Companies looking at revolutionizing the way they sustain relationships with their customers, set themselves apart from competitors and always have a potential new revenue stream on hand to explore; have turned to artificial intelligence (AI) and machine learning to pave the way. Global business value coming from AI is projected at a total of $1.2 trillion in 2018, an increase of 70% from 2017, and AI-derived business value is forecast to reach $3.9 trillion in 2022, according to Gartner Inc.
What Makes AI a Game Changer for Customer Experience (CX)
Now there is no denying that there is enthusiasm to introduce AI into businesses. Around 80% of enterprises are investing today in AI. However, 1 in 3 management executives believe their company will need to invest more over the next 3 years to keep pace with competitors. There is some ambiguity on the benefits of AI in enhancing CX, which will perhaps become clearer when you understand how it can be a game changer:
Now, let’s start with why there is a need at all for AI in CX. Customer experience, if handled optimally can drive growth of an organization and mismanaged, can be the highest source of risk. Enhancing CX today is primarily based on garnering the right data insights. But, as we all know, CX datasets are not simple, considering customer behavior is very dynamic. AI comes in at the CX dataset level to make sense of all the chaos. Client-facing employees cannot derive and put together customer history in real time and similarly automated systems cannot have a one-set-of-rules-for-all-customers approach. Being able to find clear patterns across multiple customer interaction touch-points is where AI comes in.
When implemented correctly AI has the ability to reduce response time and connect with a consumer instantly. Picture this – 265 billion customer support requests are made every year, and it costs businesses a whopping $1.3 trillion to service them. AI reduces these costs significantly when organizations upgrade to using AI, chatbots, messaging and newer technologies.
How does AI do that? Since interaction has become contextual, it becomes personalized. Any solution or recommendations offered at this point reduces the chances of any bottlenecks. The fact then that AI bots will power 85% of customer service interactions by 2020 according to Gartner should not be surprising at all.
Follow-ups after the interaction can always be automated and based on standard inquiries, which leave room for additional responses where needed. The benefit of this for the organization, besides a satisfied customer? Human resources are freed up to deal with more complex problems. Customers are a dynamic base and AI needs to be constantly upgraded to anticipate issues and come up with solutions. This is where humans and machines work together to reduce the chance of errors.
Fundamental capabilities for successful AI application in CX
The next question to address then is what capabilities does an organization need to successfully integrate AI with CX. Here are 4 fundamental capabilities you need to consider:
This is the first and most comprehensive step to ensuring that AI implementation is done the right way.
- Get the right support from the senior management: This is support for strategic implementation and back-up in case of major escalations.
- Find the right team: Quality AI depends on the team that means the entire system.
- Ensure quality data and its availability
- Create a scalable AI solution
When it comes to dealing with a customer with AI, it is based on behavioral analytics. One of the key expectations from customers is that there is a unified experience; AI comes in here and ensures that customer behavior analytics does this hassle-free. Having the right data unification tools then becomes important. Customer journey analytics platforms ensures that it brings together multiple data sources seamlessly.
Real-time Insights Delivery:
For AI to have the desired impact, information based on customer insights have to be made available in real time through the customer’s contact point. You may have SaaS platforms with a range of APIs and third party integration, but what you will also need are analytics platforms with a collection of APIs and development kits that will deliver this information and integrate with the touchpoint seamlessly.
Customer interactions today take place across a multi-channel system, and therefore for AI to deliver real value, it has to have a context to work within. This has to be more than simple segregation of data that comes in. This means that your AI will need to have an understanding on how each of your touchpoints is triggered and the kind of information it will bring in, as well as the final results that are expected from the interactions at these touchpoints.
Key AI Interaction Methods for CX and What They Do
Designed to simulate real human interactions, these do the work of providing an immediate and personalized response without making the consumer feel that he is interacting with a machine. They are available round-the-clock and therefore remove unnecessary delays.
These make use of AI to obey commands as well to answer questions. It helps a potential customer navigate through the experience and helps them on multiple levels based on simple conversations.
With AI becoming an integral part of businesses, consumers will soon be interacting with it, just as they would with a representative. Predictive personalization will be a direct result and will enhance customer relationships.
AI-enabled customer analytics, when implemented correctly, has the ability to wade through massive swathes of complex data space and come out with rational and predictive patterns. In terms of unlocking business possibilities, this is immense. Having access to such pointed data will ensure that you are prioritizing your time with insights that will fetch ideal results.