How can generative AI improve the customer experience?

ChatGPT

Generative artificial intelligence (AI) describes algorithms that can be used to create new content, including audio, code, images, text, simulations, and videos. Generative AI algorithms use machine learning models to predict the next word based on previous word sequences, or the next image based on words describing previous images. Generative AI tools can produce credible content in near real time, enabling organizations to produce content to better educate their stakeholders. 

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We have to take a step back to understand the 'why now' behind the hype. The AI technologies are confusing, and we should concede we do not understand all of the various forms of Artificial Intelligence. A quick recap of the major types helps. 

Tied together and you have Generative AI to create art (think about the Cosmopolitan magazine cover last year), articles, video, and an entire conversation that AI can have with a human. There is a new burst of products and companies to perform these feats of AI magic, such as OpenAI's Dall-E 2 and ChatGPT, Google's Imagen Video, Stable Diffusion, and many more. These images and text are sufficiently advanced to convince a human that people and not computers create them. 

To sum up: Generative AI has the possibility to change the game for business creativity and decision making, once it is harnessed to the business applications that underpin growth and efficiency.  

A study of 8,050 customer service professionals on how service orgs continue to adapt to an ever more digital-first environment, and future plans for investments in people, processes, and technologies.
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— Vala Afshar (@ValaAfshar) September 9, 2022

Q: Why do you rank Generative AI, and AI overall, as less of a factor in corporate success? From the media attention, it seems like the next big thing.

A:We just looked at how AI has matured over the past five years, to a point where it will seep into every piece of software. In many ways it already has. There is one big inhibitor to be overcome in using the new technology. This is true whether you are in a business, Public Sector, healthcare or education, and that missing piece is tying advanced AI to Personalization.

AI is not what most influences business growth and customer retention. In every industry, marketers look at the dimensions that are most valued by the customer. In the airline industry, for example, these are often listed as the cost of the flight, the emotional value of the brand to the customer, the availability of flights that interest the customer, and the experience a traveler has in flight. Airlines use advertising, flight crew compensation, good customer service, and operational excellence to meet those customer expectations.

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That does not mean that AI is not important. Once an organization understands the key dimensions of growth and customer loyalty, AI is introduced as something that will be embedded in business processes to make them more powerful. To return to our example, an airline can introduce a tool like Generative AI to personalize web experiences, video content, and messages to fit each customer. These new tools are not just for large enterprises. Take a young company like Runway that is democratizing content creation for web and social media channels.

The next step is for the enterprise to develop a plan to bring together the right team to blend Generative AI into existing customer experience programs. 

Generative AI comprises artificial intelligence technologies and applications that generate entirely new content: code from natural language, 3D assets from 2D images, and even human-like voices from scripts.
The generative AI landscape 2023 pic.twitter.com/2K6nqOaPFa

— Vala Afshar (@ValaAfshar) January 25, 2023

Q: How do Marketing and classic CRM fit together with AI?

A:The dream of personalizing the customer experience is 30 years in the making. It was almost in 1993 when Don Peppers and Martha Rogers first published their visionary book, The One to One Future: Building Relationships One Customer at a Time.It was subtitled, Building relationships one customer at a time. They painted an amazing picture of the future of customer experience. The problem was that achieving their vision was technically impossible for companies to do at scale. There was no way to treat each customer in a personalized way on their preferred communication channel using reliable real-time data. As digital channels continue to expand to include TikTok, WhatsApp, websites, devices, and mobile apps, it is a massive challenge to synchronize them atop of traditional channels, and to bring together the right customer data and business rules. 

It's audacious what Peppers and Rogers imagined the future could look like. Keep in mind that 1993 was the same year that Siebel Systems was founded, with a product line limited at the time to automation tools for salespeople.

Peppers and Rogers listed simple steps to get to this one to one future. It was the execution that was --- and still is -- difficult at scale. They pointed out the need to collect all relevant data about the customers' preferences. These are the timeless questions about their expectations, and their perception of the current relationship with the brand, and how they wanted to be treated, and how they have been treated. They really set the bar for what the future could look like, and it has taken us 30 years to build the technology to achieve their vision.

