How Qualtrics is driving experience management

Qualtrics, a supplier of cloud-based experience management software, is on a mission to shape the way businesses interact with their customers and employees – by gleaning data on human sentiments and emotions and providing recommendations on the best course of action.

It recently announced that it would invest $500m over the next four years to build more artificial intelligence (AI) capabilities into its platform and use the billions of experience profiles it has amassed to train its large language model, which can be used to coach customer-facing employees.

Qualtrics was acquired by German software giant SAP in 2018, only to be spun off through an initial public offering (IPO) less than two years later. In March 2023, the company was taken private through an acquisition by private equity firm Silver Lake, in partnership with the Canada Pension Plan Investment Board.

In a wide-ranging interview with Computer Weekly, Qualtrics’ president for products, user experience and engineering, Brad Anderson, and its Singapore-based head of Southeast Asia, Mao Gen Foo, outlined the company’s product directions, including its work in AI, its traction in the region and the future of its platform.

Could you tell us more about the work that Qualtrics is doing in AI?

Anderson: We’ve participated in a number of what I would call big platform transformations over the past 30 to 40 years. Over that time, the internet has completely transformed how products are built, and what’s happening in AI right now is going to be bigger than what we’ve seen in the past. It’s going to impact every function, and every company is going to benefit from it.

The potential of AI to enhance humanity and advance the human experience is quite remarkable. But it’s important to understand that AI is only as good as the data that you have to train the models. And so, organisations that have the most unique datasets are going to be those that will deliver the most value.

We’ve been in business for more than 20 years, and we have the largest collection of human sentiment and human emotion data on the planet. It’s organised based on what we call experience identities. Every time a customer or an employee of one of our customers interacts with a company, we store that experience in a unique profile. Today, we have more than 12 billion profiles which are growing at 60% year-over-year. By the end of 2023, we would have more than 16 billion profiles.

What that allows us to do is use all of that human experience and sentiment data to train our models, giving us a very unique large language model that we can then deliver value from. Over the next four years, we’re going to invest more than $500m in R&D specifically related to AI. We believe AI can make businesses more human because it can be used to coach frontline workers on the best way to serve a customer and deliver the best experience.

Since we’ve been taken private, we’ve had $1.7bn in annual revenue and 20,000 customers that are using our technology in a category that’s still in its infancy. The upside potential and opportunity for Qualtrics to be the next great enterprise tech company is one of the things that attracted me from Microsoft

The business impact of that is huge. It’s well understood that happy customers spend more with an organisation, but Harvard University recently conducted some interesting research which found that customers who are emotionally connected to a brand are 52% more valuable to a company than customers who are highly satisfied. And so, one of the things we see in AI is the ability to help organisations deeply connect with their customers by delivering very personalised experiences in a very human way.

What sorts of capabilities are you looking to build with the $500m investment? Also, is the large language model proprietary to Qualtrics, and what kind of guardrails are you putting in place to tame the AI beast?

Anderson: Let’s start with the latter questions. What we’ve built for our engineering team is an AI bench that has a set of third-party large language models as well as our own first-party models. That allows us to use the best model that’s fit for purpose. It also enables us to manage costs because large language models can get very expensive to build.

As to how we do the safeguarding, it’s aligned with what the industry is doing to check for biases and hallucinations. You have a stage gate where what gets exposed to the public is different from what your team is working on. We’ve been doing AI for five to six years, and we’ve learned from the industry the best way to do that. Our engineering team is made up predominantly of people whom we’ve recruited from Microsoft and Amazon. There’s a lot of enterprise security and privacy experience on the engineering team and we bring all of that together to build different capabilities.

For example, you could use ChatGPT to conduct digital interviews at scale and collect feedback rather than send out surveys. Another example is helping customers research what they should do with their products and brands. Historically, that’s been quantitative, but now we have qualitative capability where we can use ChatGPT to look at a focus group interview, identify key themes and create reels for business leaders to hear the voice of the customer. On the employee side, we can use AI to look at conversations that employees are having on public Teams or Slack channels and tell how employees feel about their experience working for you.

Your customers would already be using different tools such as contact centre systems to support different customer touch points. How can they tap Qualtrics’ capabilities to improve customer experience?

Anderson: We integrate with and extend those platforms. Most companies already have a solution that their frontline employees are using, whether it’s for voice or chat, and we integrate with those solutions to get a feed of the voice call, for example. And then we apply our AI to that voice call to help agents better understand the emotions of their customers. We extend rather than replace solutions like that.

But at the same time, those platforms now come with more native AI capabilities. What are your thoughts on that, and how is Qualtrics maintaining its value proposition?

Anderson: We’re always trying to stay ahead of the innovation that we’re delivering to market. Again, you know, in this world of AI, it’s the dataset that you have to train your models that’s the differentiator. There are many organisations that are just beginning to build out their datasets, but we’ve been doing that for more than 10 years. We have so much information that our models are always going to be ahead of anybody else in the industry.

