top of page
Search

Building Smarter Arts Organizations: What Worked, What Didn’t, and What’s Next with TRG's Stuart Nicolle

Eugene Carr




Summary: In this candid and insightful conversation, Gene talks with Stuart Nicolle, Chief Information Officer at TRG Arts and founder of Purple Seven, about the continuing challenges—and opportunities—at the intersection of arts, technology, and data. From his early days in London stuffing paper surveys for the Royal Shakespeare Company to building one of the first real-time event ticketing analytics platforms, Stuart shares his journey as a creative technologist with a passion for the live performing arts.

The discussion talks about how smart segmentation, behavioral recommendations, and AI-powered tools can unlock growth—but also why great ideas often fail when they don’t align with institutional business models. Stuart offers his advice for aspiring arts-tech entrepreneurs and a hopeful vision for the future, where even small cultural organizations can access enterprise-level insights through shared platforms and smarter infrastructure.

Gene:

Okay. Hi, everybody. I'm here today talking with Stuart Nicolle, who today is the Chief Information Officer for TRG Arts, which is an arts consulting company based in Colorado, but also operates around the world and in the UK, which is where Stuart is. Stuart and I have known each other for a very long time. I want to start at the beginning. You've been involved in arts and technology for a long time. Let's go back to the roots—how did you manifest your interest in the intersection of arts and technology?

Stuart:

I guess in my first job, a marketing director said two things to me that have stuck with me since—this is early 2000s, maybe late '90s. One of those things was highly strategic, the other was deeply tactical. At first they seemed completely at odds to me, but I didn't realize those ideas would drive pretty much everything I've done since.

He told me that he was working to one marketing strategy, but he wanted a hundred thousand strategies—one for each patron. Then he said his biggest frustration was, “I know that half of my brochure mailing is wasted. I just don't know which half.”

That blew my mind. How could you have this future vision of hyper-personalization and not know which half of your brochure is working? That changed things for me. I'd just finished my master's in arts administration. I’d majored in statistics and quantitative research. That’s when I thought, I can make a difference.

Also, I come with a background of being a classically trained, although not very good, double bassist. So I’ve experienced firsthand the impact that live performing arts can have. That’s become my obsession over the last 25 years—how do we use data and technology to ensure that live performing arts not only survive, but thrive?

Gene:

Out of that spark, you started a company—Purple Seven. How did you get it going, what was your first product, and how did that go?

Stuart:

Before we started Purple Seven, I was a market analyst for a regional audience development agency in the UK. At the time, ticketing systems were new, and I saw all this data just sitting in them—unused, latent data. We came up with this method that makes me laugh now. We wrote a software program called Data Crunch. To power it, we had to ask venues to extract their ticketing data, burn it onto a CD, and post it to us. We’d load it onto our computers, into a Microsoft Access database. That powered the software, which we’d then burn onto a new CD and mail back. The venue would load it and get insights.

That was insane—but it worked. It gave around eight or nine key insights, and they were still good. It doesn’t work anymore, but it was a great product for its time.

I was also in charge of surveys back then. I was responsible for the Royal Shakespeare Company’s quarterly surveys. We had to print and mail them, include return envelopes, and wait for responses. Everyone wanted to share their thoughts, so we ended up with masses of survey responses. Then we’d get a team to input all the data and digitize it for analysis.

We’d write a report to the RSC, and it was all very time-intensive. I think I’m a good developer because I’m lazy—so I always look for shortcuts. The company I worked for was publicly funded. If we wanted to change the software, we had to apply for a grant, pay a developer, and then give the software away for free. It wasn’t a good environment for building solid software. So the developer, my wife, and I left and started Purple Seven.

The goal was to automate insights and drive action. Our first tool was for venues—it pulled data from their ticketing systems in real time onto our web servers, which was a big deal in 2002. Venues got live, automated insights, could build mailing lists, and segment their data.

But that wasn’t our first sale. That was the first product we built. The first product we sold was to a marketing agency in Manchester. They wanted the tool for all their venues and needed aggregated insights. We pivoted quickly, integrated with different ticketing systems, and launched it. That was really the start of Purple Seven—benchmarking and regional analysis.

