Andrew Gold December 9, 2024

How to Embrace Design in 2025: UX Trends You Need To Know

A new year is around the corner, and with it comes a wave of new opportunities for organizations to step up their game in digital strategy and product design. Whether it’s delivering unforgettable user experiences, empowering employees with better tools, balancing needs across omnichannel experiences, or ensuring accessibility for everyone, the trends shaping the future of design and UX are all about creating meaningful, impactful solutions.

If you’re looking to design products that truly resonate—whether for your customers, employees, or the world at large—these are five big trends to keep on your radar. Let’s explore how each can make a difference and what you can start doing to stay ahead.

1. Personalizing user experiences with AI

Let’s be honest—personalization is no longer a luxury. People now expect apps, tools, and services to know what they need and deliver it before they even ask. AI is the engine behind all of this magic, enabling products to tailor experiences based on user preferences, behaviors, and goals.

Why it matters in 2025
The evolution of generative AI models, such as ChatGPT and Bard, has transitioned from experimental phases to now practical applications. AI-powered personalization makes users feel understood and valued, which builds trust and loyalty. Whether it’s a business tool that learns a user’s workflows or an app that suggests relevant next steps, personalized experiences are becoming a baseline expectation. In 2025, expect enterprises to integrate these AI-driven personalization tools into large-scale platforms, like CRMs and ERP systems—moving beyond pilot projects into full-scale deployment.

How to get started

Be transparent about data: users are more likely to embrace AI-driven personalization if they trust you. Be clear about what data you collect, how you use it, and how you’re keeping it safe.
Think multi-channel: users interact across multiple devices and platforms, so make sure your AI systems provide consistent experiences everywhere.
Start small, but think big: begin with focused personalization features that add clear value, then expand as your systems and data capabilities grow.

By leaning into AI-driven personalization, you’ll not only meet user expectations but also create a smoother, more intuitive experience that keeps them coming back.

2. Turning data into action with analytics

Data has been a buzzword for years, but in 2025, it’s all about what you do with it. Advanced analytics tools are giving enterprises the power to understand users better, predict behaviors, and make decisions faster. It’s like having a crystal ball for UX.

Why it matters in 2025
Customers and employees expect seamless, problem-free interactions. Advanced analytics can spot issues before they happen, helping you design systems that are proactive, not reactive. Imagine catching a bottleneck in your user journey before anyone complains—that’s a sign of better control over your systems. The introduction of new tools and APIs in late 2024 has made real-time analytics more accessible. This development enables organizations to implement predictive analytics practically, thereby facilitating better proactive decision-making.

In addition, the growing adoption of AI in analytics provides businesses with prescriptive guidance, not just raw data. In 2025, enterprises will leverage AI to receive more actionable recommendations, a capability that was still somewhat emerging in 2024.

How to get started

Focus on meaningful metrics: don’t just track everything—identify the user behaviors that matter most and use analytics to monitor and improve them.
Bring everyone on board: make analytics insights accessible to all your teams—designers, developers, and decision-makers. This way, everyone can act on the data.
Embrace iteration: use analytics to test, learn, and tweak your designs. The best products are always improving.

When you use analytics to guide your decisions, you can create experiences that feel smooth, intuitive, and perfectly in tune with what your users need.

3. Digging deeper with digital ethnography

If you want to design products people truly love, you need to understand not just what they do but why they do it. That’s where digital ethnography comes in. This method lets you study how users interact with your product in real-life situations, giving you insights that surveys and focus groups simply can’t.

Why it matters in 2025
User behaviors are more complex than ever, and traditional research methods often miss the nuances. Digital ethnography lets you see your product through the user’s eyes—literally, if you’re using tools like video diaries or screen recordings. Post-pandemic, remote and hybrid work models have mostly stabilized, allowing researchers to fully embrace digital ethnography. In addition, the development of new mobile and wearable technology in 2024 has enhanced the ability to collect rich, context-aware user data in real time. By 2025, these tools will become widely available, making digital ethnography scalable for enterprises.

How to get started

Make it easy for users to share: use tools that let participants capture their experiences naturally, like mobile apps for documenting tasks or workflows.
Act on what you learn: turn insights into actions—whether that’s simplifying a confusing workflow or addressing an unmet need.
Keep listening: user needs evolve over time, so make digital ethnography an ongoing part of your design process.

By truly understanding your users, you’ll be able to create products that not only meet their needs but feel tailor-made for their lives.

