Conversational AI

Conversational AI in Retail

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Nicklas Klemm
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Nowadays, when buyers shop in-store, they want an engaging, personalized experience, says the Retail Insider. Most Gen-Z consumers don't even think in terms of traditional channel boundaries–they increasingly evaluate brands and retailers on the seamlessness of the experience. 

Retailers that have adopted conversational AI to enhance customer experience are well-equipped to succeed as the new retail world continues to take shape. 

To meet the demand for timely service, retail brands are using both customer-facing AI-powered assistants (to help customers self-serve) and agent-facing AI tools (to get their people the information, context, and even suggested language to help customers faster). 

Source

Conversational AI in retail uses smart chatbots and voice assistants to provide instant human interactions. These tools help improve customer engagement, drive better business results, and streamline processes.

In this blog, we'll explore what conversational AI is in retail, its use cases, and choosing the right tool for implementation. 

What is Conversational AI in Retail?

Conversational AI in retail is artificial intelligence technology that empowers retailers to interact with customers through AI-driven chatbots and AI voice bots. These AI tools simulate human conversations with real-time assistance and improve the shopping journey.

At its core, conversational AI leverages advanced technologies, including:

  • Machine Learning: It's a subset field of artificial intelligence made up of a set of algorithms, features, and data sets that continuously improve themselves with experience. As the input grows, the AI platform machine gets better at recognizing patterns and uses it to make predictions. 

Based on the day of the week, the season, social media data, nearby events and customer past behaviour, these dashboard can provide a daily dashboard of suggested orders to a purchasing manager. 

  • Natural Language Processing: This is a method of analyzing with the help of machine learning algorithms. Through NLP, they can understand the context, sentiment, and intent behind user messages. 

For retail, this enables users to engage in conversations that feel natural as if they're interacting with a human.

This technology lays the foundation for building powerful, quick, and scalable voice assistants in retail. Now that we understand its basis let's discuss the future implications of using conversational AI in retail.

Future of Conversational AI in Retail

Retail brands can deploy conversational AI agents to help customers find items they're looking for faster than ever before and provide solutions based on their specific needs. 

One Salesforce study found that 92% of retailers are increasing their investment in conversational AI to enhance customer's shopping experiences. Leading use cases of conversational AI voice bots in retail include:

  • Personalized recommendations (66%)
  • Branded virtual assistant for customers (52%)
  • Customer analysis and segmentation (50%)
  • Personalized marketing and advertising (46%)
  • Multilingual agents for customer service (41%)

For instance, if a customer visits a computer manufacturer's online store with a special requirement–such as a 20-inch laptop with an i7 processor in black color–they could directly and more naturally interact with a conversational AI agent to find it instead of clicking buttons to set the filters themselves

Since conversational AI coordinates with the back-end systems, the agent would instantly suggest every suitable laptop that the buyer needs. After making a decision, the buyer can then ask the agent to place an order for in-store pickup at the nearest location. 

Interactions such as the above would be nearly impossible for a basic FAQ chatbot. By deploying conversational AI agents, retailers can provide the same quality of human-like, personalized support to every customer that they would receive from an employee during in-store interactions. 

Key use cases of conversational AI in Retail

Conversational AI helps shift from a system based on selling physical products in a limited and controlled world towards an interconnected digital world. These AI-driven systems, from chatbots to voice assistants, redefine how retailers interact with their customers. 

Here are some compelling use cases for conversational AI in the retail domain:

Personalized Shopping Assistance

One of the most impactful uses of conversational AI in retail is the ability to deliver personalized product recommendations. By analyzing customer data, AI algorithms can suggest and predict that align with a customer's personal needs and shopping habits. This not only enhances the shopping experience of the customer but also boosts sales for retailers by increasing the likelihood of conversions. 

Some of the ways conversational AI can be used for personalized shopping assistance in retail include:

  • Gift recommendations
  • Product recommendations
  • Complementary product suggestions
  • Outfit suggestions
  • Size and fit assistance

Case study: L'Oréal’s Beauty Gifter

L'Oréal, a beauty company, recognized the opportunity offered by conversational marketing to connect with their customers, get to know them as individuals and promote ongoing relationships. 