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— Vala Afshar (@ValaAfshar) January 24, 2023

Q: Looking past the challenges inherent in introducing Generative AI, what is the big opportunity for businesses to get this right?

A:Where this gets incredibly exciting is how Generative AI converges with emerging ways of managing data, and how that links to the future of CRM and engaging customers. It opens up enormous opportunities.

Until now it has not been possible to turn the idea into action. The notion that a company can collect this data, prioritize it for each customer, and for multiple customer segments, and then engage customers in a customized way in real time based on the analysis of this information on the customer's preferred channel is only now becoming a reality.

A business can think of this as a Customer Data Cloud. Until now, it was impossible to connect all of the customer data at scale. It came in too many formats, from too many devices and applications and systems. There was also too much data for a business with a large customer base. The data management alone required dozens of data scientists, plus custom built connectors. At Salesforce where I work, we have changed all of that with the advent of Salesforce Genie Customer Data Cloud. We have connected the customer data, harmonized it into a customer graph, and made it available to all departments in the organization. The result is the foundation for a personalized customer experience.

It looks like the problem of a unified view of the customer should be enough for a great customer experience. That still does not answer the question: "What does Generative AI add?"

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— Vala Afshar (@ValaAfshar) September 7, 2022

Q: To wrap up, what do we recommend that businesses do to accelerate their use of new AI technologies? 

A:AI initiatives have resulted in gains for some companies, though they are in the minority. For the other 99% of organizations, AI projects are small and tactical and focused on analyzing and optimizing business patterns and processes. Through 2025, Generative AI, which we defined roughly as the ability of language models to create things -- images, code, language transcription -- will be an added IT component, the impact of which is as of yet unclear. There is some practical advice on how to move ahead.

The first step is to make it clear that AI, like automation and analytics, is meant to make the lives of people easier. There will be profit, but it is not about profit over people. There is a good deal of anxiety about AI, and not as we might think. Much of it is around the effect of AI in the workplace. It is replacing all non-complex activities. Some activities look complex, but they are not so much complex as requiring many steps and advanced reasoning and calculations. Activities like completing forms, assessing contracts, forecasting, ordering materials, and others already mentioned, are math problems, and perfect for AI. What this leaves employees for work is one of two scenarios: Either they are performing menial tasks that are too expensive to build AI and robotics for, or knowledge workers with a constant stream of highly complex challenges with no single correct answer. 

Unless AI is deployed thoughtfully, the workers of the future will either be poorly paid and bored, or well compensated and stressed. How will we engineer dignity and happiness in the AI future?

Also:What is ChatGPT and why does it matter? Here's everything you need to know

Where does this leave an employee at work? Mostly spending more of their time assigned complex tasks that require higher-order analysis of situations that have no clear resolution. The situation will lead to anxiety and fatigue. 

The only way to turn AI into a net-positive is to make it work as a support tool that makes the life of the employee more productive and rewarding. Be creative and create a short list of the top processes that you would like your organization to do better, and see if AI offers an answer. Here are a few examples:

• Create personalized sales presentations and demos.

• Create personalized marketing campaigns and content in real time. 

• Deploy Web 3.0 dynamically customized web experiences that evolve with customer engagement. 

• Refine customer service to pinpoint information of high value to customers and deliver it proactively on their preferred channel.

• Detect problems before they arise -- delayed delivery, software glitch, engine wear, insufficient funds -- and create solutions that work for the customer.

• Give agents and customers the mutual understanding of a situation and suggest the next best action to take.

The advice is for business leaders to educate themselves on the implications of AI. They need to understand not just the technology, but the impact on existing processes and in turn the impact on the culture of the enterprise. Every business leader wants to have a trusted enterprise. 

So, the advice is: To build a Trusted Enterprise with a strong AI footprint, express AI programs in terms that better the lives of employees and customers.  Done correctly – following ethical and humane use guidelines to reduce risks associated AI technologies – Generative AI baked into customer processes will improve customer experience and create unique new moments for success. Proceed with caution, taking small steps into the AI future.

Maoz reminds us that the combination of AI technologies, automation at scale and real-time data analytics, visualization and reporting are key to improving the customer experience.  

This article was co-authored by Michael Maoz, Senior Vice President, Innovation Strategy, Salesforce.

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