Why People Buy with Rowena Humby on The Six Sells Podcast

How can brands understand why people buy, not simply what they buy? Rowena Humby, CEO and Co-founder of Starcount and Trustee of The Female Lead, joins Fern Potter on The Six Sells Podcast to discuss behavioural data, open banking, customer motivations, AI, female consumers and the importance of keeping human context at the centre of increasingly automated marketing.

Episode summary

In this episode of The Six Sells Podcast, Fern Potter speaks with Rowena Humby, CEO and Co-founder of Starcount and Trustee of The Female Lead, about how behavioural data can help brands understand the motivations behind consumer decisions.

Rowena explains how her background in astrophysics taught her to identify patterns in data and infer the meaning behind things that cannot be directly observed. That same principle now sits behind Starcount’s approach to understanding the “why behind the buy”.

Starcount combines behavioural signals from search, open banking and telco data to help brands and agencies understand what audiences care about, where they spend, how they move and when they may be open to changing behaviour. Rowena explains how this can help businesses identify high-value audiences, understand competitors, grow share of wallet and activate audience segments across channels including connected TV, out of home and digital.

The conversation also explores the growing role of AI in advertising and business. Rowena argues that as machines become more capable of making logical and rational decisions, human context and emotional understanding become even more important. She and Fern discuss AI bias, the risk of machines reproducing historic inequalities and the importance of keeping people involved in decisions.

Rowena also discusses her work with The Female Lead, its mission to raise the visibility of women, the Disrupt Your Feed campaign and why businesses need to understand women not only as employees and founders, but as a major economic and consumer force.

Topics discussed include:

• Rowena Humby’s journey from studying astrophysics to working with behavioural data
• Learning data analysis through astronomy and the study of dark matter
• Growing up around entrepreneurs Edwina Dunn and Clive Humby
• The legacy of dunnhumby and Tesco Clubcard
• Using data to infer human motivations and behaviour
• Building and closing a business during the pandemic
• Co-founding Starcount
• What Starcount means by uncovering the “why behind the buy”
• The difference between knowing what customers do and understanding why they do it
• Combining search, open banking and telco data
• How brands can understand customer intent, interests, spend and movement
• Using microgeographies to connect behavioural data sets
• Activating behavioural audiences across connected TV, out of home and digital
• Using behavioural data for customer acquisition and sales conversion
• Why emotionally driven categories such as gaming, sport, music and fashion are well suited to motivation-based targeting
• How behavioural data can also help more functional categories such as supermarkets, broadband and telecoms
• Starcount’s Battlegrounds product
• Identifying areas of brand strength, competitor strength and switching opportunity
• Increasing share of wallet by reaching people at moments when they may be open to changing provider
• Measuring campaign outcomes using search and spending behaviour
• Building feedback loops between planning, activation and measurement
• Why the customer journey is not linear
• The role of human context as AI becomes more influential
• Where AI automation is useful and where human creativity still matters
• The danger of AI reinforcing existing bias
• Gender bias in recruitment data and AI models
• How AI could also lower barriers for female founders
• The work of The Female Lead
• The Disrupt Your Feed campaign
• Using audience data to understand what women care about
• Creating female-first products and marketing strategies
• First-party data enrichment for brands and media owners
• Understanding customers’ wider spending behaviour
• Identifying loyal, cross-category and lapsed customers
• Integrating audience insight directly into activation workflows
• Contextualising campaign performance against wider category performance
• Open banking as a behavioural data source
• The future of human context and emotional data in advertising
• Building more relevant brand-to-consumer relationships

Who is Rowena Humby?

Rowena Humby is the CEO and Co-founder of Starcount and a Trustee of The Female Lead.

Her career began with a degree in astrophysics at the University of Bristol, where observing galaxies and analysing astronomical data taught her how to identify patterns and infer meaning from information.

Rowena later worked alongside her parents, Edwina Dunn and Clive Humby, whose company dunnhumby became closely associated with Tesco Clubcard and the use of customer data in retail. Her subsequent work covered telco, banking, ticketing, social analytics and retail data before she co-founded Starcount.

