Editorial
The Gist
- AI in customer experience & data. You develop products with the data you have, not the data you wish you have.
- A ‘people’s business.’ The human touch still goes a long way in complementing technology in the AI era.
- The impact of listening. Cutting customer churn by 75% gets execs’ attention.
Artificial intelligence (AI) isn’t sci fi like you see in the movies — not yet anyway, and it probably won’t be for a long time. But because so many futuristic, cyberminded depictions are out there about AI, it’s important to remind ourselves that people — flesh and bones — are still and will always be the technology’s main drivers.
Let's take a look at some aspects of AI in customer experience.
AI Is Moving Into Daily Life
It seems generative AI, which is capable of generating text, images or other media, using generative models, is coming into our daily lives in helpful ways. It is speeding up workflows with ChatGPT, creating images in seconds via DALL-E and writing responses for our emails before we can think of them. And it’s just the beginning, as amazing folks are working on AI software engineering to improve the customer experience (CX) and user experience (UX).
Avalanche of AI Activity
This reality should give us hope, whether as everyday people, consumers or tech-loving professionals. Due to an avalanche of AI software activity since late 2022, generative AI may already be in every enterprise tech stack out there. And for companies that want to remain competitive, it will likely be needed: According to a McKinsey study this summer, generative AI will add up to $4.4 trillion of value to the global economy annually over the next few years.
Generative AI: A Big Deal
Generative AI is a big deal, but we shouldn’t get ahead of ourselves. Before joining ASAPP, I worked at Apple, Samsung, Electronics Arts and other tech companies where I had a front-row seat to AI’s genesis. From my decades of watching this technology evolve and grow, here are three AI-minded tips for CX pros.
Related Article: AI & ChatGPT: Do You Trust Your Data?
When It Comes to AI in Customer Experience, Data Is Never 'Complete'
The AI hype is palpable and has been building for some time, including for AI in customer experience. Two years ago, Google CEO Sundar Pinchai was already proclaiming that the invention of AI will eventually be “more significant than electricity or fire.”
AI Misconception
Though, there’s a misconception that AI can only be as strong as the data it’s fed. While data is the lifeblood of how AI gets smarter and smarter via machine learning (ML), it is still just one piece of how AI works. You still need architecture, algorithms, training processes, computational resources and data cleaning to work together with the data coming in.
Data Never Complete
Further, it’s important to remember that the data set will never be complete, especially in our world full of privacy restrictions and security measures. Therefore, if a CX team waits for “the data to be entirely complete” when designing a product with AI in customer experience, a completed solution might never materialize because there could always be more data to make a system even smarter.
Pushing Beyond Perceived Limits
Sometimes, you just have to go for it. One of the great things I learned at Apple during the Steve Jobs-led era was the huge value of championing meaningful ideas and pushing yourself beyond perceived limits. This mindset can be needed when an engineer feels the data isn’t quite there yet. I believe it’s important to remember that data is not the only quintessential input for AI in customer experience. Furthermore, don’t sacrifice “good” to achieve “perfect.”
Relevant Data Is Key
That said, having enough relevant data is still crucial. The more complex the problem is, the more training data you should have. But leaning into the available data can help product teams avoid a trap — wishing you had more, better data — that stymies product development and could keep your CX lagging behind the competition.
Related Article: How AI and Data Analytics Drive Personalization Strategies
Remember That It’s Still a ‘People Business’
CX leaders like ourselves are in the business of using data to make the customer journey seamless, and we see AI’s superb potential for greater personalization and solving old problems. But we need to remember that the human touch still goes a long way in complementing technology in the CX — it’s still a “people business” even in the age of AI.
Listening to Customers
I’ve always loved talking to customers and still do. It’s all about the impact we can make by simply listening: Per McKinsey, an unnamed CEO, in recent years started listening in to customer calls to learn about customers’ frustrations, leading him to revamp policies while reducing customer churn by 75%. As the CEO reportedly said: “It’s amazing the things you can do when you shut up and listen to your customers.”
Paying Attention to Customers
Customers want to spend money with a brand that’s paying attention. Studies have shown that CX drives over two-thirds of customer loyalty (more than brand and price combined), while 66% of consumers say they will share personal data about themselves if they think it will improve their experience.
Tailor Tech to Customers' Requirements
The driving question for CX leaders should almost always be: What does the customer seek from this interaction with our brand? Brands must offer technology that is tailored to the customer's requirements, ensuring seamless speed and an experience aligned with their expectations, whether via a chatbot or a phone call.
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AI Is a Human Creation
As brand experiences evolve, AI in customer experience will solve more and more real problems. AI’s not a “futuristic, sci-fi idea” anymore, and it never truly was because it’s a human creation. As AI improves CX and UX at scale, that potential should fascinate every leader in this space.
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