4. Building better tools for employees

Let’s not forget—employees are users, too! They need tools that are as seamless and intuitive as the customer-facing products you create. Unfortunately, enterprise tools often lag behind in user experience, which can lead to frustration and inefficiency. At this point in 2024 there is now a heightened recognition and acknowledgment that applying consumer-grade design principles to employee tools directly impacts productivity, retention, and business outcomes. We expect this investment in employee tools to continue on into 2025.

Why it matters in 2025
In a hybrid work world, employees rely on technology more than ever to stay connected and productive. In 2025, refined solutions will integrate productivity, collaboration, and well-being features into cohesive ecosystems, addressing the evolving needs of the workforce. By investing in tools that prioritize ease of use, collaboration, and well-being, you’ll not only boost productivity but also show your employees they’re valued.

How to get started

Ask employees what they need: don’t guess—conduct quant and qual research to understand workflows, pain points, and opportunities for improvement.
Blend function with delight: employees are used to slick consumer apps. Bring that same level of polish to your internal tools.
Measure and refine: use analytics to track how employees engage with tools and refine the experience to better meet their needs.

Great and easy-to-use tools lead to happier employees—and happier employees create better outcomes for your customers and business.

5. Designing for accessibility and inclusion

Accessibility isn’t just about ticking a box—it’s about making sure everyone can use and enjoy your product. From people with disabilities to those in different cultural or linguistic contexts, designing for inclusivity creates better experiences for all users. Designers have been voicing the importance of this for years and now we are at the point where it is becoming more of the norm inside design processes to consider a wider variety of user types.

Why it matters in 2025
Accessibility is no longer optional. Updates to the Americans with Disabilities Act (ADA) and European accessibility regulations in late 2024 have certainly brought accessibility to the forefront. It’s a legal requirement in many places, but beyond that, it’s simply good business. When you design with inclusivity in mind, you expand your audience, build goodwill, and create more equitable experiences.

How to get started

Test early and often: don’t wait until the end of the design process. Test for accessibility at every stage to catch and fix issues before they become major problems.
Think beyond compliance: standards like WCAG are a starting point, but true accessibility means creating delightful, intuitive experiences for all users.
Educate your teams: make sure everyone involved in product development understands the principles of accessible and inclusive design.

Furthermore, AI-driven accessibility solutions have become more viable, enabling companies to detect and address accessibility issues in real time during product development—a capability that was not reliably available in 2024. Accessibility isn’t just the right thing to do—it’s an opportunity to innovate and create products that work better for everyone.

Looking ahead to 2025

These trends—AI-driven personalization, advanced analytics, digital ethnography, employee experience tools, and greater focus on accessibility—are reshaping the way organizations think about user experience. By embracing these ideas now, you’ll be ready to build smarter, more inclusive products that delight your users and drive your business forward.

At Grand Studio, we’re here to help you navigate these trends and design solutions that make a difference. Let’s make 2025 the year you transform the way your users experience your products.

Grand Studio August 23, 2024

A Checklist for GenAI Readiness

This is the first in a multi-part series about Generative AI, focused on how to set up your Generative AI project for success. Whether you’re new to GenAI, or have your own tactics to share, there’s more we can all learn about implementing this new technology.

With the many offerings available now in the GenAI landscape, from OpenAI’s DALL-E and ChatGPT – already at a 4o version—to Meta’s LLaMA, to Microsoft’s Orca, to Google’s multiple AI offerings, Generative AI Large Language Models (GenAI LLM) now feels a bit inescapable. It can be easy to get caught up in the excitement about adding a GenAI LLM-enabled tool to your company’s portfolio, but it can be difficult to know where to start, and what needs to be in place to succeed. So before we discuss the various offerings or how to implement LLMs, let’s take a look at how you can set your team up for success—whether you’re in Engineering, Product or Design—before embarking on your next GenAI LLM project.

Know what you can change with LLMs – and consider how you can change the rest
This is a question we think about all the time at Grand Studio: what problems can – and should – be solved with a given technology? With technologies as complex as LLMs that involve trillions of tokens, years of training, and millions of dollars, designing a new LLM might be a bit out of reach for many. But even for those who can access these solutions, it still doesn’t mean that all aspects of their problems should be solved with a GenAI modality. That’s why exploring what the problems are, how users behave and what tools they use, as well as what combination of solutions may most holistically address the issue(s) is an important first step. And if a GenAI LLM is in fact the right solution, there may still be quite a few elements of a problem that can be solved for and improved outside of a GenAI.