And we’ve got data in 55 geographies and 65 industries. You can go in and say, “Help me understand the benchmark for a specific customer experience metric and I want to look at that metric for the financial industry in Singapore”. And I want to be able to ask questions like, ‘If I want to move to the 90th percentile in inclusion in Singapore and Japan, what would I need to do?”

We’ll look at the benchmark data we have across 12 billion experience identities and tell you what organisations in the 90th percentile for inclusion have done, and say, “Here are the things that you can do.”

What sorts of conversations are you having with customers in Southeast Asia? What is the typical entry point? Qualtrics is known for its customer experience capabilities, but are your customers increasingly using your platform for employee experience as well?

Foo: A lot of customers use us for multiple customer channels because that’s the key proposition we bring to the table. We’ve helped many of these organisations to break their silos. For example, Vietnamese conglomerate Vingroup was rolling out a new electric vehicle last year in America and Germany. They wanted to make sure that their product, brand and customer experience – which were being managed by different teams – were spot on as they were up against the likes of Tesla.

To your question around employee experience, the Covid-19 pandemic has driven more organisations to listen to employees. IHH Healthcare, for example, is using our solution to listen to 68,000 employees across the region and to understand what’s needed to make sure that their employees are well taken care of. But they are not stopping there – they are going one step further to find out how employee experience is impacting their patient experience and patient outcomes, which in turn affect their financials.

When I started the company’s operations in Singapore in 2017, I was trying to get people to see experience management as a category, as employee engagement, customer experience and branding were managed in silos. When we started to educate the market and engage our clients, people got very excited. Today, nobody disagrees that experiences are interconnected, but the challenge is finding the talent to understand and bring everything together.

We went to the Economic Development Board (EDB) and spoke to them about the upcoming experience economy. Clearly, Singapore is lacking those sorts of talent, and if we want to be an innovation hub, we will need to address that. So, in 2021, EDB, together with Qualtrics and SAP, launched a centre for experience management, with the goal of building awareness and talent. Since then, we’ve partnered with SkillsFuture Singapore to advance learners’ experience and identify new areas which we will need to train people on.

Qualtrics was taken private by Silver Lake and the Canada Pension Plan Investment Board. How has that made a difference to your R&D and the way you’re addressing the needs of the market?

Anderson: I honestly believe that Silver Lake acquiring Qualtrics was one of the best things that has happened to us. I’m very excited about the future because of their track record and the best practices they bring. Having the knowledge and expertise from the companies they’ve worked with made it much faster for us to make changes.

IHH Healthcare, for example, is using our solution to listen to 68,000 employees across the region and to understand what's needed to make sure that their employees are well taken care of. But they are not stopping there – they are going one step further to find out how employee experience is impacting their patient experience and patient outcomes

If you think about it, we are one of the largest pre-IPO companies. Since we’ve been taken private, we’ve had $1.7bn in annual revenue and 20,000 customers that are using our technology in a category that’s still in its infancy. The upside potential and opportunity for Qualtrics to be the next great enterprise tech company is one of the things that attracted me from Microsoft.

Qualtrics has also now spent about five years with SAP. What were the learnings and expertise from that time that could help Qualtrics moving forward?

Anderson: One of the biggest things that helped was our significant break into the enterprise. SAP is one of the most trusted brands on the planet by enterprises and chief information officers. Being a part of SAP helped us to understand the best practices and policies of enterprises, so we can make sure we’re meeting all the enterprise-grade requirements.

SAP also helped us to get into some of our first large customers. As you’re building software, you have to work with customers to deeply understand what it is that they need help with and what you can do. And so, helping us to break into many of the world’s largest companies has enabled me to take the product forward faster.

I think those were the two things, more than anything else, that SAP gave us. Without SAP, we wouldn’t have scaled to $1.7bn in revenue. They were fundamental in helping us to scale our revenue and understand what it means to grow at that kind of enterprise-grade level.

Where do you see the Qualtrics platform evolving? You’ve talked a lot about AI, but what is the vision that you’ve set for yourselves?

Anderson: I love the question because it shows that you understand the value of our platform. The things we’re building that will benefit every single use case is obviously AI, as well as putting all that experience data to work to get the best actions, recommendations and predictions. In many ways, you can think of Qualtrics as becoming a data company, in addition to being an experience management company because of all the data we have.

We’re also moving everything about experience management – which has been about getting and acting on feedback post-interaction or post-transaction – into real-time. One major thing we’re trying to do is recommend and deliver the best experiences in the moment and not after the fact. Those real-time recommendations will be driven by AI, data and the benchmarks we have to help an organisation understand what their best actions should be.

Finally, Qualtrics has been known as a survey company. Our customers often deal with structured solicited data, but what’s happening in the market is that customers are now feeding unstructured, unsolicited data into our platform. This combination of structured solicited and unstructured unsolicited data coming together to give that 360-degree view is what our platform is really invested in.