The Q4 AI Advantage: Turn Holiday Browsers Into Buyers With Conversational Commerce

With the Q4 holiday season critical for most consumer-focused retailers, there's still time to make some additions to the e-commerce technology stack. And in a year with the rollout of so much commerce-focused artificial intelligence (AI), online retailers should be considering conversational commerce technology. Despite all of the hype around AI, the technology is delivering real e-commerce business value across channels, product use cases, and customer service pain points.

According to research from personalization and customer experience platform Bloomreach, 97 percent of shoppers who have used an AI shopping assistant found it helpful, while 76.8 percent said that an AI shopping assistant helped them decide to purchase an item faster than if they had shopped on their own.

Use Conversational AI to Power Customer Service

About 25 years ago, as e-commerce was taking off, online chat technology enabled retailers to answer shopper questions in real time in order to close the sale more effectively. For a new technology designed to help shoppers still more familiar and comfortable with in-store retail, online chat solutions helped retailers and consumers make the transition from in-store to online by offering a customer service representative to answer questions shoppers had in real time.

Today, thanks to advances in AI technology, the chat a user engages with on an e-commerce site or app might be operated by conversational shopping agent technology instead of a human being.

Conversational shopping agents, utilizing AI technology, are designed and developed to address common e-commerce challenges. For example, for a consumer about to abandon a shopping cart, conversational shopping agents can provide the consumer with additional product information, delivery times, and other useful data about the product(s) in the cart to reduce the likelihood of abandoning the cart. Because the conversational shopping agent technology is customized based on the respective retailer’s data, the responses in the conversational shopping chat can be more relevant and helpful than a customer service representative could provide based on a much broader pool of data.

Conversational shopping agent technology is effective in a broad range of e-commerce use cases, including first-time purchasers, seasonal products, or opportunities where personalization and/or cross-selling can increase the customer's purchases.

AI sales experts powered by saywhatt’s technology, which can be found on skin care site ahava.com, provide shoppers with nuanced answers, like recommending specific products over others based on the shopper’s demographics and skin conditions. The company’s technology offers retailers an end-to-end solution from initial engagement through checkout. According to data from saywhatt, for Ahava.com, 20 percent of the items that the AI sales expert recommends get added to the shopping cart, and 34 percent of shoppers who engage with the AI sales expert via chat purchase from Ahava’s website. Beyond websites and apps, saywhatt’s technology can also be used by in-store sales and customer service representatives working in physical stores.

In addition to on-site or in-app chat integration, technology like this can also be incorporated into digital ads, enabling marketers to close the sale directly from a digital ad.

Unified Shopping Experience: From Online to In-Store Support

The same technology that can provide conversational shopping agents can also be used by in-store sales and support representatives to provide better service via a tablet or in-store kiosk. Whether it means finding the store that has the desired product in the right color and size, finding a matching accessory, or if a specific supplement can be taken by pregnant women in their third trimester, the insights presented via conversational shopping agent technology enable closing the sale quickly and improving customer satisfaction.

According to data from Point B, a consulting firm specializing in leveraging technology to unlock human potential, conversational shopping technology is particularly important for luxury retailers. When the conversational agent technology includes previous purchases and loyalty data, the in-store sales representative will receive recommendations for this current visit based on sales history, shopping patterns, and seasonality. For example, if a shopper typically buys his wife clothes for her birthday from a particular boutique in early March, the technology will prompt the sales representative to verify that this visit is to purchase a birthday present, and once confirmed, make appropriate recommendations based on the style and budget of previous birthday presents.

For 25 years, digital technologies have promised to solve the problems of physical sales and marketing. Whether it’s digital ads, which would finally provide marketers with true attribution (vs. a TV commercial or a print ad), or e-commerce sites/apps, which enable shopping from anywhere, these digital solutions either didn’t completely solve the problem (ad attribution) or created new ones (an increase in returns). Conversational AI shopping technology appears to solve customer service challenges, both online and in-store. It will be interesting to see how much of an impact conversational AI shopping technology will have on the coming Q4 holiday season.

Sapir Diamant is a senior sales manager at Zoomd, a global mobile-first marketing company that delivers measurable growth for brands and apps across 70-plus markets.