One recent example came up as we were designing a GenAI LLM solution: one of the use cases we wanted to tackle had to sit outside the solution’s access point due to security measures and therefore could not be addressed by the GenAI. We were able to do a UX/UI heuristic pass and create a set of digital UX adjustments that reduced the issues with that use case so much that the amount of money the enterprise was spending dropped an entire contract tier. So don’t underestimate the impact of UX/UI within a holistic solution.

Clean up your data
We’ve said it before and we’ll say it again: your GenAI will flourish or fail depending on how clean and organized your data set is. The general data sets that inform current LLMs are massive and in order to get answers that are relevant and accurate for your company, or even your industry, you’ll likely need to help the LLM focus in some way. Data lakes – essentially centralized areas for your data that an LLM can be required to check first before generating answers, and carefully crafted back-end directions on what information to present – and how – (called system prompts) can help your LLM prioritize certain data before going into its general knowledge. The trick is that data has to be organized, well-written, and clean of errors first. This can be a big ask if you are the kind of company that has a huge knowledge base archive that maybe hasn’t been overhauled in years.

One way to tackle this is to start small(er). You won’t be able to get away with only 100 clean pieces of data, but you might be able to get away with ~ 1000. Starting small and establishing a content governance structure can help you out in the long run, as knowledge becomes more relevant and up to date, both for your new GenAI buddy and for the employees in the business itself. (And if content governance is new to you, that’s something that consultancies like Grand Studio can help with.)

Testing, testing, testing
GenAI is a new – and therefore unpredictable – technology. People have a lot of mixed feelings about GenAI; some people are excited about what they see as a tool of the future, while others are skeptical or even afraid of what GenAI will mean for their job security and place in the workforce. Building multiple moments of user-centered research and testing into your project plan can help you build empathy with your target audience, with an added benefit of not only spotting technical bugs and glitches, but also helping people start to build trust and understanding of what this technology is capable of. Thorough research with the right users can also help your internal comms or external product marketing teams create a finely-tuned product launch messaging and rollout plan. (As it happens, Grand Studio is so committed to user-centering all products and services that we’ve created a public-facing framework to help put this into action).

Embrace the whimsy
Finally, as you’re gearing up to get started on your exciting new GenAI-enabled product, it’s important to set some grounded expectations and cut through the marketing hype. GenAI, and LLMs in particular, are not silver bullets. They are emerging technologies that are still being experimented on, developed, and tested out every day. There are limited functionalities as to what these LLMs are capable of; they’re not truly “intelligent” and they can’t read your – or your users’ – minds. And there’s still a learning curve to understanding how to get the best out of these technologies.

Bias and hallucinations are real risks that could open you and your company up to potential liability depending on your target audience and industry. Company security is an additional concern given that data once fed into an LLM – even a company’s proprietary LLM or Wrapper – is impossible to remove once it’s in there so there will need to be additional protections in place. Having these hard conversations about why your solution should include a GenAI-enabled product and what the expectations of this technology are before you get started will save everyone a lot of time and pain later on as these limitations make themselves known.

Overall, GenAI is an exciting thing that has a whole world of potential and possibilities attached to it. We believe that being honest about the technology’s limitations and setting yourself up for success as best as possible will give you the greatest chance to make the best use of this emerging technology and its capabilities.

Stay tuned for the next part of this series: The Ideal GenAI Design Process

Diana Deibel July 23, 2024

4 Things You Won’t BELIEVE Design Can Learn From Buzzfeed

July: a time for pools, slushies, bike-riding and hanging out with friends. What better way to celebrate mid-summer than to look for inspiration in one of the quintessential lighthearted media outlets?

Without further ado, here’s what design – at all levels – can learn from the Buzzfeed approach.

Bite-sized content works. People read listicles and short articles because they are brief snippets they can parse quickly and move on. Often in design, we try to pack too much in, and it gets lost in the process. Bullet points of quick takeaways, illustrative impact quotes or screens, and executive summaries work really well – with an offer to dive deeper for those who genuinely want more.

