Customer AI: Twilio OpenAI partnership headlines SIGNAL 2023
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The current playbook for how businesses can benefit from generative AI is typically a two-step process. The first part involves feeding company data into a large language model (LLM). And stage two is using the next-word predictive powers of that LLM to surface all kinds of business information – from part numbers to contract pitches – all through a conversational interface. Internally, the view is sharpened, but there’s still something missing. To complete the business picture, companies need to know what’s happening client-side, and that’s where customer AI fits in – as Twilio’s Jeff Lawson explained at SIGNAL 2023.
The firm’s CEO and co-founder took to the stage yesterday – at the customer data platform provider’s annual developer conference – to consider the impact of AI on companies, with the help of some special guests. And Lawson framed the rewards in terms of the flywheel effect of customer signals on digital businesses.
Using customer AI to turn the flywheel
“Every website visit, every mobile app, every click, every scroll, everything they buy, everything they don’t buy – those are all signals about the customer and what they are all about,” he told the SIGNAL 2023 audience. “And then you use all of that data to do a better job of engaging with those customers…and when you do, they are more likely to click the email or open your mobile app, and suddenly you start getting more data about them and the flywheel turns.”
The issue for organizations – and the differentiator that puts great digital businesses ahead of their competitors – is allowing those signals to flow freely and avoiding insights becoming siloed. Companies that get it right can lower their cost of sales and tend to have customers who are more loyal and have greater lifetime value (LTV). But keeping that flywheel spinning isn’t easy and momentum is lost when customer behavior is missed.
CRM systems and data warehouses are both steps toward making sense of clients campaigns and the wider business implications. But the difficulty is that more customer interactions generate more signals. And the deeper that companies want to dig into that data – to spin that flywheel – the larger the number of analysts that businesses need to employ, which doesn’t scale.
Or at least it didn’t scale until the advent of generative AI. And it’s telling that one of Lawson’s video guests in the opening keynote presentation is Sam Altman, CEO of OpenAI – a firm that’s shot to fame based on the capabilities of LLMs (GPT-3 and GPT-4, in the case of OpenAI) to summarize vast amounts of data.
What’s also clear is that the benefits of the flywheel effect don’t come by simply retraining, or fine-tuning, AI models with any old company data. Businesses need to be integrating the right information to start reaping the rewards of powerful LLMs. And that gets to the heart of customer AI. “This is something that can truly change the nature of business,” Lawson told SIGNAL 2023 attendees. “Customer AI is a set of capabilities that use predictive and generative AI to perceive your customers, all the signals they are giving you, to form that into an understanding of what [those] customers are about.”
What’s more, customer AI can then activate that understanding across all of the interactions, or touchpoints, that companies have with their clients. And it’s those automated insights that Lawson believes will add up in comparison with previous approaches to keeping that prized flywheel turning.
Altman was candid in his fireside chat with the Twilio CEO about his vision of the future, pointing out that being able to drive the cost of intelligence and energy towards zero will create a massive abundance of resources that place a limit on what’s possible today. From a customer AI perspective, reducing the cost of intelligence by a factor of a million would enable companies to serve clients in a much more personalized way.
In principle, if LLM solutions deliver as promised, AI-enabled services should have an almost uncanny ability to predict what customers want. And their capacity to do this tracks back to those touchpoints mentioned earlier. Every interaction between a customer or potential customer can provide a signal that helps to shape – in Twilio’s case – a personalization engine, which reduces friction and drives business.
And there’s potential to go further with AI too. As models become more adept at spotting business patterns, users could ask them bigger questions. For example, say a company has a certain amount of inventory that it wants to sell at a given profit margin, generative AI with detailed customer knowledge could provide sales strategies based on that information.
Twilio is by no means the only firm to recognize how AI and reducing the cost of intelligence (to borrow Altman’s way of thinking about the future) could change the economics of understanding customer behavior. For example, Adobe provides an Experience Platfom that lets organizations generate customer predictions, using AI-as-a-service, to help firms personalize customer experiences intelligently.
Users can design campaigns to grow and activate new customers, engage with those clients, and retain and enhance those business relationships using insights that, in the past, may have ended up being siloed or overlooked. And highly-customized scenarios can be explored across a range of verticals where previous one-size-fits-all approaches have failed to deliver.
AWS is another provider facilitating customer AI to improve client acquisition and retention, helping firms optimize their marketing efforts. “It helps you get closer to your customers by providing a more personalized experience to increase value and reduce churn by serving the right recommendations, at the right time, via the right channel,” writes AWS partner Peak.
There are signs that the rise in LLM-based services may already be influencing the economics of attracting and retaining clients. In March 2023, global management consultants McKinsey & Company reported that AI-enabled customer service is now the quickest and most effective route for institutions to deliver personalized, proactive experiences that drive customer engagement. And, in the banking segment alone, AI technology could deliver huge numbers to the bottom line through improved customer service.
For clients, this sounds like good news. But whether customer AI is a rising tide that lifts all boats remains to be seen. Timing could be a factor, and judging when to get on board might end up making all the difference.
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