Laura Richardson

Laura Richardson is currently the Founder of Blue Fortune Group. At the time of this interview, she was VP CX at Publicis Sapient where she focused on North America, namely retail and CPG. 

Tell us a little more about yourself and your role.

There's nothing more exciting than understanding people and how to design for people. That's what I love to do for a living – strategy for clients. So I'm always future-casting. We're talking two to five years out and it's always “What is the future state and how do we bring consumers along with us?”


When you think about customer experience and any insights or research you might do to inform today, tomorrow, and future decisions, we’ve typically heard that there are a couple of different buckets of research:

• Big projects: the big thing we're working on. 

• Ad hoc requests or questions we're reacting to: CEO has an idea; we might have a hunch. 

• Recurring bucket: we want to stay smart on something. (I imagine that might align with where you spend your time.) 

Curious if those three resonate as you're looking towards the future? 

I’m essentially a strategist. Insights are everything. I call it “lenses for looking.” And the lenses I look through depend on the client as I'm not internal. Let's take an airline client I've had. They are obviously getting a lot from the C-suite. “We have an idea for an innovation. Where are we in that innovation pipeline? Do we go do this innovation? How do we go do this?” 

Our work with them was very much: “What is the future of plane turning? How do we innovate turning the plane?” which is when it comes in, unloads, reloads, disembarks, because there's a lot of money to be had in the plane turn. 

So it's kind of both [types of buckets].

What’s interesting though, as someone who's interested in lenses for looking: what has helped me thus far before AI has been that, as a consultant, I've done almost every industry. I was just talking to a CPG for a snackable product. I was able to pull from intraoral dental device work that I had done previously, as well as from a client that does tobacco. And both of those had something to offer me from an insight perspective that I could immediately share and say, you want to think about it maybe from this perspective. 

So I'm constantly taking in all the lenses. I call it “colored glass” – kaleidoscope thinking. I'm constantly thinking about what I have, but also that future state. Trends change, things change. So I am very interested in what the state of the state is. 

I think about partnering, because one person, one company, honestly can't do it all anymore. Things are just so complex. Everything has been deconstructed. And because of that, we're now having to get more and more partners to help us accelerate faster and innovate faster. The world doesn't wait, right? 


I definitely resonate with the intersectionality of ideas – the synapses where you've got a lot of different industries, topics, and there’s the time trajectory as well. 

Thinking about different sources of insights you’ve mentioned (going to conferences, your team, different projects, and thinking about primary versus secondary types of insights), how do you think about if and how those interface?

In terms of primary versus secondary, here is my biggest concern about AI. 

Qualitatively, I'm a designer, so I research to design the future. And thus far, I'm not saying it's the only way of doing it, but really great future casting has come from conversations like this, where I hear you. 

I will do a love letter to a brand, like a love letter to The New York Times. I will have someone create that and then read it back to me. And then I can probe on when they say they love The New York Times. “What does it mean to them and why?” It's in the story. Now, that's not quantitative. That gives me an emotional gestalt, but it's not the quantitative piece. 

And then there's another piece here that to some degree has been missing, I think, until more recently. We're seeing this develop over time, which is: you need quick answers. You need them now. And you need it to convince the C-suite, to convince the board of change. It has to be numerically sound – a thousand, ten thousand, international – and we need it now. 

Some of it is signals. Signaling is great, but then there's also what is the size of the prize? How are you quantitatively validating this? 

Over 20-25 years, I've honed a lot of skills to see that future state, but it's not enough anymore. 

We have to have the underpinning of the quant to go with that qual. The one thing about AI – and I did hear it echoed today [at IIEX] – is that in general, it cannot be all AI because there are still very much things still being missed. It is too early of a technology, at least right now. I'm not saying 10 years from now, five years from now, we may be there, but there is something profound that happens in my opinion that, just like right now, there's something that happens here – being physically together – that you can't lose. 

We can't off-lift everything to an AI because we will have lost something in that translation. It is not there yet. It might be at some point. I reserve the right to say that. 


If you had to sum it up as one word, what would you use to describe the future of research and AI together?

There was a German philosopher that once said, any technology mediates human experience. We are in that moment of time. The phone, the iPad, there are obviously many types of technologies, but this? I have been in the forefront of technology for years. This is massive. And I think there'd be people, we're all trying to figure out where we land and where's the wealth there. Where's the money at? What's next? How do I create that next? 

If we look at the positive and we look at the glass half full, then it's not really one word. It could be an unbelievable partnership. That's not one word. I think partnership is the right word. 

But there are clearly things I miss that I can't see. That's okay. It has been until now. But I'm hoping! And I'm going to try to interview every vendor [here at IIEX] because I need to understand what the offering is so I can figure out which are the tools to use. 

