The Many Ways AI Enhances the Customer Experience in eCommerce
When was the last time you truly enjoyed contacting the customer service department of a product or service? Sure, there are those companies far and in between that are known for resolving issues quickly, but do you enjoy repeating yourself over and over again as you’re being transferred between departments? Especially when you know they have most of the information they need right in front of them?
The reason for the frustration is because there is a huge disconnect between each aspect of the customer journey. In most cases, each touchpoint is run independently across the company, without a central source of data. In turn, this makes each touchpoint compete and conflict with one another, which leads to frustration on the part of the customer. This is where AI comes in.
AI is a tool and method that is often used in conjunction with machine learning and deep learning for customer experience professionals to mine data from. CustomerThink did a great job in explaining the differences between the three:
Artificial intelligence is a field in computer science that focuses on developing computer systems to perform tasks that usually require human intelligence, including visual perception, speech recognition, decision-making, and translation between languages. Machine learning uses statistics/math to allow computers to find hidden insights (i.e., make predictions) without being explicitly programmed where to look. Deep learning is a class of machine learning algorithms that are modeled after the information processing and communication patterns of the brain. Deep learning uses layers of units or nodes for feature extraction and transformation, each layer using the output of the previous layer as input. Higher level features are derived from lower level features to form a hierarchical representation.
As far as eCommerce is concerned, AI introduces intelligent engagement that is scalable, as well as more personalized experiences that will help customers get to the bottom of their issues more quickly and efficiently, while improving their overall satisfaction. The adoption of AI applications for eCommerce companies is quickly becoming the standard, as it helps digitally transform processes with purpose and customer centricity. The most popular AI applications that are being implemented today are chatbots, preemptive routing, task performance/management, augmented engagement, digital concierge/ assistant collaboration, and many more.
Here are some ways AI is being applied to enhance the customer experience in eCommerce:
- Chatbots: Chatbots are virtual agents that provide intelligent conversations across a variety of scenarios in customer engagement. These bots pick up on conversational cues, and quickly provide solutions that meet the needs of customers. A lot goes into the process of creating chatbots, because you would have to factor design, execution, and maintaining the right balance between speedy transactions and positive experiences.
- Virtual Concierge: These branch out of chatbots, and can be found on both messaging platforms, as well as hardware devices. Virtual Concierges are bots that provide personalized services, and can even be paired with human counterparts if needed. In eCommerce, a virtual concierge can be used to act as a personal shopper, or even help visitors to your site find and purchase the right gifts.
- Virtual Assistants: Virtual assistant appear similar to virtual concierges, but are actually quite different. The concierges assist users with items that can be viewed as tasks, whereas the assistants assist with very simple questions and commands. Think Siri, Echo, and Cortana. These platforms are partnering with developer communities to help extend functionality, but even at this stage, they can prove to be useful in eCommerce. Virtual assistants can update consumers on their order status, billing, and the like.
- Cognitive Computing: This refers to the simulation of the human thought process to augment human engagement. It’s requires self-learning systems to mine data to recognize patterns, and process natural language to interact with users in a way that is complementary, value-added, intelligent, and of course meaningful. The IBM Watson is a popular example of cognitive computing. In eCommerce, it can be used to handle many customer service inquiries up to a certain level before actual human representatives have to take over. This is more an enterprise solution that can be used for vetting purposes.
AI is to be viewed as an investment in customer relationships. It generally takes a bit of trial and error to get it right, but once you reach that point, you will find AI improving every aspect of your business.