Qualtrics CEO explains why AI should be used to elevate the human experience between organizations and consumers

Derek du Preez Profile picture for user ddpreez March 7, 2024
Summary:
Zig Serafin, CEO of Qualtrics, explains to diginomica that the proliferation of AI means that consumers will pay a premium for human-like experiences with organizations. But we need AI to build a ‘memory’ of our consumers to facilitate how we engage with them.

qualtrics
(Qualtrics)

The last time diginomica met with Qualtrics CEO Zig Serafin was at the company’s annual customer summit in Salt Lake City, Utah, in March 2023. At that time, the hype surrounding generative AI and ChatGPT in particular was still building, but few vendors had laid out their plans for how the quickly developing technology would be adopted in the enterprise. As such, our discussion with Serafin then was largely focused on why ‘the new blueprint for operating a digital company is experience’. 

Qualtrics is the leading vendor in the field of ’experience management’ (XM), and provides a platform that integrates siloed data from systems of record, bringing that information together to allow organizations to turn these into ‘systems of action’. There are a variety of use cases described in our previous pieces on the vendor, but the top level overview is that Qualtrics provides buyers with real-time information about their customers or employees - how they are feeling at any moment or time, with context about how they’ve felt in the past - to enable them to adapt and respond to their needs. 

However, AI is now front of mind for buyers, vendors, investors and consumers - and everyone is very aware that decisions made now could impact their competitive advantage in the future. AI is the new gold rush. 

Earlier this year Qualtrics itself announced a $500 million investment in AI across its XM platform, focusing on product areas that include Generative AI for frontline teams, real-time agent assist, as well as automated call summaries for contact center agents (amongst other things). 

However, there are some very valid questions about how AI will change how we interact with organizations. Not all technology advancements have resulted in more positive experiences with companies (anyone who has tried to argue with an automated voice tool whilst trying to ring a call center can attest to this). So, how do we use AI to enhance the relationship between a buyer and seller? Sitting down with Serafin this week in London, he certainly has some ideas. He said: 

AI will actually make businesses more human. Part of the draw towards that is that human beings are people and consumers will pay a premium for a better human connection between them and the organization that they do business with. 

Well, how does that happen if we're using AI? Using AI, as part of the Qualtrics platform, you have the ability to better come to know how someone feels about something and how that might correlate with their future likelihood to engage with your business. 

But it’s important to note that key to this thinking is an organization’s ability to look across its data silos, pull information about its consumers together into one platform, and gain insights using effective analysis. Some vendors have an advantage in this area, having been working on a platform strategy for a number of years (Qualtrics included), and having seen data analysis, automation and AI as central to their focus prior to the onslaught of ‘AI everything’ in recent months. Commenting on Qualtrics’ advantage here, Serafin said: 

I came to the company (Qualtrics) because I left a job working on probabilistic based computational learning at Microsoft. I realized that the human in the loop, the human feedback loop, is going to be extremely important to building high precision models. 

However, understanding how to collect and engage and connect with data is an I/O psychology problem. It's not just building a form or a template. It's about methodologies that have been proven for several decades that are from a very different domain, and you had to actually merge that domain with software that actually allows you to be able to build probabilistic outcomes and become even more precise over time in how you do it. 

Well, that is actually machine learning. And so we've been doing that for four plus years. Now, obviously, people have introduced the label of AI. And it is true that the AI techniques have become far more comprehensive, and far more expedient, as more computing power has been brought to the equation and as models have become more sophisticated. 

But for us, this is a continuation of a trend that we've had - and we're also starting to see step functional improvements in what we're doing.

Building a memory 

Serafin’s central hypothesis is that AI can actually make organizations ‘more human’, but that this isn’t a given. On the one hand it requires this platform approach to pull information into one place and place real-time analytics in the hands of people to make the necessary changes. And on the other hand it requires companies to reorganize their strategy around ‘experience’, giving people the authority to adapt based on the information they have available to them, and make changes based on the feedback they’re getting. Key to this is the data. Serafin explained: 

If you look at the role of AI and experience management, it goes hand in hand with the dataset. The dataset is an extremely precise understanding of how people feel in the moments that matter the most, which provides you a very strong indicator for what will happen in the future, given what people have told you. 

And some of that telling comes from them directly responding through solicited information. And some of that is actually people telling you without you ever asking. For instance, the data that is in your call center. The data that's in your social media experience. Or the data that employees might be providing as part of cases and tickets that they're writing, given troubleshooting issues. 

And we're able to synthesize from that, provide a clear signal, and then build models that help to be able to drive action at scale, that drives revenue growth, that helps to create cost efficiencies inside of a company, that helps to be able to drive better employee engagement and productivity as a result of that as well. That's the approach that we're taking to AI.