They launched an innovative messaging bot for Facebook Messenger called Beauty Gifter–a chatbot that gets to know each user's needs and preferences and makes personalized recommendations from 11 different L'Oréal brands. You can either send voice notes or text messages to quickly communicate it with the agent. 

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Results: Beauty Gifter chatbot case studies results show 27X higher engagement than email, 31% rich profiling, and 82% loved the experience.

Inventory and Order Management

There are a number of repetitive tasks that go along with order management that can be automated using AI chatbots. Once you integrate your ERP/CRM with your AI agent, they can use the power of machine learning and NLP to automatically utilize order numbers and product names, provide confirmations, and more. 

Conversational AI in retail helps retail brands:

  • Handle high volumes of inquiries and queries like order placement, confirmation receipt, order tracking, order reminders, and notifications. 
  • Eliminate human errors in processing data.
  • Take bulk orders without any human intervention.
  • Keep a real-time view of the stock levels in the inventory. 

Automating your order management with AI chatbots reduces manual efforts significantly. While the business is scaled up and costs are reduced, the order management team saves a lot of time and achieves a high level of productivity. 

Case study: HelloFresh's 'Freddy'

HelloFresh is a subscription box that delivers fresh ingredients to the door, along with instructions to transform it into a delicious dish. It has launched an agent named "Freddy" to cut wait times for customers. 

Freddy can respond automatically to numerous customer queries, and many customers interact with the bot before speaking to a human customer support representative. 

Source

Results: 76% decrease in response times, even though they now get 47% more messages on Messenger

Customer Feedback and Engagement

A recent report shows that 30% of customers change their usual retail store to meet their needs. That's why understanding how a customer feels about your products is crucial to align with their needs. 

AI-driven tools can process and analyze large volumes of customer feedback from various sources such as reviews, surveys, social media, and customer support interactions. This analysis helps retail businesses understand customer preferences and pain points, which can be used to improve customer experience. 

Case study: Ben & Jerry

Ben & Jerry's is an ice cream brand that implemented an agent with their first messenger marketing campaign to provide great customer service. They started by running both organic and paid social posts to drive awareness. Customers who engage with the posts will be sent a handful of chat messages outlining the new flavors and getting feedback on what they want to try. It would then provide a coupon and a free pint slice of that flavor.  

Source 

Results: There was 5 times more engagement on social media over this period, with over 13,000 people interacting with the brand. All 5,000 of the free slices were snapped up, and sales over delivered by 20%. 

Key Benefits of Conversational AI in Retail

Retailers are constantly pressured to deliver personalized, seamless experiences while optimizing operations. Conversational AI bridges that gap by providing scalable, efficient, and customer-centric solutions. It empowers brands to enhance engagement, boost satisfaction, and drive exceptional operational excellence. 

Improved Revenue and Customer Retention

Conversational AI plays a crucial role in customer retention by empowering businesses to understand their customers better and tailor their experiences. AI-powered agents can analyze vast amounts of data and provide valuable insight into customer behavior, preferences, and pain points. 

Conversational AI isn't just about support–it drives revenue by proactively engaging customers. From upselling to personalized promotions, it helps retailers maximize revenue opportunities. 

Case study: Alibaba's "AliMe"

Alibaba, an e-commerce platform, has more than 550 million active customers and millions of active sellers that generate millions of transactions. 

Given the rising customer service demand, Alibaba launched "AliMe," the artificial intelligence chatbot that analyzes large amounts of data to predict customer service needs and reach out to customers. Therefore, AliMe can send users precise service information even before users have even asked for help.

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Results: Alibaba could generate US$31 billion gross merchandise volume (i.e., the dollar value of total transactions), 27% higher than the previous year.

Enhanced Operational Efficiency

Conversational AI can enable operational efficiency by automating routine tasks, such as password resets or access requests. This can help free staff to focus on more complex issues, improving businesses' productivity. Conversational AI can also assist in monitoring and analyzing user behavior over time, providing insights that can help retail businesses fine-tune marketing and sales campaigns. 

