With 80% of internet-browsing Americans making an online purchase in the last month, internet retailers would be wise to take advantage of the influx of e-commerce data. But how do you connect the dots when there is so much data coming in from countless sources? Enter artificial intelligence (AI).
AI sorts and segments all of this information, so retailers can pull actionable insights to appropriately support their customers. If a retailer tried to do this without AI, it would be unmanageable (if not impossible). By learning from the data they have available, e-commerce organizations can personalize everyone’s experience from marketing to sales to post-purchase support.
We asked one of Traction’s resident e-commerce experts, David To, how to best leverage this data to turn prospective customers into brand loyalist throughout the sales cycle.
Step One: Targeted Marketing
“The dream is to have e-commerce, marketing and customer service intimately connected,” says David. “But the reality is many retailers don’t have clear communication between the three departments and this leads to a disruptive experience for customers.”
By combining the power of e-commerce data, a marketing automation platform and AI, retailers can achieve a 360-degree customer view. From a marketer’s standpoint, collating familiar and new data gives the organization the ability to:
- Understand each customer’s unique buying cycle to know which channels are the most effective.
- Segment their database by shopping behaviour to send targeted communications.
- Provide intelligent recommendations based on a customer’s browsing and purchase history.
With AI, marketing teams can parse through a customer’s online behaviour, abandoned carts and purchases to build a robust profile of their interests and shopping habits. For instance, Canadian outdoor apparel retailer, MEC, can see that John has recently:
- Looked at mountain bikes on their website.
- Clicked through an email to a blog about the best trails for mountain biking in North Vancouver.
- Abandoned an online shopping cart with a helmet and a bike lock.
AI combines the data from the different sources to let MEC know that John is interested in mountain biking, but isn’t quite ready to make a purchase. Once the marketing team knows this, they can target their communications with John through email, social and retargeting to help him to make his next purchase.
This information allows the team to automatically communicate with each prospect in a one-to-one manner. According to a report by the Boston Consulting Group, retailers that provide shoppers with a personalized experience expect a six per cent increase in annual revenue lift.
Step Two: Get the Sale
By combining an e-commerce platform with AI, retailers can better predict the products that a customer is likely to purchase without returning or exchanging.
“A great example of enhancing the e-commerce experience with AI is The North Face,” explains David. “Their Fit Finder takes each shopper through a series of questions which they combine with other shoppers’ purchase and return history. This determines which size is the most likely to fit and if the shopper will be happy with his or her purchase.”
Figuring out which size to buy online is always tricky and is a contributing factor to a 30 per cent return rate for online purchases (compared to nine per cent for brick-and-mortar retailers). The Fit Finder capabilities help each shopper find the products and sizes that they are most likely to enjoy, while lowering return rates and saving the business time and money.
Step Three: Seamless Support
Downloadable user manuals and customer support portals are the norm for customer service, giving customers quick access to the information they need. However, it’s not the personalized service that customers expect. With the support of AI, bots can:
- Support service teams through natural language processing to find resources for reps to share with customers.
- Manage basic issues in a one-to-one manner, as if customers were speaking with a service rep.
Natural language processing is the first phase of AI in customer service. A bot determines the nature of an incoming request and provides relevant resources or potential solutions for a representative to share with customers. This AI-enhanced support still provides the human element, but makes each service interaction more efficient as reps spend less time searching for support articles.
Moving beyond AI-enhanced support are automated chat bots. This form of artificial intelligence has the power to manage the simple cases such as returns, billing inquiries and shipping updates.
“We’re going to see bots play a larger role in retail and e-commerce,” explains David. “As we saw with adidas at Dreamforce, they can manage the repetitive cases. This frees up time for the service team to dig into more complex cases and bring further value to the customer journey.”
With bots handling repetitive cases, customers are getting the personalized and instantaneous service they expect in the digital age without the added pressure on service teams.
Preparing for a Customer-Centric Future
As we saw at Dreamforce in November, AI is the next big focus for Salesforce and it is up to us to make sure we have the systems in place to support it. This means implementing integrated systems that feed data between Commerce Cloud, Marketing Cloud, Sales Cloud and Service Cloud. With big data available, AI helps organizations with the heavy lifting to ensure that every touch point with an organization is effortless and personalized.
One industry where we’ve seen AI play a significant and growing role is in retail. If you’re a retailer heading to the NRF 2018: Retail’s Big Show in New York next week, we’ll be joining the Salesforce Trailblazers at Booth #4103; come by and see us. Otherwise, get in touch to learn how you can leverage your e-commerce data to improve the rest of your business.