The British military historian Sir B.H. Liddell Hart compared a strategic plan to a healthy tree, full of branches. With customer expectations on the rise, assuming your customer care reps will be able to understand eCommerce consumer behaviors and customer expectations — all while handling requests — is equivalent to depending on a single tree branch to take your business forward, rather than a full tree.
Businesses must be open to technological advancements if they really want to boost their prospects.
The adoption of tech will not only help businesses tap into customer expectations but also tailor communications precisely to their needs. This should help reduce the eCommerce cart abandonment rates, which stand at a whopping 68 percent.
Now, the question is: What technology will help eCommerce businesses watch customer behavior and meet the ever-rising expectations across the customer journey?
Understanding eCommerce consumer behavior
As it turns out, a mountain of raw data is available on consumer behavior these days, thanks to website analytics tools. But that’s only the first part of the equation.
Extracting real value from the data available — and then actually using it — is not that easy. But with the help of artificial intelligence (AI)-powered tools like IBM Watson or web analytics like Google Analytics, businesses can nail down the most relevant data, fully dissect customer behavior, and even tailor communications specifically to their needs.
A well-organized approach to AI tools aids eCommerce businesses in choosing how to present products and services, and simultaneously guides and advises customers on different products.
With consumers bombarded with pricing and product information from all sides, AI offers personalized inputs in terms of product, quality, price, size and more — and at the right time, on the right device, and with the right message.
AI tools are also adept at designing individualized promotions, making adoption of AI a necessity in the eCommerce arena these days. So, if you intend to incorporate AI tools in your eCommerce store, check out GoodFirms’ list of top AI companies.
Widespread adoption of AI in the eCommerce arena
Ecommerce businesses could bet on tools as simple as Google Analytics or try using comprehensive systems such as IBM’s Cognos Analytics System to analyze customer behavior. Currently:
- Seventy-five percent of enterprises are using AI and machine learning to enhance customer satisfaction by more than 10 percent.
- Three in 4 organizations are using AI and machine learning to increase sales of new products and services by more than 10 percent.
According to a U.S.-based consulting firm Walker Information, by 2020 customer experience will be at the top of the agenda of eCommerce businesses. So, eCommerce companies must embed AI solutions if they want to meet the needs of demanding customers.
Here are three ways that AI can benefit your eCommerce business.
1. Rein in runaway customers with extreme personalization
The best way to reduce cart abandonment cases is by tailoring messages in a way that motivates customers to act on the messages.
Activewear and outdoor sports gear company The North Face joined with IBM to offer personalization services. By adding AI — IBM’s Watson — to its online shopping app, the company generated a psychoanalytic profile of customer data. Next, it went on to ask in-depth questions regarding where, when and why their customers would be using their apparel.
Further, the AI-offered personalized recommendations in the form of “High Match” or “Low Match.” In an instant, the shoppers were able to figure out whether the apparel would suit them or not, saving them from scrolling through thousands of apparel images.
The result of incorporating AI into their online shopping app?
Customers started spending two minutes with the AI, which accelerated the click-throught rate for product recommendations by 60 percent.
Takeaway: Leveraging AI in eCommerce apps, specifically for personalization purposes, could help eCommerce stores rein in runaway customers, specifically during the cart abandonment stage.
2. Kick customer service interaction up a notch
The customer service window is so precious it must be protected by a bodyguard of AI algorithms. As demand for extreme personalization grows, customer service reps will increasingly be pressed for time and won’t be able to address all customer concerns all the time, even if they want to. This is when chatbots that run on AI algorithms could act as a saving grace. The AI filters requests and loops in customer service reps only when the bot can’t handle the request.
This is how chatbots aid in customer service: First, a chatbot learns to mimic client interaction, typically between a sales associate and a customer-care assistant. From there, it picks up the tone of the user message and devises ways to address their needs.
The result: Today, chatbots answer 80 percent of the routine questions.
British online retailer Shop Direct is working with IBM to develop an AI-powered chatbot that could be used to detect customer mood. The service again uses Watson to gauge users’ mood based on the words used and the tone of their messages.
Once the technology connects the dots between the words and tone, a customer service rep is then brought in to take it from there, online or via phone.
Takeaway: The use of AI-based chatbots for customer service could free your workforce from routine tasks, thereby helping customer care reps to focus on crucial tasks that might require their personal intervention.
3. Anticipate customer needs and replenish stock
Inventory issues will eventually be a thing of the past as data analytics powered by AI can ensure that in-demand items are restocked as needed.
German online and catalog retailer Otto Group is working with Blue Yonder, a provider of AI solutions for retailers, on a stock replenishment optimization solution that would aid retailers in predicting buyer requirements in advance.
The technology is programmed to analyze a whopping 1 billion historical transactions plus 200 other variables, including weather conditions and website searches, to predict future purchases. In short, the system will help Otto stock only those goods that customers are likely to buy, thereby ensuring faster delivery and reduced returns in the process.
The solution also ensures that products are sold within a 30-day period and enables direct delivery from the supplier to the customer without passing through Otto’s warehouse.
Takeaway: A stock replenishment optimization solution powered by AI would help eCommerce businesses successfully reduce returns. In case of the Otto group, by nearly 2 million items a year.
With customer expectations increasing, brands must adopt a two-pronged strategy that leverages humans while also embracing AIs to drive deeper engagement (and sales).
In short, companies need to creatively use both AI and the human workforce to take the guesswork out of understanding eCommerce consumer behavior and connect with them on a more personal level.
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