Qualtrics has built a compound AI system, which allows it to use a variety of different models. It started years ago with Meta’s Llama, but now uses OpenAI’s GPT and Mistral too. In other words, it’s not tied its future to one approach and aims to use the best models for the best outcomes, depending on which circumstances are at play. 

Serafin said that organizations need to think about building a ‘memory’ that focuses on experiences, making that ‘memory’ of how consumers feel readily available to frontline users, and other members of an organization, to allow them to better service their customers. He added: 

Using AI you can build a better memory, and then use that memory to be able to be proactive in actions or suggestions. Those suggestions or actions might come in the form of a mobile experience or an app or an agent that's interacting with you. Or it might come by way of enabling a frontline workforce just to serve you better. 

Being in a position where you can actually start to enable the frontline to be more well aware and suggest things that suit people more effectively helps an organization to be more human. We have deep research and evidence that companies will ultimately benefit from that and they become more profitable. 

A platform of platforms approach

Serafin is keen to reiterate that your understanding of your customer based on their interactions with your website, for example, may well give you a false idea of how your customer genuinely feels about your organization and your interactions with them. This is just one small part of a story that needs additional information from all other touch points, or data sources, that are available. 

Businesses have historically organized themselves around siloed departments, and then siloed systems of record, which make this difficult. For instance, HR, sales, finance, customer service, etc. Serafin said: 

Consumers, each individually, is the sum of all those things. But most businesses have been set up and organized in a way where each of those are separate departments. So over time, they created separate systems. That means the COO or the CEO or the CMO of the company would get a fragmented view and every department would be saying ‘I’m doing my part’.

But in this day and age that’s not enough. Qualtrics’ ambition is to become Ader connective experience tissue that ties an enterprise together. He added: 

It becomes a platform that orchestrates where and what interaction makes best sense. I'll use an airline as an example. An airline's ability to say, ‘I'd like to communicate with my customer through the mobile app’. 

Qualtrics fires off the request and creates the behavior inside that mobile app, because we're orchestrating that. At the same time, we're also triggering an alert inside of a ticket that's facing a customer service agent saying, ‘for any other customer that looks like that one, do the following’. 

A company does not have to go and replumb the plumbing that they already have today. They plug in Qualtrics and now they're supercharging the way that their systems of record and systems of engagement have been designed to work, because of the experience with data.

I put it to Serafin that this approach sounds very similar to ServiceNow’s strategy, of becoming a ‘platform of platforms’ across a company’s systems of record, to make work flow across an organization, as well as outside of an organization’s borders to customers. Serafin said that ServiceNow and Qualtrics are very complementary, which is why they already have an existing partnership. He added: 

Anywhere the ServiceNow building block workflow engine exists, you want Qualtrics. You've put in place the plumbing layer for workflow, now you’d like to be able to optimize the way that workflow works based upon the singularly most important dataset that your company has access to - which is your customer and employee experience data. 

Now you can say ‘I’d like to do the proper reasoning and inferencing on, have the right intelligence, so all that plumbing is actually optimized’. That’s what Qualtrics does. 

It’s gold

Serafin said that if an organization is able to deploy Qualtrics, put this real-time data in front of users that can act on it effectively, and respond to the needs of customers, then that company will likely build ‘fans for life. He said: 

We like to say that the experiential data has a very short half life. That means that it's gold, it's magic, but you better do something about it. If someone has entrusted in you something that they're happy or unhappy about, you need to act. 

Commenting on the experience of organizations Qualtrics has worked with, he said that companies have been able to reduce the cost of what it takes to serve a customer, whilst also improving retention of employees, and bettering satisfaction rates across the board. He added that a lot of this has to do with the speed at which organizations can understand how to connect with someone and do something about it as a result. 

However, his advice for buyers at the start of this journey is to start small. Serafin said: 

Start with basics, and in small ways. It's often that a solution that can be configured within a few hours on our platform, will yield very significant results for an acute problem, or an acute opportunity, that people are going after. 

The platform has been designed in a very simple way, so that you don't have to hire a lot of extra overhead to be able to get going. And then bit by bit, you start to connect the dots with the different solutions that you have and you start to develop a very valuable asset that can be used to be able to run your company differently. 

But you can start small, that's the beautiful part, based upon a pressing problem, no matter how large or small.

My take

A compelling pitch from Serafin and Qualtrics. It’s quite telling when I speak to a vendor that has clearly been using data and intelligence for years as a central part of their strategy - and this ‘AI Revolution’ is just a continuation of a theme. It’s helpful to awareness, but it was already part of the plan in many respects. diginomica will be at Qualtrics’ 2024 customer summit in Salt Lake City in a couple of months, where we look forward to hearing the user stories - and how they’re thinking about experience in combination with AI. It’s not easy to center your organization around an experience strategy, listening is difficult. You don’t always hear what you want to hear. But in a world where consumers have plenty of options, experience is everything. 

 

 

 

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