Nothing engages like gossip. Put another, more design-y way, stories anchor everything. We all want that tea spilled and frankly, when details are grounded in a narrative that starts with a bang and sets the stage, tension that builds, and an ending that wraps up that portion of the story (even if the overarching narrative will continue on), we’re listening the whole way through. Along those lines…

Juicy headlines draw people in. Is it clickbait or is it cutting through the noise to grab your audience’s attention? (Both?) We can do the same in design when communicating important research insights with leadership or naming design options with stakeholders managing busy schedules. Marketing exists for a reason and oftentimes Design doesn’t do a good job of utilizing it for ourselves. Juicy headlines or naming conventions can help our business stakeholders understand what problem is being solved, or what they or their users will get out of a particular solution from the get-go and bring them along in a productive, collaborative way.

Embrace the whimsy. Buzzfeed always has a silly quiz on things like “what your favorite sandwich says about your future” – and people love those. Sometimes design takes on the personality of business and the thing is, we really can’t take ourselves too seriously for two reasons:
1. We need to take the work seriously but take ourselves lightly in order to really enable creativity to flow. Putting on formal structured thinking and expression can feel quite confining to many designers. Which leads to…
2. We’re the “creatives.” (Yes, everyone is creative but we’re the people who are expected to bring the outside-the-box thinking and artifacts). We’re not only allowed but expected to bring some amount of rule-breaking and whimsy to the table.

Put another way, if not us then who? ESPECIALLY within your own teams. So have fun. Do a little something silly. Have a team-building activity that’s a little weird (we’ve done Secret Santa lunches sent to each other’s houses and at-home Nailed It challenges). Change your Teams photo to a raccoon meme. Use gifs in communication.

When you embrace the silly you make space for other people to relax, bring themselves and create a more creative and innovative space for work to take place. A place where they can take risks – at first with just themselves but then with the products and ways of working. And smart risk is how you get to great.

Want help figuring out how to set up and maintain a high-functioning and impactful design team? Drop us a line!

Anna Lathrop June 25, 2024

Scaling Research by Activating the Frontline

Innovation is the name of the game in UX Research; we are often being asked to find creative ways of gathering insights from end users with smaller teams and even smaller timelines and budgets for recruitment. As we continue to seek out ways of reaching people, there’s an often untapped source of research insights who are working with our target users day in and day out: frontline employees. This is a key strategy, particularly when dealing with any protected or vulnerable population, such as patients or children, who are often very difficult to access for a variety of (very good!) reasons.

Frontline employees are the boots-on-the-ground people who are interfacing with users every day. Depending on the industry and problem space they might be receptionists, call center employees, nurses, cashiers, etc. They spend their time putting out fires and hearing directly from customers about what’s working and what isn’t.

So, where do I start?

First things first, activating any group to be part of research often starts with building relationships. Frontline employees are busy people who are usually being managed by busy people who are often concerned about preserving their teams’ bandwidth and protecting their time. To reach them you’ll need allies, and allies start with relationships. Start by getting to know their managers and team leaders (or whatever the equivalent role is). SME (Subject Matter Expert) interviews can be a great method here, both to learn more about pain points and also to help people understand that you’re there to help them and their teams with their jobs. Research is a way of letting people be heard, and that’s a valuable thing you can do for them.

Once you’ve built a relationship with the managers and team leads, you can start asking about getting access to their teams who are interfacing directly with your target audience.

I’ve built relationships…now what?

Now that you’ve gotten access to the frontline employees, there are a couple different research methods we suggest considering. This is your chance to get the inside scoop about what kinds of pain points exist for users and employees, what kinds of tools they use, what kinds of ideas or suggestions they have for improvement, and more. Keep in mind that while research can be hugely impactful, if you’re not careful it can also be very time-consuming and extractive – meaning it takes knowledge, expertise, energy, etc from people without giving anything of value back. So consider how much bandwidth, time, and energy people have when planning your research, as well as what you may be able to give back to them.

Two non-extractive options we’ve leveraged in the past are:

Diary studies

Diary studies are an unmoderated research method that asks someone to keep a log about their experience at certain times or in response to certain triggers such as after speaking to a customer or using a piece of software. You can ask people to take photos of key moments, record their emotions or activities during or after certain events, or provide reflections on changes they might have made or ideas they have. Diary studies are a great way to turn your frontline employees into researchers themselves by having them think about and interrogate their own workflows, softwares, and scripts when interacting with end users.

Diary studies can be very impactful because they are straight from the participant’s unfiltered perspective and are designed to happen in the moment, so they are less likely to be misremembered. Some drawbacks include people forgetting to fill them out at the right times – or at all, especially if they are busy – or providing unclear information that is difficult to follow up on and get additional clarity.