Today, Starcount focuses on using behavioural data to understand not only what consumers do, but the motivations behind those behaviours.

What does Starcount mean by the ‘why behind the buy’?

The “why behind the buy” is Starcount’s approach to understanding the motivations behind consumer behaviour rather than looking only at the transaction itself.

Rowena Humby explains that conventional large-scale data often tells businesses what somebody has done, such as shopping with a supermarket, booking an airline or choosing a broadband provider. But that action alone does not explain why the person chose that particular brand.

The motivation might be convenience, digital experience, quality, heritage, price or another emotional or functional consideration. Starcount aims to infer those motivations from patterns in behavioural data and make the insight usable within advertising.

Rather than forcing people into a fixed taxonomy, Rowena describes an approach in which customer behaviour reveals how different groups cluster together and what appears to matter to them.

How does Starcount use search, open banking and telco data to understand audiences?

Starcount combines search, open banking and telco data to build a richer picture of consumer interests, spending and movement.

Search data provides signals about intent and interests by looking at the topics people search for and the context of pages they read. Open banking data provides insight into where people are actually spending money at merchant level. Telco data helps show where groups of people are at different times of day and how they move.

Starcount brings these behavioural sources together using microgeographies and demographic patterns such as age and income.

The resulting audiences can then be activated across channels. Rowena gives examples including connected TV through household-device matching, out of home using telco data to understand exposure to inventory, and digital activation through geographical or contextual approaches.

The aim is to connect audience understanding with practical media activation rather than leave it as research that cannot be used.

What is Starcount Battlegrounds?

Starcount Battlegrounds is designed to show brands where they are strong, where competitors are stronger and where consumers may be most likely to switch.

Using open banking data across different geographies, age groups and income bands, Battlegrounds can create a map of competitive behaviour within a category.

A broadband provider, for example, could use the data to understand areas where it has a strong market position, areas where another provider is winning and groups where there may be an opportunity to gain customers.

Rowena says this allows businesses to divide their media strategy more tactically and focus on consumers who may be more receptive to switching.

The broader goal is to increase share of wallet by reaching people at moments when their behaviour suggests they may be open to making a change, with messaging designed around that situation.

How can behavioural data improve media planning and campaign measurement?

Behavioural data can improve media planning by helping brands decide which audiences to prioritise before a campaign and then showing how behaviour changes afterwards.

Rowena says many briefs begin with an audience that has already been chosen. Starcount is increasingly trying to help businesses answer the earlier strategic question: who should the brand be going after in the first place?

That involves understanding the whole category, competitor spending behaviour, likely switchers and which audiences may be particularly valuable.

After activation, search and spending data can then help indicate whether exposed geographies show increased interest in or spending with the advertiser.

Rowena also argues that measurement needs wider market context. A campaign can look disappointing when judged only against an advertiser’s internal figures, but if the entire category is declining and the advertiser is declining significantly less than competitors, the campaign may look different when viewed in context.

Why does human context matter more as AI becomes more powerful?

Human context matters because AI can identify patterns and make rational decisions without necessarily understanding the emotional or personal circumstances surrounding them.

Rowena Humby says she would like Starcount to become a “human context layer” as more decisions across advertising and business are made by machines.

Her view is that there is still a consumer at the end of those decisions, and consumer journeys are not linear. People have different motivations and need states, and behavioural signals can mean different things depending on the person and the situation.

Rowena gives the example of automated product recommendations to illustrate the danger of interpreting behaviour without sufficient context.

She believes AI can be extremely useful for scale, automation and repetitive tasks, but human judgement, creativity and genuine interaction with colleagues and customers remain important.

How can AI reproduce bias?

AI can reproduce bias when models learn from historical data that already reflects inequality or skewed human decision-making.

Rowena discusses an example involving recruitment data, where a model analysing historic applications and successful placements learned patterns associated with traditionally male names rather than identifying a genuinely meaningful indicator of candidate quality.