Gene:

Tell me the arc of that business—how long did you work in it, and what were some of your successes and challenges?


Stuart:I think I’ve had more failures than successes -- but I had three wins. One was solving the problem of brochure waste. I built something called Balance Database—a segmentation system that predicted who was most likely to make a purchase. And it worked. I proved through data that you could cut your mailing in half without losing revenue. That was big—but short-lived, which I’ll come back to.

The second was a recommendations engine that used behavioral data to predict what you’d attend. So now I knew who would attend and what they’d attend.

But --- both failed, spectacularly. I hadn’t considered the business context. I’d solved the problem in an ivory tower, but venues didn’t want to cut mailings. Touring companies paid to be in brochures, so success was measured by how many brochures got sent. Cutting that in half? Not appealing!

The recommendation engine worked technically. It curated the Barbican’s homepage for each user, increased purchases, and they used it for years. But it took eight hours a day to process data for one venue. Not scalable!


What we learned was that people need action tools—tools that help them act on insights. Back then, most people were looking in the rearview mirror. We were trying to show them the road ahead.

The one thing that really succeeded was our surveys tool. It sent automated post-show surveys linked to ticketing data. So you didn’t have to ask how much they paid, or where they sat—we already knew. That meant we could analyze price sensitivity, first-time visitors vs. regulars, and more. That became a real success.

Gene:

Let’s jump to now. Organizations are still grappling with many of these same issues—using systems from the 2000s or earlier, struggling to understand customers. Do you think that’s still the state of the field? And what are you working on now that might change it?

Stuart:

It’s slightly depressing. I remember being out with two seasoned consultants around 2007. They said nothing had changed in the past decade—and were disheartened.


But I think change is finally coming. We’re on the brink of real transformation, and a big part of that is AI—leveling the playing field. Technology that used to be available only to big institutions is now accessible to smaller ones.


At TRG, we’re taking the Purple Seven product library—previously only available in the UK—and combining it with TRG’s experience to deliver value to North American organizations. It follows a “plan, do, review” cycle. Plan your shows, act to make them successful, then review and learn.


We have organizational-level insights down to individual events. Trackers use AI to create sales trajectories—for single tickets, donations, subscriptions—and show how you're doing against those. If you’re underperforming, it helps pinpoint where—do you need more single ticket sales? More acquisition?

Surveys are plugged in too. And they’re powerful because motivations matter. My motivations vary: "I’ll attend classical concerts alone, plays with my wife, and something else with the kids." So, if you only look at my purchase history, you miss that.


Understanding motivation lets you make much better recommendations.


Gene:

You're an entrepreneur who’s been building tech for arts orgs. How easy is it to start a company in this space? What advice do you have for people in their 20s who are passionate about the arts and want to make a difference?

Stuart:


It’s tough. Cultural orgs don’t have deep pockets. Any investment has to reduce costs or increase revenue—ideally both. Teams are stretched, so a new product has to create capacity, not consume it.


Also, philanthropy plays a huge role. In 2019, $6 billion was donated to arts orgs in the U.S.—but most of it went to close operating deficits, not to invest in tech that would make them sustainable.

That’s the opportunity. If orgs don’t use tech to personalize and modernize how they engage audiences, they won’t just struggle—they’ll collapse. And when that happens, we lose more than ticket sales. We lose part of what makes cities and communities vibrant. Arts make us human. That’s something I believe deeply.

Gene:You’ve nailed exactly what I care about too. Cultural orgs struggle to stay afloat. But AI can help us do things faster and smarter. It’s not about replacing people—it’s about making our jobs easier. If orgs are looking for a quick way to improve, tech is the way. That idea isn’t yet intuitive for many people. That’s part of why I’m doing interviews like this—to spread that message.

Stuart:I totally agree. One last piece of advice for young founders: build something that helps groups of orgs run on the same platform. Share tech, share costs. That’s where the impact is. Otherwise, every org becomes a unique snowflake with its own tech setup—and that’s not scalable. We’re starting to see it with ticketing consortiums. That model could apply to lots of other areas too.

Gene:


This has been a great conversation. You’re still in the thick of solving these problems, and I’ll be eager to see your new products roll out in the U.S.

Stuart: Thank you, Gene.

Comments


bottom of page