We live in the Age of the Customer. Technological breakthroughs have allowed innovative companies to serve customers better than ever before and at lower cost. As a result, customer expectations have radically increased for every company across every interaction, regardless of whether they’re a tech firm in Silicon Valley, a manufacturer in Cleveland, or a retail bank in Minneapolis.
According to Salesforce Research, 52% of customers are likely to switch brands if companies don’t personalize messages for them; 64% expect real-time responses from brands; and 66% say they’re very likely to switch brands if they feel treated like a number, not an individual.
The most successful companies understand that no matter what they sell — whether it’s a toy, a car, or a financial product — they are in the business of delivering exceptional customer experiences. And, a key to deeply understanding their customers on an individual level and using that understanding to deliver exceptional customer experience anytime, anywhere is artificial intelligence (AI).
You hear the phrase in the business press: “Data is the new oil.” If data is the new oil, AI is the new internal combustion engine, converting data into insights, predictions, and recommendations that boost productivity and augment decision-making.
AI can spot trends and patterns that we would not otherwise see. Given the flood of data generated by a huge and growing number of customer touchpoints spread across an enormous number of channels, there is only so far you can get with traditional CRM and analytics tools. With advances in computing power and machine learning, AI can harness the flood of data to discover insights, predict outcomes, recommend next steps, and automate business processes.
In the past, signals in customer data that could personalize customer interactions were nearly impossible to detect at scale. But with AI, companies can scale personalization across millions or billions of customers, creating 1-to-1 customer journeys that lead to increased loyalty and business value.
For example, whenever customers walk into a bank branch — or log in to their internet banking site or call the customer service line — it’s an opportunity to engage with them.
If a customer has been looking for guidance on estate planning on a bank's website, AI can detect the interest, automatically let the bank teller or customer service agent know in real time, and surface relevant content so the agent can engage with them on the topic. This capability to proactively engage with customers so effortlessly wasn’t feasible before.
According to a recent IDC research report, 40% of companies expect to adopt AI for CRM within the next two years. In fact, by 2018, IDC forecasts that 75% of enterprise and ISV development will include AI or machine-learning functionality in at least one application, covering a large spectrum of use cases, including accelerating sales cycles, improving lead generation and qualification, personalizing marketing campaigns, and lowering costs of support calls.
AI is a game changer, but simply acknowledging AI’s power or market growth isn’t enough. Companies must be able to operationalize the deployment of AI across their business. From our experience implementing an AI-powered customer relationship management solution, we’ve found four keys to ensuring that AI benefits are realized.
First, make it clear to employees that AI is designed to give them more power to do their jobs better. That means ensuring machine intelligence and humans work effectively together.
Deep Blue, IBM’s supercomputer, beat reigning world champion Gary Kasparov at chess 20 years ago. But time and again since then, a human paired with a computer has beaten the strongest AI chess program. The same will be true in business. Competitive advantage comes from cultivating the most effective human and machine partnerships in your company.
Human + Machine > Human or Machine
Think carefully about where to incorporate AI into your business. How can it help your employees complete specific tasks more efficiently and effectively? Operationalizing AI will fail if it’s presented as an additional to-do for your employees and not a natural extension to their workflow. It has to be seamlessly embedded in business processes with measurable ROI to drive adoption.
What’s more, it’s important to build a constant feedback loop with employees, customers, and others who are impacted by the deployment of this new technology. Learn from them what is working and what isn’t, and look for ways to continually fine tune the algorithms and business processes.
AI can empower every employee to perform at the level of your best employee. When a top salesperson breaks revenue records for the quarter, a goal has always been to institutionalize what he or she has done and apply those lessons so that everyone can benefit from proven best practices.
With AI, it becomes considerably easier to elevate the game of every employee.
For example, a company might discover through machine learning that when a customer has a loan application in process, the top performers tend to call them every two days, and that this action has a meaningful impact on conversion.
An AI-powered app could automatically insert reminders into other salespeople's calendars, reminding them to call their customers back after two days. This becomes a self-optimizing process, designed to help every salesperson improve performance.
U.S. Bank and Salesforce have a strong focus on customer success. Every employee is motivated to deliver the best experiences possible for customers. AI provides a path for them to do their job better and delight customers.
The implementation of AI at Netflix, for example, is so successful because it has a core role in improving the customer experience — surfacing the films and TV shows that a customer is likely to enjoy. At Humana, AI is used to direct customer queries to the appropriate service agents or chatbots, resolving health insurance issues more quickly and efficiently.
Tying AI to this underlying culture and focus on serving the customer better ensures it does not become a technology in search of a solution.
Financial services companies compete with their industry peers, but when it comes to customer experience, they are compared with Amazon, Uber, Netflix, Airbnb and others who are infusing AI into their customer experiences.
In a world where customer experience is the new differentiator and where companies compete far beyond industry boundaries, companies cannot ignore the potential of AI to transform their businesses.
Rohit Mahna is General Manager of Financial Services at Salesforce. Bill Hoffman and Steve Daniels are Chief Analytics Officer and Business Information Officer at US Bank respectively.
To learn more about how US Bank is investing in customer relationships with Salesforce, check out their Customer Story here.