Her point is that machines can repeat and amplify the patterns present in their training data unless people deliberately put the right controls and context around them.

Fern and Rowena also discuss the wider challenge of positivity bias in AI systems and the risk of tools simply reinforcing the perspective of the person using them rather than challenging their thinking.

At the same time, Rowena sees AI as an enabling technology. She believes lower-cost access to capabilities that once required significant funding could help more female founders build businesses without needing the same level of external investment.

What is The Female Lead?

The Female Lead is an organisation created to raise the visibility of women and better understand women as consumers, employees, leaders and founders.

Rowena Humby is a Trustee of The Female Lead, which was founded by her mother, Edwina Dunn.

It began with a book celebrating 60 women who had shaped the world. Brand sponsorship helped distribute copies to schools in the UK and US.

Conversations with girls in those schools then led to the Disrupt Your Feed campaign. The idea was to encourage people to follow six inspiring women in an area they cared about so that social media algorithms would begin serving more positive and relevant content.

Rowena says The Female Lead has since built a large social audience and uses the resulting data to understand what women care about, what unites them, what divides them and which subjects generate positive or negative reactions.

The organisation is also exploring how those insights can help brands create genuinely female-first products and strategies rather than starting with a general product and tailoring it afterwards.

How can first-party data enrichment help brands and media owners?

First-party data enrichment can help brands and media owners understand more about who their existing customers or audiences are, what interests them and where else they spend money.

Rowena explains that Starcount can match its behavioural data to first-party customer or publisher data.

For a media owner, that can make inventory more useful to non-endemic advertisers because the publisher can understand not only what somebody is reading or doing on its own platform, but wider spending patterns.

For a brand, enrichment can help answer questions such as: what share of wallet do we have, where else do our customers spend, do they also shop with competitors and what happened to customers who have lapsed?

Those insights can then be used to distinguish loyal customers, cross-category customers and lapsed customers and shape strategies for retention, acquisition or reactivation.

What future does Rowena Humby see for data and advertising?

Rowena Humby wants human context, emotional understanding and behavioural data to become an underlying layer across the advertising ecosystem.

She draws an analogy with the way dunnhumby helped Tesco turn customer data into both business insight and products that could benefit other organisations.

Her ambition is for behavioural data to become fuel for smarter decisions throughout planning, activation and measurement rather than operating in isolated silos.

Rowena believes advertising became more useful when brands could connect people with things they genuinely cared about, before excessive retargeting made that experience feel intrusive.

She sees an opportunity to move towards more meaningful brand-to-customer relationships in which advertising is relevant to an individual’s current context and need state, rather than simply broadcasting messages or following people around the internet.

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Six Sells is a UK-based executive visibility and thought leadership agency that works globally with CEOs and senior leaders in media, advertising, adtech and technology.

Founded in 2018, we turn each executive's expertise into distinctive, authoritative content in their own voice, built to reach two audiences at once: the humans that matter to them, and the AI models those humans now ask for answers.

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We also help executives and their companies improve their visibility in AI search and large language models (LLMs) through generative engine optimisation (GEO), increasing the likelihood that platforms including ChatGPT, Google Gemini, Perplexity and Claude can discover, understand, cite and recommend their expertise.

Read more here, or email hello@sixsells.co.uk for more information.

Full episode transcript:

Mike Nicholson: Hello and welcome to The Six Sells Podcast. My name is Mike Nicholson from Six Sells. Before we jump into today's episode, I just want to say a huge thank you to the team at Intelligent Assistants. Not only are they partners of Six Sells, but they're also sponsors of this podcast. So thanks again to the team over there.

Intelligent Assistants combine human intelligence with artificial intelligence to solve real business challenges. And they believe in a process of human first, human last, which really chimes in with the way that we think about things at Six Sells. So thanks once again to the team at Intelligent Assistants.

And let's jump into today's episode.

Fern Potter: Hi, I'm Fern Potter. I'm the host of The Six Sells Podcast today, and today I'm very excited because we've got the wonderful Rowena Humby, who is the CEO and Co-founder of Starcount, also Trustee of The Female Lead. So welcome.

