For most merchants, harnessing artificial intelligence, or AI, may seem like too futuristic a goal to add to their 2017 priority lists. But while there’s plenty of hype swirling around such implementations as chatbots and the Internet of Things, the fact of the matter is that ever-more-sophisticated personalization and recommendation technologies are already verging on AI. Merchants should lay the groundwork now for future shopping experiences that are both automated and satisfying.
Consumers’ desire for personalized shopping experiences is by now well documented. More than half of consumers say they expect brands to recognize them across touchpoints, from the store to the mobile device to the eCommerce site and back again, and say they buy more from merchants whose offers take into account past purchases and interactions (both online and offline).
In response to this expectation, merchants are increasingly using tools that present products and content that reflect shoppers’ preferences and past picks. Earlier this year, two-thirds of merchants reported they were either already using personalization tools and planned to invest more or were launching brand-new personalization initiatives in 2016. These investments are likely to pay off, as merchants report that personalization improves results throughout the customer lifecycle:
- Engagement: 44% of merchants report improved email click-through rates, and 22% report improved time on site
- Revenue: 51% of merchants report an increase in site conversion, and 36% said average order value increased
- Loyalty: 26% of merchants said personalization caused both customer lifetime value and customer satisfaction to increase
Product recommendation and customer profiling tools increasingly integrate past brand interactions with “big data “insights that predict shoppers’ likely needs and paths to purchase. AI is the logical next step in this progression, enabling machines to respond to shoppers’ input with relevant information and products. Usage of AI-enhanced services is on the rise: more than a third of U.S. online consumers report using a website’s virtual agent or a smartphone-based virtual assistant, such as Apple’s Siri, to seek customer service help.
On the eCommerce front, merchants are using AI to transform their businesses through what’s been termed “conversational commerce,” whereby natural-language dialogue replaces explicit searching and browsing activities, such as keyword-searching for products or navigating through the customer service section to find shipping information. From Facebook chatbots to on-site product discovery tools, merchants are using AI to give shoppers a user-friendly entry point into their offerings.
As an example, 1-800-Flowers has debuted GWYN, a “gift concierge” that directs shoppers to suggested products across the company’s line, which includes 1800flowers.com, Harry & David, and more. A fixed footer keeps track of past inquiries and recommended products, and offers shoppers a means to provide feedback on the service.
Whatever the platform, these AI implementations are built on a common foundation: solid knowledge of the customer experience and the purchase lifecycle. Therefore, merchants contemplating their own AI-enhanced shopping experiences would do well to ensure that they have a wealth of data and best practices to draw upon.
To gather information relevant to future AI-driven tools and services, merchants should:
Document successful store interactions. There’s a reason 77% of merchants said human sales associates were their top store asset: nothing can replace the interplay of staff expertise and one-to-one product guidance that occurs face to face. But merchants should attempt to capture store shoppers’ most common product and service questions and build their AI routines to accommodate those needs. Similarly, top associates’ sales techniques and scripts can be woven into AI responses.
Expand product discovery tools. As an interim step en route to AI-facilitated product suggestions, merchants can offer an expanded range of product search tools. To start, they should implement current best practices for on-site search, including faceted search tools that can surface which product attributes matter most and suggested search terms that can guide shoppers to categories and even individual products directly from a drop-down box that adapts as new terms are typed.
In addition, merchants should consider search tools that use input other than text to find relevant products. Visual search gives shoppers the means to select a particular color or icon to see matching products, or to input photos from their smartphones to find similar items, match color swatches, or find products that fit within the pictured dimensions. Geographical data from smartphones can be factored into search results to show shoppers items available at outlets near them. Such solutions move merchants one step closer to providing the relevance shoppers expect from AI shopping agents.
Use proactive chat for customer service. Fully 46% of U.S. online shoppers have used live chat or messaging with customer service agents, signaling a high degree of comfort with messaging tools as mobile messaging apps become ubiquitous. Merchants should not only offer a live chat link alongside their customer-service phone number; they should also experiment with proactive chat triggered by specific actions (or non-actions) along the path to purchase, such as stalling on the cart page or backing out of checkout. Not only do such prompts highlight chat as a customer service option; they help merchants understand the context of shoppers’ on-site behaviors, fueling richer interactions in the future.
Are you contemplating an AI implementation for your business? Why or why not?