. Need help finding something specific? We’ve got some new arrivals you might love!” If the customer says yes, the chatbot acts as a virtual assistant and tries to close the sale.

Proactive engagement can also reduce cart abandonment. Ecommerce platforms have an average abandonment rate of 70.19% — proactive engagement can help close a good number of these sales and contribute to your top line. If a customer has items in the cart but hasn’t checked out, the chatbot can remind them about items in the cart and offer help with any issues the customer is facing.

AI-powered predictive analytics

AI can analyze historical data, trends, and customer preferences to make smarter decisions. Brands like Macy’s have been using predictive analytics for over a decade. But AI amplifies the power of . Think of it as a crystal ball that gives you insights on the following:

  • Predicting trends: AI agents use data collected from customer interactions to predict upcoming trends. This allows you to stock up on trending items before the price shoots up and stocks run out.
  • Recommending products: AI agents offer personalized recommendations based on customer preferences and purchase history.
  • Managing inventory: Predictive analytics tells you the level of inventory required to meet demand for a specific product based on historical data. This ensures you never lose revenue because of a stockout or overstock slow-moving items.
  • Targeted marketing: Predictive analytics helps you understand a customer segment’s probable response to a targeted marketing campaign. Factor in the insights from predictive analytics when creating a marketing campaign to make it more effective.
  • Dynamic pricing: Striking a balance between price and demand is vital — you won’t sell enough if the price is too high, and you won’t generate enough return if the price is too low. That’s where dynamic pricing helps. Unfortunately, only 21% of ecommerce businesses use dynamic pricing. 

The key is to price the product based on demand, competitor pricing, and customer behavior. AI can bake in all of these factors and determine a dynamic price that allows you to stay competitive and maximize profitability.

"Shifting to these novel pricing approaches [like dynamic and personalized pricing] can increase company profits by 3-25%."

- Arnd Vomberg, Assistant Professor, University of Groningen

Features to look for in an AI agent

Modern AI agents are packed with features. Let’s talk about a few essentials to look for:

  • Natural language processing (NLP): NLP enables chatbots to interpret natural language. When a customer says, “Help me find some shades,” NLP helps the AI agent understand the customer is referring to sunglasses.
  • Omnichannel compatibility: Customers often use channels other than your website to get in touch. They might reach out via your mobile app. Or if you’re running Facebook ads, they might message you on Facebook. Select an AI agent that works on all popular channels.
  • Media support: Select an AI agent that can handle rich media formats so customers can share images and videos. The ability to share visuals makes it easier for customers to explain themselves and provide additional context.
  • Analytics and reporting: Analytics helps assess the chatbot’s performance. It also helps your customer service team identify the most common queries and understand customer preferences.
  • Integrations and APIs: Integrating your chatbot with your tech stack (CRM, ERP, what have you) allows you to capitalize on existing data. This allows the chatbot to modify information in the CRM — zero manual effort.
  • Security and compliance: Compliance with security standards like GDPR and HIPAA and robust encryption protocols ensure the safety and privacy of customer data.

Redefine customer experiences with an AI agent

Research shows 80% of customers consider the experience a company provides as important as its product or service. A winning product brings traffic to your ecommerce store. But immersive and personalized customer experiences convert those visitors into paying customers.

An AI agent is your silver bullet to over-delivering on customer expectations. Differentiate yourself with an AI agent that offers more than just the basics.

Guide to interviewing an AI agent

Understand the differences between chatbots and AI agents, and discover the success criteria you need to get the best ROI.

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