Rowena Humby: Thank you.

Fern Potter: I'm so excited to have you here. I mean, we're going to be talking about so much, but I think I really want people to understand your journey, where you've come from, where your experience has been and what's got you to the role at Starcount today. So let's talk a little bit about you.

Rowena Humby: Yeah, of course. No pressure. Who am I?

Well, I guess maybe going back to academia and school, I always leant towards the science subjects. I don't know, for me, I loved the fact that there was a right and a wrong answer, so psychoanalyse into that what you will. But I found those more subjective subjects, like English literature, really overwhelming. Whereas with science, once you knew the answer, I was like, “Great, I can get it right.”

And then, yeah, I guess one thing that I totally fell in love with at school was space.

So I went on to do astrophysics at university at Bristol.

Fern Potter: Wow.

Rowena Humby: Yeah, it was amazing. The bit I really fell in love with was dark matter. So the fact that there's something out there that we conceptually don't understand scientifically yet, but we know it's there because we can see light bending or gravity pulling in ways that don't make sense from the observable universe. I could just talk to you about this.

Fern Potter: I do love a sci-fi film.

Rowena Humby: I absolutely loved it. I had a very cool degree where you kind of learn a lot about that sort of dark matter side. I must admit, at university, the mathematics in astrophysics is so advanced that it kind of became a bit more focused on formulas than it was the theory, which is the bit I really loved.

But I did get to do some practicals where I'd go and observe galaxies through telescopes. And that is where I learned the skills of data analysis. So collecting data, looking at different patterns, and then having to learn how you use code to run that trend analysis, those patterns, find the kind of things that come out.

So that's where I learned my sort of skills and technical skills. But when I left university, I had no idea what I wanted to do. And I really left with the intention of, well, I'll do what everyone does and go backpacking for a year and work out who I am and what I want to do.

Fern Potter: Absolutely. You know, that time for yourself after an intense subject.

Rowena Humby: Exactly.

Fern Potter: Where do we go next?

Rowena Humby: Yeah, exactly. But just before I went, I was actually at home. And I guess, for me, I grew up in a family of entrepreneurs. My mum and dad ran a business together.

That business is known in the media industry. It's dunnhumby. So my mum was Edwina Dunn, my dad Clive Humby. And they started the company two years before I was born.

They are famous for their work with Tesco Clubcard, and that sort of started in 1995. But really, my whole childhood was spent watching them build that business. It really was. And, well, I say it was. It is when I look back at it now. At the time, it was just normal, right?

Fern Potter: It's amazing.

Rowena Humby: So when I finished university, they had, a year before, sold dunnhumby to Tesco. They'd retired, they'd sailed around the Med for a year and realised they weren't quite ready to give work up.

So they came back and started a consultancy called Humby and Dunn, very original name, which essentially was about helping other businesses think about how they'd monetise their data.

So the first job I had, they basically said to me, I was eating probably my bowl of Coco Pops on the sofa or something, student style, and they said, “Look, Rowena, do you want to come work with us, learn the ways of the corporate world, earn some money before you go travelling?”

And really, I never left.

Fern Potter: I love that. What a wonderful experience to be able to have, to just have exposure not only to the entrepreneurial side and the kind of psychology of building a business, as well as the data and technology. And it obviously feels like something that you really enjoyed as part of your course and curriculum that you could bring into business.

Rowena Humby: Yeah, exactly. It really is. And I feel so lucky.

My mum was a CEO of this big business. She really inspired me on how to be a leader, a woman and a leader, and to use people skills to navigate difficult problems.

And then my dad was a creative with data and he taught me how to look at data differently and how to spot the things that other people wouldn't necessarily see.

And that was really the part I fell in love with.

The first job I did was that Dad was working on some Vodafone data. It was a project for the Southbank Centre and we were looking at why people come to the South Bank.

