The AI-enhanced CX: Agility for an uncertain future

30-second summary:

In March 2020, market research firm IDC forecasted 2020 artificial intelligence (AI) spending to range from $48 billion, a 25% increase from 2019, to $50.7 billion, a 32% increase.
Demand for AI is showing resilience compared to other technologies in a post COVID-19 reality.
Here’s how AI is impacting three CX-focused business functions: marketing and customer engagement, sales execution and omnichannel customer service.

In March 2020, market research firm IDC forecasted 2020 artificial intelligence (AI) spending to range from $48 billion, a 25% increase from 2019, to $50.7 billion, a 32% increase.
While the second half of this year remains uncertain due to COVID-19, demand for AI seems to be showing resilience compared to other technologies.
As businesses work to identify the best approaches for how they can operate and succeed in a new reality, AI continues to play a critical role.
By automating repetitive tasks and finding patterns in large quantities of data, AI services have the potential to help organizations with everything from enhancing remote work and data processing to advancing patient care and powering workforce analytics.
But an area where the technology promises an even broader impact is in the customer experience (CX). With the exponential growth of data arises an opportunity for both B2B and B2C brands to utilize it along with AI to improve everyday experiences for customers.
AI impact in three CX-focused business functions
To deliver a top-notch experience, all customer-focused business units must join forces, including sales, customer service and marketing.
1) Marketing and customer engagement
To be successful, marketers need to simplify the buyer journey. While this is necessary in both B2B and B2C scenarios, it’s never been more important when interacting with consumers, whose purchasing habits have changed drastically as a result of the pandemic – especially on e-commerce channels.
Marketers can make the buying experience seamless by activating customer data and using AI to uncover patterns and surface new insights.
Two of the most high-impact use cases for AI in marketing are target account selection and lead nurture. For account selection, predictive analytics can be used to select the best set of target accounts based on their propensity to convert, allowing marketing teams to be laser-focused on the accounts where it matters most.
Additionally, AI-driven lead nurture and qualification can be applied across the breadth of customer interactions to further segment accounts according to interest, engagement and readiness to make a decision.
The end result of both strategies will improve the ROI of marketing efforts by increasing the relevance of engagement and focusing resources where they have the power to deliver the greatest impact in the shortest amount of time.
2) Sales execution
The selling experience has become more complex than ever, driven in part by the rise of digital channels and the imperative of providing a highly personalized experience every time.
Today’s buyers are sophisticated and in control; they want a combination of products and services that fit their unique set of needs, are available on their preferred platform or channel and meet a desired price-point.
Lead-to-cash is one of the most important customer-centric processes in an organization – it starts with an intention to buy and ends with revenue recognition.
By integrating AI and big data into the process, organizations can make the experience more intelligent and enjoyable for the customer. AI and machine learning help transform sales teams from being reactive to proactive and intuitive to prescriptive.
Most importantly, these technologies can guide the sales journey from initial identification to customer acquisition and retention.
3) Omnichannel customer service and chatbots
Recent data found that 67% of consumers expect to directly message with businesses more over the next two years. And, in the wake of COVID-19, it’s likely that customers will want to interact with service leaders even more.
With this in mind, it has never been more important for brands to orchestrate seamless service to support customers throughout their entire journey, regardless of channel.
With that, organizations must strike the important balance between self-service and human interaction to deliver the most convenient experience possible. AI-powered chatbots are a valuable tool that can save businesses money while allowing customers to take care of minor issues on their own time.
It’s important to remember, though, that chatbots won’t perform as well if they try to understand everything; rather, they should be used to tackle a select number of topics such as invoice management, order tracking and account management.
In fact, research shows that chatbots are able to accelerate the handling of queries regarding invoice management by 2-3X.
And while chatbots can be a huge time saver, there are also many cases where a customer would prefer to speak with a live agent. For complicated issues, engaging live with a service agent is by far the fastest and easiest way to get things resolved.
Modern businesses should view chatbots not as a replacement for humans but rather as supplementing the human workforce to help their employees be as efficient as possible.
Deepen customer relationships with AI
As we look ahead to the future of business, AI and machine learning will be critical to staying agile and always keeping up with customers’ evolving needs.
Organizations must continue to prioritize their digital transformation to meet these needs and drive the customer experience forward.
More than ever, customers are looking to connect with the brands they engage with on a deeper level. With the right approach, AI has the potential to help businesses connect with their customers on a much more personal level.
Sven Feurer is Senior Director Product Engineering & Operations SAP Customer Experience at SAP SE. 
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