Over the past year, consumers’ expectations of retailers have elevated, putting a spotlight on the importance of delivering exceptional customer experiences across every channel.
The margin for error is thin: one study shows that 50% of customers will switch to a competitor after just one bad experience. Conversely, delivering a personalised and engaging experience ensures that customers keep coming back.
With higher uptake of e-commerce, fierce competition and tight margins, retailers need to use smart technology to create rich and personal customer experiences with efficiency and at scale. With artificial intelligence and machine learning (AI/ML), retailers can give consumers a tailored experience across every channel while elevating automation across the business.
AI/ML solutions can also help retailers to identify patterns in vast streams of data that would otherwise be difficult to identify and provide their employees and business leaders with rich insights that they can use to shape customer engagements.
Let’s take a closer look at some of the most powerful AI/ML use cases for retailers that want to transform their customer experience.
Recommendations
When done well, product recommendations can lead to higher basket values, revenue growth and higher customer satisfaction. But when they’re done badly – for example, suggesting an inappropriate product or nudging a customer to buy something they’ve bought already – they can annoy customers and even drive them away.
Smarter AI/ML recommendation solutions like Recommendation AI from Google Cloud delivers high-performing recommendations at any customer touchpoint including the website, mobile experience, email and contact centre – no manually curated rules or cumbersome recommendation models required.
Recommendations will be more accurate and lead to higher levels of cross/upsell and conversion.
Watch to see how Hanes delivers personalised shopping experiences to their customers with Google Cloud Recommendation AI:
AI in the contact centre
In today’s on-demand world, customers expect a rapid response when they get in touch wanting to return a product or get support for the new widget they bought. Conversational AI chatbots and voice assistants can enable a retailer to process customer requests 24/7 within a matter of seconds – and with no need for customers to wait for a human operator. AI assistants will be able to quickly deal with routine queries, allowing humans to focus on the more complex cases. AI assistants can also provide real-time, step-by-step assistance to human agents as they navigate customer calls.
One solution being Google’s Contact Center AI:
Visual product search
Consumers today find product inspiration from many sources, including retailer websites and social media platforms. Visual search allows them to search for products with an image and receive a ranked list of visually and semantically similar items. It uses ML-powered object recognition and lookup to provide real-time results of similar, or complementary, items from retailers' product catalogue.
https://youtu.be/9R_Q2Eh777s
AI can play an important role in improving retail experiences, from delivering personalised messaging early in the customer journey when the customer is discovering a need or product to enriching in-store interactions with augmented reality experiences or smart checkouts.
Contact us to learn more about how our AI/ML solutions can enable your business to offer richer omnichannel customer engagements.