The data we had were just pings on cell towers from Vodafone data, and we were able to interpret who was there, who was commuting through versus who was visiting as a tourist versus who was a school afternoon. And this was all human motivation uncovered through cell tower pings. And I just was like, wow, this is so cool.

Fern Potter: It's just incredible, though, isn't it? That you can turn the quant into the qual and vice versa. The data is meaningless without understanding what's behind it.

Rowena Humby: Exactly. And it took me back to what I'd learned with the astronomy point, which is the inferring of dark matter through the patterns that you're seeing on what you know and observe.

And it was a similar kind of thing. It's like, well, this is the behaviour that sits behind it. So, yeah, I totally fell in love with it.

And then we had the privilege of working with, starting in telco, we worked with a bank and helped them monetise their data. We did ticketing, theatre ticketing and site analysis.

And then social media and all of that. And the social business was really all about using social analytics to understand trends and communities.

And I guess this is then when the more tumultuous part of my journey started, because that's when Cambridge Analytica happened. And it became incredibly difficult to be in the social trends world.

We then moved into, we're like, okay, well, let's move into enriching customer data with social data because that's sort of what people are doing in store and then what they're loving online.

And then, lo and behold, GDPR came in, rightfully so. But that made email matching incredibly challenging. So we moved into good old-fashioned footfall retail, site locations, et cetera, site analysis.

And then, of course, a pandemic happened. So it just felt like one thing after another, totally out of our control.

Fern Potter: But what an incredible experience to have to pivot the business model, but also, I guess, emotionally as well. Having to pivot the entire business as a team to what the next challenge could be.

As much as it must have been really tricky, you've got a lot of foresight to go, right, we're going here next. Let's go.

Rowena Humby: Yeah, it's true. And actually, now I feel like where my business today has got that more stability, I'm sort of being like, “Oh, when's the next pivot going to come?” Because it excites me now to solve those challenges.

Fern Potter: I love it. You might have this kind of business crisis that you can bring out.

Rowena Humby: Yeah, definitely.

Fern Potter: So then that brings you on to what you're doing today, though, which is kind of an evolution of your experience so far. And I feel like now, knowing what you studied at university and your passion there, bringing that into it, tell us a bit more about it.

Rowena Humby: Absolutely. So I guess that sort of took us all the way up to 2020, the pandemic.

So, yeah, through that time, I worked with Mum and Dad, for Mum and Dad, building that business. And actually, they had, in November 2019, stepped away and said, “Right, Rowena, you're ready to run this business now. We hand it over to you,” in partnership with Michael, who was our CTO.

And we made the very difficult decision during that first year of lockdown to close the business. It was the right thing to do by staff, shareholders, suppliers, et cetera. We were in a position where a huge amount of our business was reliant on that footfall retail piece and we didn't know how long it was going to last for.

So I was a little bit heartbroken, I'm not going to lie. I started thinking about what I wanted next from my career and where I was going to go.

And in all honesty, I was so passionate about what we had sort of tapped into that I wanted to continue that. So I turned to Michael and said, “Crazy idea, but do you want to start a business together? Co-found a new version of the company called Starcount and essentially bring all the skills that we've learned to date to market?”

So that's what we did. We co-founded Starcount in 2020, five years ago, six years ago now, started trading in 2021.

And everything at Starcount is about uncovering the why behind the buy.

What we noticed between the two of us and our careers working on data is so much of what people do with big data is look at what people are doing, but they don't look at why they do it.

And the why is traditionally understood from surveys and claimed data. Surveys are amazing to uncover what matters to people, their motivations, but ultimately you can't activate it. You can't push it into the big advertising ecosystem.

And so what we wanted to do is really uncover the why with large-scale behavioural data so it could be activated.

Ultimately, the theory behind it is where a bank might say, right, these are customers that shop at airlines or supermarkets or broadband providers. In all honesty, we all shop at supermarkets. We all have broadband. And most of us fly on an airline.

But you, Fern, might choose to fly British Airways and have British Gas and shop at M&S because you care about premium, quality, British heritage.

Whereas I might choose Octopus Energy and book my flight through Skyscanner because it's all about digital and convenience.