Passive prompt wall

This is a good method to use if your participants all share a physical space – such as an office or breakroom. Setting up an installation such as oversized post-it papers with markers and prompts that participants can fill out on their off time can provide you with first-hand insights about how people are feeling, what they’re hearing from users, and what ideas they might have for how to improve the products or services they deal with day-to-day.

Some watchouts to this method is that you need to be mindful of how you word your prompts so they are easy to understand and you’re surfacing relevant information. There’s always a risk of people responding with unserious, off-topic responses with unmoderated forum-type research, so have a plan in place to vet some of the more suspicious answers you receive (possibly from those SMEs you interviewed earlier).

I’ve gathered my research, what do I do now?

Congratulations on gathering research from frontline employees! Now it’s up to you to synthesize your insights and pull out the necessary takeaways. Consider conducting 1:1 interviews or focus groups to follow up on interesting themes and patterns. If you are developing concepts or prototypes out of your insights, frontline employees can be a great group of people to start gathering some validation on your ideas.

Research is an ever-evolving practice, and finding new ways to learn about what works and what doesn’t can sometimes feel like a moving target. But if you build relationships early and expand your participants to include not just those experiencing the pain points first hand, but to include the people who are experiencing them second-hand as well, you can capture more data in richer and more informed detail than ever before.

Interested in how you can activate your frontline employees? Drop us a line!

Andrew Gold April 18, 2024

Stretching Lean Budgets Strategically

Every business hits times when the budget gets tighter — it’s an inevitable part of being in it for the long haul. For a lot of industries, their short-term futures are a bit unpredictable right now, leading to questions about how to best set up their business to weather any twists and turns.

In the face of uncertainty, many organizations scale back as quickly as possible to alleviate the pressure on their overhead. While understandable, rushed decisions can sometimes be short-sighted decisions, making it harder for those businesses to rebuild once lean times have passed.

Just as strategy is important in times of growth, it’s also key in times of reduction. Whether you’re the one facilitating trims or absorbing them as best you can, read on for our take on putting strategy into leaner times.

Center existing customers

While you can’t completely lose sight of expansion, the math is simple — it’s much less expensive to retain an existing customer than it is to acquire a new one. In moments when efficiency with available budgets is essential, the best move is often to invest the majority of your efforts in customer retention through the products, services, and/or tech systems your teams may already be running. This means maintenance, yes, but it also means uncovering new ways to provide benefits for them, ensuring they will return to you. Growth is important, and should not be forgotten, but it’s important to balance such endeavors with true investment in preserving what’s working for you today.

Step back and learn, and go “lightweight”

We’ve seen huge payoffs for organizations that take budget setbacks as opportunities to zoom out on their business and take a closer look at their products and services. What makes the most sense to focus on in this new climate? Where is infrastructure/development urgently needed, and where can it wait? Which projects are going to best prepare the company for when the market forges ahead? In all likelihood, a change affecting your business also means changes for the partners and clients around you. How might these circumstances affect your short- and long-term success strategies?

In lean times, it’s also very important to get to the learnings quickly so you can pivot if needed. Consider stepping back to ask what the scrappier, more agile version of your process might look like. You want to be investing efforts in the right places, so getting that feedback loop on a quicker cycle is key.

Consider how projects are shelved

When an organization tightens the belt, it’s almost certain that internal priorities will need to shift. This often involves shelving longer-term projects, and refocusing resources to work on lower-hanging fruit that will generate income in the short term.

Once the worst of the budget drought has passed, though, most organizations will want to pick up where they left off on those shelved projects. The problem is that many times, the employees with the institutional knowledge to restart those projects have been shuffled around in a reorg, laid off, or have left the company out of fear for the business’s future. Countless times, we’ve seen work either need to get redone because there was not enough context to pick it back up again — or, get restarted from scratch only to realize midway through that much of what they’ve worked on had already been done.

While it may not be realistic to avoid any kind of turnover or layoffs, consider using the lower-budget times to thoroughly document any mid-flight work that needs temporary shelving. This includes the work done to date, by whom, what was learned and the impact moving forward, and what still needs to be learned or done. Taking the time to do this in “quieter” times is hugely important to not wasting effort when your business is finally in recovery and expansion mode.

