The Evolution and Future of AI in Conversational Commerce

We are all excited to participate in #Shoptalk17. Here are some thoughts about AI in Commerce.

AI powers the digital web. Viewing everyday examples - from Apple’s Siri and Google’s self-driving cars to Netflix's movie recommendations, and to VISA’s credit card fraud detection - this statement isn’t far from the truth. But never before has the impact of AI been more evident in commerce, and this has large implications for retailers and brands, both large and small. 

Consumers drive the buzz, but enterprise need to own the discussion

There’s a lot of buzz around AI being used to power chatbots, personalized shopping, and conversational commerce, and so on. Big brands and retailers - like Macy’s, North Face, even Domino’s Pizza - are experimenting and piloting AI across customer touchpoints. Investors and startups are also riding the wave, with tremendous explosion in funding. It’s a no-brainer - consumer-facing AI applications offer companies a competitive edge and brand loyalty amongst the many choices and options consumers have at their fingertips.  

AI applications for enterprise solutions, however, will bring exponential ROI in the future. Because if AI is the rocket, data is the fuel. And all the data is currently placed at enterprise backend. Consumer AI has a cold-start problem when it comes to gathering data.

Companies who use AI technology across both consumer-facing and organization-specific contexts, i.e., a holistic approach to commerce, will become drivers of next gen commerce.

3 Key takeaways for Brands and Retailers

Leveraging the success of retailers, there are 3 places brands and retailers should consider to begin their journey towards a holistic approach to AI and to becoming drivers of the future of commerce:

1. Build customer-facing systems for your teams:

Give all teams access to AI-based tools and applications. Developer APIs are the most common form of AI-enabled applications for enterprises. But offering data in the same format as consumers, in the forms of dashboards and notifications, will empower brands and retailers with the knowledge and insight to make informed decisions around customer experiences.  

2. Address areas that are labor and resource intensive

AI is ideal for automating tasks across retail functions, especially those that support human decision-making. For example, marketing campaigns are developed by marketing teams, but much of the work happens before scheduling and deploying the actual campaign. From A/B testing to segmentation and creative development, marketing teams spend a lot of time preparing a campaign. Focusing AI on automating data-intensive, repetitive tasks can help your teams focus on strategic initiatives, thereby allowing them to be more creative, more productive, more profitable. 

3. Experiment, learn, and refine

Most enterprises are at early stages of adopting AI. From warehouse processing to predictive maintenance, commerce companies can benefit from actively seeking out use cases and seeing how the technology can best fit their needs. Instead of using the “wait and see” approach, empower teams to experiment, learn, and refine, and to become more responsive and adaptive to changes in organizational and consumer trends.        

With a dynamic retail environment where consumers have many options, and where business models evolve, the future of commerce will be driven by the smartest, relevant, and most adaptive retailers and brands. Organizations to succeed will not only be the ones that offer their customers an inspired and frictionless shopping experience, but those that also look internally to empower their teams with intelligence, automation, and action.