And so those motivations are really what show what consumers care about.

We're looking at behavioural data, not by forcing it into a fixed taxonomy, but letting customers show us how they cluster together and therefore what matters to them.

Fern Potter: That's incredible, by the way. I absolutely love that.

Funnily enough, I was having a conversation earlier about really trying to tap into the emotional state of what it is to be human. I think that's more imperative than ever considering AI and where the world's going.

So, for you to be able to take all of those signals, and I love “why behind the buy”.

Rowena Humby: Thank you. That's our new tagline, actually. We should have named it that from the start of the business.

Fern Potter: Being able to tap into that information, the emotive patterns, how are brands, or is it agencies, working with you to take advantage of this opportunity to really intersect with people where they're at?

Rowena Humby: Yeah, great question.

So we're combining three data sets really, three behavioural sources.

One is search data. So looking at what people are interested in, what their intent is, using the context of the web pages they're reading or the things that they're searching for to understand the fact they're interested in fashion, celebrity, environment, et cetera.

We're then combining that with banking spend data. That's open banking data. So the great thing about open banking data is you can go to merchant levels. That's then people spending at Temu, SHEIN, Primark, Tesco, Octopus, wherever it might be.

And then finally, telco data to look at where they are at different times of day, when they're at home, when they're out and about, where they're moving, how they move, et cetera.

We're bringing those three data sets together and combining them using microgeos. So, within a postcode, looking at the different age and income patterns.

And then how brands and agencies are using that is being able to say, right, who are my customers? Who are my competitors' customers?

So, I am this automotive brand. I want to understand what my customers look like versus my competitors. I want to understand the adoption of EV as a market trend.

And we're using that spend data to look at that and understand the different types of behaviours, create those segments, and then those segments can be activated in omnichannel by using the geo.

So that geo can tap into connected TV by matching to household devices. It can connect into out of home by using the telco data to understand inventory exposure. And then places like digital by either onboarding using geo to ID or using contextual across to ID.

And then that allows them to activate against those audiences.

And it's working. We're seeing we're reducing cost per acquisition by 20%, or increasing sales conversions by four times. So the results are really proof in the pudding, hopefully.

Fern Potter: Yeah, that's fascinating, isn't it? Because there's so many ways in which you can reach audiences.

I think, as you said, having those case studies and those proof points are imperative for brands and advertisers now to really understand where the value of the technology and their targeting and deterministic versus probabilistic and inferred versus not inferred, all those different strategies.

Do you find that there are specific brands and clients or verticals that are working better to get those results?

Rowena Humby: Yeah, such a great question.

It works very well for those obviously emotion-led brands. So if you think about gaming or sports or music or fashion, these are things that people really love and care about. Because your spend for that is passion and emotion-led, it works really well for identifying people that care about that. So, for that, it's very powerful.

Interestingly, more recently, we've been doing a huge amount of work with the more, I don't want to say non-emotion-led brands, but they are more functional brands. So supermarkets, broadband, telco, brands that the majority of us have in our everyday lives.

And the reason it's really working for them is because of that open banking data.

We've launched something called Battlegrounds, which is basically, within different geographies, age and income bands, who are winning from the open banking data? Which broadband providers are people choosing?

Being able to almost create a battleground map of the UK, which is: where am I strong? Where have I got market stronghold? Where are my competitors stronger? Where haven't I really converted yet? And then where are the most likely to switch audiences?

Being able to use that and divide their media strategy up into tactically going after those in different ways is really driving results for them and making sure that they can increase share of wallet by reaching those customers in the moments they're likely to switch with the message that's making them want to.

Fern Potter: That's fascinating, isn't it? Because then you've got such a holistic growth plan for that business.

I love the idea of being able to see in real open banking data the conquering element. Before, I think social media might be indicative of brand preference, but being able to actually see what was purchased can be fascinating and so insightful for the brands to understand.