Many of them professed to inspire curiosity, but I get into the UI and I'm like, what should I be curious about? Because I'm not feeling it right now. I'm not seeing it. And I understand that this is new, you guys are still a startup. There's a lot here. You're not even telling me, giving me a hint as to where I should even start. Help me! Where should I be curious? I still want to do some of that because I have to fuel my own curiosity. 

My hope would be partnership. My biggest concern is limitation. Because if we rely on it too much, we will also miss something in that experience. 


There's Google, there are LLMs, there's this breadth of information out there, but you can still feel like you're missing something. There's no way for a human to get all the things that are relevant to a given topic from what's out there. So imagine you're going to wave a wand and make any of these types of research that you might use for public resources or public information better or faster. 

Is there one type of research (market, competitor, etc. that you lean on desk research for) that you wish you could just make better, make it quick and easy to find the type of research you need?

Right now, size of the prize analysis. 

My goal was to create what they call category kings. I look for the whole in the hole. Where are the opportunities? How do we competitively differentiate? 

But it's not enough today to say, “this is going to move the market. This, from a consumer perspective, has incredible emotional resonance. This is a future state that, yes, it's going to take you 35 years to develop, but I know this is the future state for you. You will be a category king by doing this.”

It's not enough anymore. You have to marry that, whether it's a qualquant argument or it's a literal, more designed, fuzzy front-end emotional state partnered with the size of the prize analysis. That is what we are still using deep data sets for. It's still prediction. How do you predict a future state? And we have to be better at that. That actual data is, from what I've seen, not great right now. Now, I will say... I'm also very excited about what I'm hoping for, but I haven't seen it yet. 

Sentiment analysis is not the right word. That's a little too surface level. I design from emotion. 

Long ago, there was a gentleman who had a degree in computer science and art. He did a project called We Feel Fine. That was probably the first of its kind doing large scale sentiment analysis. You would look across the internet and feel, generally speaking, across the world, “what is the general feeling?” It was just kind of binary, more positive or less positive. We have that capability today so much stronger, but it is not granular enough. You cannot use NPS or CSAT as a score and do anything with that. There are emotions that compose that number. There's a lot more to be done on the emotional side of the house. 


Any final thoughts, words or emotions around the future? 

You mentioned AI and research, but when you think about all of these different sources of insight, with so much to wrap your head around, and you're tapping all these different vendors, where is it headed and where is the opportunity?

I am telling every client right now to create their own corpus, and not only legally – there is incredible competitive differentiation to be had. Everything will become proprietary. So at some point, any brand – Disney, Walmart, Best Buy – will have their own corpus created. 

And then to your point, there are, and I hate to even use the word vendors, but there are companies that are providing insight analysis. You will also have your own proprietary offering. And the question then becomes who has the best proprietary offering? 

And that is why when I'm doing my evaluation, it is how much of this is old data? How much of this is new data? How nuanced? How detailed? How does it help me create... “story is the wrong word. What I strongly believe in and ultimately what I sell is it's not enough to give someone a PowerPoint slide anymore and tell them that's the future state and show them “There's a bunch of headwinds. And here's the graphs and charts. And we're concerned.” It is literally an immersive, not metaverse, but an immersive experience where I could be any brand. 

Again, let's just say Disney. The future of Disney. What is it five years out? If I look at the future of Shop Disney, what if I was like, “Okay, the future of Shop Disney is the launching point for any experience at Disney because everything can be bought. What does that look like? What does it feel like? What does it smell like?” 

I have to put my clients in a position to not only see that, but then unify and rally the organization around it. 

When I think about the power in the future and what I feel is missing is it cannot be served cold. Does that make sense? The concern with AI is that it's served cold. We can't lose the context, the feeling. We'll see what it looks like, but when you're like, this person has cancer, and they were not seen by a doctor in time to fix that. That's a data point, yes, and there's a lot to go on in that, but there's so much to be mined from that. 

I look forward, truly, to seeing how Wonder thinks about it differently. Granted, we're still limited by technology. There are only so many things we can express and how we express them. 

But I have had more than one vendor say, “we activate curiosity, we augment curiosity.” Help me see a world and understand and navigate that world, and also help me identify what I should be curious about that I can go explore. You might have different lenses for me to look through by all means. But be that partner. Don't overtake it. Because I don't want to offload everything. This is great that you've done all the work. But when I go into the meeting and I'm like, “the AI literally generated the tagline, and the executive summary, and the this, and the that?” 

First, what am I supposed to be curious about? Because you've just done it all.

And then secondly, how am I the hero? And I think if there's something to take away from all of this, it is how can you make the user of your system the hero of the experience? If I think about any company supporting me, I still need to be the hero to my organization. They're going to help me be that hero faster, stronger, better. But what are the tools that you're going to give me where I still seem like the smartest person in the room? It's not the AI. It's me. If we have a question, I'll go query it again. But anyway, that's how I'm feeling. 


And that's a wrap. Thank you!