9 ways AI elevates the retail customer experience

The fact is, AI has long been providing enhanced customer experiences for brands, helping agents work more effectively, resolve customer issues more quickly, reduce costs, and build customer loyalty.

In this article


Within five days of OpenAI releasing ChatGPT free to the public, more than a million people had asked the artificial intelligence to help them with travel plans, computer code, and writing stories. But AI isn’t exactly new in retail and other industries, which have been using data analytics and machine learning to improve customer experience for years.

According to Statista, worldwide AI revenues could reach $1.5 trillion in 2030. Generative AI, such as ChatGPT, is expected to make up about 9% of that total. Other types of AI include computer vision, robotics, deep learning, and predictive AI.

The fact is, AI had already been providing enhanced customer experiences for brands of all sizes. Applied AI helps humans in myriad ways to work more effectively, resolve customer issues more quickly, reduce costs, and build customer loyalty. But the heart of great CX is still human.
Retailers heavily leverage 9 avenues for AI
These use cases demonstrate where AI can shine:

1. Churn reduction: Knowing which customers are at high risk of bailing from a store, website, or the brand itself helps reduce churn. AI tools combined with customer interaction analysis help track customer engagement and send out offers designed to prompt re-engagement.

2. 24/7 customer service via chatbots: Chatbots have come a long way since the days of Microsoft’s Clippy, the office assistant paperclip that would never leave the corner of your computer screen. Today, with AI, chatbots handle more complex interactions and can be trained on your FAQs or knowledge base to skillfully handle more scenarios or direct customers to the correct resource. But human agents are still critical for many situations.

3. Intelligent call routing: AI-based platforms identify customer intent, sentiment, and language to automatically route calls to the right CX team members as quickly as possible. And they can filter spam messages so agent time isn’t wasted.

4. Coaching: Once calls reach a human, AI-based assistants “listen” to the conversation and help guide the calls, including quickly pulling up knowledge base information that the agent can use to answer questions. They offer suggestions for de-escalating a call if emotions run high.

5. Demand forecasting: Predictive analytics can comb through vast amounts of historical data to help retailers make projections on how much product to stock.

6. Inventory management: Machine learning helps retailers more precisely track current sales, historical sales trends, and logistics so they can fine-tune their product inventory and ensure the right amount of supplies are available.

7. Opinion mining: AI sifts through numerous sources from public review sites, social media posts, internal user surveys, support tickets, and caller sentiment to uncover potential friction points as well as positive differentiators for your brand. It can perform similar analysis on competitors to provide insights into what your customer base values.

8. Personal assistant for employees: As in other industries, retail companies can challenge their employees to experiment with generative AI to see what tasks it can help them with. Walmart, for example, has given its corporate employees a generative AI-powered tool to help speed up processes and to serve “as a creative partner.”

9. Personalized product recommendations: Amazon and Netflix use their algorithms to suggest products or movies based on customers’ browsing history. By applying AI to consolidated customer data, from sources such as loyalty and credit card programs and email and SMS lists, retailers can offer even more granular recommendations.

Caution Ahead: The potential pitfalls of AI in CX
There are many advantages to using AI in CX. But we’re by no means about to take smart, empathetic, well-trained humans out of the picture.
Even the best chatbots can leave customers frustrated or confused. And if brands adopt customer-facing generative AI without adequate training, testing, and safeguards, they risk playing a starring role in an embarrassing news story or social media post.

The new generative AI tools sometimes produce inaccurate answers and can replicate the biases they were trained on. There are also concerns that as AI takes on more of the workload, companies could run afoul of consumer protection laws, for instance by suggesting inappropriate financial products for a bank customer.

And no AI tool possesses the genuine empathy needed to help customers with difficult, complicated, emotionally fraught situations.
Why it matters

45% of executives say ChatGPT has prompted an increase in AI investment.

The global AI market could reach half a trillion U.S. dollars by 2024 and could grow to over 1.5 trillion U.S. dollars by 2030.

By April of 2023, a third of organizations surveyed were using generative AI regularly in at least one business function.

AI in retail is forecast to reach $57.8 billion by 2030, with predictive merchandising currently accounting for the largest share of the market as companies seek more proactive methods of stocking the products that fly off their shelves.

The most common focus of generative AI investments was customer experience (CX)—cited by 38% of executives in a Gartner survey.

Retail especially is turning to generative AI to enhance the shopping experience and help improve back-end decision making.

How Ubiquity uses AI and other technology to improve CX
Ubiquity is well positioned to help you take advantage of AI opportunities while remaining focused on your most valuable CX resources: carefully recruited and well-trained human CX agents.
We deploy technology wisely to provide the most efficient, effective service for our clients. Our artificial intelligence platform seamlessly integrates with existing telephony and customer relationship management (CRM) systems, actively listening to calls and helping agents perform their best, in real time. Using machine deep learning, our AI coaching continuously improves with each customer interaction. Its custom speech model is designed specifically for contact center customer support.
Our secure platform features four core tools to help agents in the moment make interactions quicker, more informed, and always compliant.

Real-time Coach supplies pertinent guidance and information to agents as they are working with clients.

Process Genie instantaneously sifts through an unlimited, cloud-based scenario library and built-in knowledge database to help agents of any experience level support myriad programs or unique brands as if each one were their specialty.

Call Monitor detects trigger words and sentiments likely to lead to complaints and provides tips for disarming the situation or routing the call to the appropriate team quickly.

Transcription IQ makes quality assurance and compliance audits much more efficient, accurate, and actionable with automatic call transcription into a searchable database (without sensitive data).

Ubiquity-designed technologies like inTouch® management platform and inCall interactive voice response (IVR) can easily share and analyze data that other AI systems use to improve the customer experience.

inTouch: Our agent performance monitoring and management app connects supervisors and managers with their customer service agents to identify and solve issues in real time, provide coaching, monitor performance KPIs, and support teams in realizing their potential.

IVR: Our interactive voice response solution is custom-designed to meet individual business needs and KPIs. It reduces operational costs, streamlines information for more efficient service, and empowers agents with more context about a customer’s journey and intentions to determine the best outcome and help increase first-call resolution.

Leverage innovative approaches to CX and learn more about the Human Side of AI.

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