As artificial intelligence (AI) continues to grow, evolving technologies will naturally emerge. In the realm of e-commerce, businesses can barely keep up with the pace of AI as it is, but they must in order to capitalise on opportunity and maintain a competitive edge. AI cannot be ignored. There’s too much useful, revenue-driving technology to embrace. If you’re interested in gaining a competitive advantage in the retail e-commerce space, then it’s essential to learn the AI trends sure to impact business systems and development in 2018. Here’s what you can expect:
Online shopping on Amazon, for example, can often be a price hunt and peck. Items that sit in a shopping cart for even short lengths of time, often experience price fluctuations. Amazon and its respective vendors are learning how to not only price items to match demand and seasonality (think: last-minute holiday shoppers), but specific buyer personas and behaviours.
Knowing when to target a shopper with the price point that will ultimately lead them to purchase is invaluable. e-commerce business owners can set minimum and maximum price point parameters, but AI will automate the rest. Prices and discounted prices will no longer be aimed at a business’ entire consumer population. They will instead uniquely target the right person at the right time with the right price. Not only will the price be personalised to each shopper, but it will also determine the profit margins that each retailer desires to reach, so you can be achieving the same sales level with higher profit margins.
AI-powered platforms can enable ecommerce professionals to analyse large amounts of consumer data in order to offer personalised incentives to each visitor that enters their website. Backed by the science of behavioural economics, they can create unique shopping offers based on each visitor’s shopping habits, personal preferences and the retailer’s KPI’s.
As AI develops, its ability to collect and utilise data from multiple consumer channels continues to improve. Data from both digital and in-store shopping experiences can be collated and analysed to provide direct insights to consumer habits, interests, and purchase intent. Here are a few examples of these channels and how they can benefit shoppers and e-commerce business executives alike:
Digital Customer Journeys: Business Intelligence (BI) measures the customer’s online journey and is significantly enhanced by AI. BI comprises of the strategies and technologies used by e-commerce companies for analysing business data. BI powered with AI can provide past, current and future forecasts of business operations, with data points such as page visits, clicks, and time spent on specific sites. Once collected, AI can utilise this data to predict personalised buying habits and a consumer’s likeliness to purchase.
Customer service interactions: Interactions between consumers and customer service professionals are highly powerful. This is the company’s opportunity to directly speak with customers to find out what they want, what their challenges are, and what solutions will work best. Measuring success via surveys or Net Promoter Scoring (NPS) are highly efficient ways for AI data systems to help business leaders get a more solid grasp on the bigger picture.
Chatbots and virtual assistants: AI is already capable of immediately capturing consumer pain points and frequently asked questions through chatbot and virtual assistant platforms. Not to mention, AI-powered chatbots are on-call 24/7, allowing e-commerce websites to answer customer inquiries no matter what the time of day.
Most shoppers who have used a website’s chatbot know there is a great deal of opportunity for these digital customer service representatives to improve. We predict that 2018 is the year chatbot technology will get it right. Once implemented, chatbots are easy and inexpensive to maintain. By automating data measurement and analysis, chatbot technology uses predictive analytics and survey tools to learn more about a given business’ audience. The key to chatbot improvement in 2018 is incorporating Natural Language Processing (NLP) in the technology in order to adapt to better serve customers.
Facebook Messenger Platform’s Lead Project Manager, Kemal El Moujahid, says, “The promise of chatbots is personalisation at scale.” Whether chatbot or human, he explains, “…The most important thing for humans is for their expectations to be managed.” As long as chatbots are managing expectations by providing solutions, they will continue to seamlessly adapt into the customer service fold.
Point-and-click analysis is the traditional way most e-commerce professionals have historically interpreted website audience traffic. Customer journeys, site-pathing, and click-through-rates do provide useful data points such as:
In 2018, these metrics will not go away, but they will be enhanced by conversational analytics. Far more personal than clicks, chatbot conversations empower AI analysis to get directly to the heart of a consumer’s needs. Conversational analytics move beyond point-and-click methods to examine real-time conversational interactions. Consumer segmentation becomes automated. AI assesses when a user is most engaged with a chatbot, what their last conversation point or question was, and can more seamlessly adapt messaging that is most useful to that user.
This information will, without a doubt, dictate and speed up brand-wide improvements in a far more consumer-centric manner. I can’t wait to see how these AI trends will position e-commerce growth for even greater success in 2018.