Automating routine and repetitive tasks like FAQs, order status, and return inquiries reduces costs by up to 30%. These virtual agents serve as an invaluable support system, offering real-time guidance on optimal customer service. This dynamic support ensures round-the-clock availability for their queries and support needs. 

Case study: 1-800 flowers.com chatbot to drive sales 

The flower delivery company built an e-commerce chatbot that allows customers to order flower arrangements right within Facebook Messenger. It allows customers to choose bouquets and enter delivery information and instructions that they want the card to say. 

Result: Within only a few months of launching the shopping chatbot, more than 70% of their Messenger orders were from new customers.

24/7 Omnichannel Customer Support

Today's consumers (88%) say they are more likely to purchase from businesses that connect their interactions across phone, email, and messaging platforms (text messages, WhatsApp,

Facebook Messenger), on websites, or in-app messaging.

Source

Unfortunately, 70% of customer interactions are traditional call centers. With conversational AI agents and voice bots, you can extend your customer service beyond the traditional 9-to-5 window and deliver customer support 24/7, even when reps are not available. 

Here are just a few examples of of what well-trained AI chatbots and voice bots are capable of:

  • Responding to Frequently Asked Questions (FAQs)
  • Handling returns and exchanges
  • Setting and rescheduling appointments
  • Providing order information and delivery status updates
  • Booking and confirming reservations
  • Renewing subscriptions

Case study: Decathlon's chatbot for 24/7 availability 

Decathlon is a global sporting goods company that designs, produces, and sells a wide range of products for popular and niche sports. They collaborated with Heyday to create a chatbot that is available 24/7 to sign up new members and help customers shop. With this new chatbot, they wanted to provide a seamless shopping experience to its customers. 

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Result: Decathlon saw a 346% increase in member acquisition and an 8.5x reduction in the cost of customer acquisition compared to traditional channels. 

Choosing the right conversational AI platform for Retail

Implementing conversational AI tools in the retail sector requires selecting the right platform that meets the unique needs of e-commerce companies. Here are some of the critical factors to consider when choosing the right conversational platform:

FactorDescription Natural Language Understanding (NLU)Ability to comprehend customer queries in various formats (text, voice, multilingual support).Context awareness to handle complex or multi-turn conversations.Omni-Channel IntegrationSeamless support across platforms (e.g., website, mobile app, social media, messaging apps like WhatsApp, Facebook Messenger, etc.).Retail-Specific FunctionalityAbility to understand and refine:Product Search & FilteringCart ManagementOrder TrackingScalability & PerformanceHandle a large volume of simultaneous conversations without compromising quality.AI-Driven InsightsAnalytics dashboard to track key performance metrics like conversion rates, customer satisfaction, and frequently asked questions.

Why choose voice AI Synthflow?

To summarize, conversational AI is more than just a tool, it's a revolutionary catalyst benefiting the retail landscape. As the retail industry continues to evolve, those leveraging the capabilities of conversational AI are poised to lead this exciting area of retail excellence. 

And, if you’re wondering about your next steps as a retailer, think of a conversation AI solution that provides a seamless conversation between a brand and its customers. 

Synthflow's no-code, drag-and-drop interface allows users to set up a AI voice agent in minutes without needing any technical knowledge or coding ability. It can seamlessly handle a large volume of calls across all timelines and languages.

Features:

  • Zero latency
  • Text-to-speech and advanced transcription features
  • 11labs integration – clone voices and automatically schedule appointments into your calendar
  • Robust customer support
  • Advanced call sorting, logging, and transferring
  • Generate responses and action them live in call
  • Resell Synthflow – fully white-labeled version available
  • CRM Integrations – High Level, HubSpot

Want to try a free demo to see how you can replace your traditional call centers with AI voice bots? Sign up here.

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Effortless Human-Like AI Phone Calls

Build a no-code AI phone system with our AI voice Assistants: stop missing calls and start converting more leads