Judicious use of outside help

It’s hard to justify spending any money when your budget is limited. That said, given the overall fear of making the wrong decision that can pervade stressful times, it can be helpful to call on outside eyes for perspective and strategic support. Things like day-long prioritization workshops, short research sprints, or new tech trainings can be sensible ways to spend less money but still get a lot of impact and keep initiatives moving forward.

Another smart way to use outside support in tighter times is as short-term personnel augmentation. When you can’t commit to retaining FTEs for each role you need, hiring an agency can be a smart way to access a wide array of skill sets for less money.

Plan like the storm will pass — with the right strategy, you can help make sure it does. And if you’re looking for a partner in weathering that storm, we’d love to hear from you.

Anna Lathrop March 20, 2024

Leveraging AI in User Research

Grand Studio has a long history of working with various AI technologies and tools (including a chatbot for the underbanked and using AI to help scale the quick-service restaurant industry). We’ve created our own Human-Centered AI Framework to guide our work and our clients to design a future that is AI-powered and human-led and that builds on human knowledge and skills to make organizations run better and unlock greater capabilities for people. When ChatGPT hit the scene, we started experimenting right away with how it could improve our processes and make our work both more efficient and more robust.

Given our experience with what AI is good at doing (and what it’s not), we knew we could use ChatGPT to help us distill and synthesize a large amount of qualitative data in a recent large-scale discovery and ideation project for a global client.

Here are some takeaways for teams hoping to do something similar:

1. Don’t skip the clean-up. As they say: garbage in, garbage out. Generative AI (GenAI) tools can only make sense of what you give them – they can’t necessarily decipher acronyms, shorthand, typos, or other research input errors. Spend the time to clean up your data and your algorithmic synthesis buddy will thank you. This can also include standardized formats, so if you think you may want to go this route, consider how you can standardize note-taking in your upfront research prep.

2. Protect your – and your client’s – data. While ChatGPT doesn’t currently claim any ownership or copyright over the information you put in, it will train on your data unless you make a specific privacy request . If you’re working with sensitive or private company data, do your due diligence and make sure you’ve cleaned up important or easily identifiable data first. Data safety should always be your top priority.

3. Be specific with what you need to know. ChatGPT can only do so much. If you don’t know what your research goals are, ChatGPT isn’t going to be a silver bullet that uncovers the secrets of your data for you. In our experience, it works best with specific prompts that give it clear guidelines and output parameters. For example, you can ask something like:

“Please synthesize the following data and create three takeaways that surface what users thought of these ideas in plain language. Use only the data set provided to create your answers. Highlight the most important things users thought regarding what they liked and didn’t like, and why. Please return your response as a bulleted list, with one bullet for each key takeaway, with sub-bullets underneath those for what they liked and didn’t like, and why.”

Doing the upfront human-researcher work of creating high quality research plans will help you focus on the important questions at this stage.

4. It’s true, ChatGPT gets tired. As with any new technology, ChatGPT is always changing. That being said, the 4.0 version of ChatGP that we worked with demonstrated diminishing returns the longer we used it. Even though the prompts were exactly the same from question to question, with the input of fresh data sources each time, ChatGPT’s answers got shorter and less complete. Prompts asking for three synthesized takeaways would be answered with one or two, with fewer and fewer connections to the data sets. By the end, its answers were straight up wrong. Leading us to our final takeaway:

5. Always do an audit of the answers! Large language models like ChatGPT aren’t able to discern if the answers they provide are accurate or what you were hoping to receive. It’s also incredibly confident when providing its answers, even if they’re wrong. This means you can’t blindly rely on it to give you an accurate answer. You have to go back and sift through the original data and make sure that the answers it gives you line up with what you, the researcher, also see. Unfortunately this means the process will take longer than you were probably hoping for, but the alternative is incomplete, or incorrect answers – which defeat the purpose of synthesis in the first place and could cause the client to lose trust in you.

Outcome: Did using ChatGPT speed up our synthesis significantly? Absolutely. Could we fully rely on ChatGPT’s synthesis output without any sort of audit or gut check? Not at all. We’ll keep experimenting with ways to incorporate emerging technologies like Generative AI into our workstreams, but always with research integrity and humans at our center.

Interested in how GenAI might work for your organization? Drop us a line – we’d love to chat!

Grand Studio February 21, 2024

A New Way of Understanding Sports Fans

A lot of sports organizations think about their fan base in terms of subscription tiers. Their business strategy is largely about moving fans up those tiers, converting them to higher levels of monetization. Accordingly, they ask themselves questions like: what would it take for a fan to upgrade to a season ticket holder, an ESPN+ subscriber, or a daily reader of sports news?

This approach makes sense. After all, a company is in the business of monetization. But to get a fan to upgrade, they must first and foremost be engaged with whatever it is you’re offering — be that a product, a team, or the game itself. To bring them up the tiers is essentially to ask them to increase their level of engagement with you. And if you want fans to engage deeply, you have to deeply understand what it is that they want.

In other words, the better you can understand the crux of a fan’s engagement — how it is shaped, how it’s maintained, and how it grows (or stagnates…) — the better you can cultivate their inspiration to upgrade. Getting to this level of a fan identity requires an intimacy with their beliefs that goes beyond the details on an account subscription.

A fan-centric view of sports

As mentioned, while there is clear value in analyzing subscription trends, it is inherently top-down and corporation-centric, placing fan behaviors primarily in relation to their monetary value for the company. If this is the key variable by which segments are sliced and diced, it can limit the organization’s ability to surface the most meaningful characteristics and variations that define their fan base. And, subsequently, limit the organization’s ability to serve such needs, and get the very upgrades they are after.

What many sports companies could use is a complementary bottom-up approach to segmenting and analyzing fans. This approach would start by understanding how and why a fan engages in a sport. Is it all about supporting a particular team? Is it a larger appreciation for the sport? Is it about the culture? Belonging? Nostalgia? Hometown pride? Is it about going to games because all their friends do? Starting on the ground to understand attitudinal and behavioral differences across fans can set organizations up to learn something deeper and more important about that fan than their subscribership status — things that ultimately do more to determine how they can serve each segment.

Stories from the stadium

In a previous project, a major sports league asked us to overhaul their mobile app. Their goal was to get fans to spend more time on the app so they could generate more ad revenue. When we started doing research on their fan base, we uncovered surprising trends that ended up influencing the league’s overall engagement strategies. For example, there was a significant portion of the fan base who were what we called “adopted fans.” Instead of inheriting a team from traditional family ties, they adopted a new team when they moved to a new state, or adopted one based on its underdog status. As newer fans, they looked to national news for sports intel. Diehard fans, on the other hand, primarily went straight to their local beat reporters for sports news. This stratification uncovered opportunities for the league to serve each group differently and personalize their experience on the app, increasing the engagement opportunity for each group.

In another project with a major sports team, the avidity level of a fan turned out to be among the most important characteristics to analyze. We uncovered, for instance, a segment of the population we called “tag-alongs” — those who attended a sporting event because someone had invited them. Many of these tag-alongs didn’t know much about the sport to begin with, but loved the experience of going to a live game and rooting for the team. For this sub-group, the atmosphere and amenities at the stadium made a big impact on their likelihood to return. Once this group was uncovered, the team was able to do more to convert these tag-alongs into fans in their own right.

Doing the “field” work: meeting fans where they are

Let’s assume your organization has bought into the value of uncovering the unique fan archetypes within their population. What comes next?

One important way to research fan attitudes is, of course, going to games. Observing fans interacting with their sport or team, and also observing them in community with one another at games, is not to be overlooked.

But fans are not only fans during sports games. They are also fans when they are reading the news, keeping up with players or stats or the league at large. They are fans when they’re out at a bar with friends and see their favorite player’s jersey on the wall. They are fans during off-season as well, even when there aren’t as many ways to show it.

Understanding a fan means understanding the rhythm of their fandom, the ebbs and flows in addition to the moments of peak excitement and engagement. How they stay connected to their team or sport when games aren’t going on can be just as informative as how they behave during a game. There are cadences to the experiences of different sports fans, and understanding that richness of detail is key to understanding how their needs can best be met. We’ve found that understanding these harder-to-capture aspects of fandom require different research methodologies — for instance, perhaps you need diary studies to check in on fans during off-season or lulls in action. Perhaps you need to post up in a sports bar and catch people stretching out the emotion of a game by connecting over it. Perhaps you need data points from people as they read sports news throughout the week.

Sports mean a lot to people. For some, their fandom is a key piece of how they see their own identities. Taking the time to understand these segments with multidimensional attributes with care can pay off greatly for fan satisfaction as well as overall engagement metrics.

Looking to better understand and serve your fans? We’d love to hear from you!