Rowena Humby: Exactly. And where we'd love to take it next, and what I'm focused on at the moment, is looking at, right, once you've used Battlegrounds to work out where you need to go, then obviously when the advertisers are reaching those audiences, because we've got search and spend data, we can see the outcomes off the back of that campaign.

Geos, for example, that are being exposed, can we then see an uplift in people searching for or spending with that advertiser?

And then what I'd love to do is, how does that tap back into the supply side so you can optimise the campaign and make sure that you're constantly learning from the data and looking at how that initial pre-planning piece is feeding into something that can grow and iterate over time?

Fern Potter: I love that, the dynamism of being able to build that back.

We always used to talk a lot about the consumer journey not being a linear pattern of channel activation or even a linear emotive state.

There's a lot around the customer journey that's more this ebb and flow and ups and downs, and different data sets help in different ways to target that individual at the different needs at that point in time, when, “Oh, I'm open to switching. Go for it.”

What are those indicators? How have I collected them?

And doing that, to be able to feed back that loop and just be able to have a media and creative campaign that is as dynamic and fluid as the customer journey itself, would be incredibly important.

Rowena Humby: Absolutely. And I guess with AI, you can do that at scale.

Fern Potter: Yes, exactly.

Rowena Humby: And I think, I don't know how you feel about how AI is going to particularly affect our industry, but I think the human element, the emotional drivers, are super important.

Where I would love us to be is, I think our industry is going to go through some real changes and turns over the next five years, and I would love for Starcount to be known as that human context layer.

That emotional driver of the fact that whilst decisions made by machines are very logical and rational, there's still a consumer at the end of it.

To your point, the journey isn't linear. So being able to tap into those moments and understand what motivates them and how those different signals are reflecting that will be really key.

To give you a real-life example, it was a long time ago, but when Amazon launched their next-best-product recommendation, obviously that's kind of like a machine saying, right, what is the next best thing?

So, in America, when you bought a baseball bat, what do you think the next best item was?

Fern Potter: I'm going to say a baseball glove or ball.

Rowena Humby: Yeah, exactly. Glove and ball. And what do you think it was in the UK?

Fern Potter: Oh no, I don't want to know.

Rowena Humby: It was a balaclava.

Fern Potter: A balaclava?

Rowena Humby: So imagine if you are a woman who, no, we shouldn't laugh, but it goes to show the reality of if you let the machine do it and you don't think about the context.

Because imagine if a lady had recently moved on her own. She's buying a baseball bat for safety and security reasons because she feels unsafe in her new property. And then she goes on to Amazon and that's what she sees.

If you could see from her basket that previously she'd bought X, Y and Z, you would be able to know the context a bit more of who she is.

Obviously, AI will be sophisticated enough to take those nuances. But I guess it was just an example of how the human layer is still so important.

I don't know what you think about it.

Fern Potter: It's a good question. I mean, we built the business, myself, James and Sarah, off the back of a human first, human last philosophy.

So everything that we build at Intelligent Assistants is about empowering human thinking. It's about using AI as an acceleration for growth, but grounded in human intelligence.

There was a conference on in the US yesterday around, will AI cause a human existential crisis of humanity and where is it going? I'm like, surely we can just switch it off if it gets to that point. But maybe not. Maybe it's out of the box.

But I think it's imperative.

To your point, we're looking at how AI is impacting organisational change within a business. A lot of that is actually the individual's personal interaction with AI in their own home, on their own time.

So they've already got a psychological preference or an experience. Like you said, if you'd had that experience because the AI algorithm had served you something up like that, you're going to have a negative emotion that you're going to then take into the workplace.

Because we're not just talking about AI for business, it's AI for everybody.

And so that's one of the challenges we have when we're embedding AI tooling into organisations, overcoming some of the legacy experiences. Can I say legacy when it's been a few years?

Rowena Humby: I mean, I feel like we're moving so fast. It's legacy last month, really.

Fern Potter: Some of those legacy experiences where the right guardrails haven't been put in place have actually really created quite a fear and a barrier to adoption.

Rowena Humby: Yeah, I can see that.

I think it's interesting as well. It's both in the workplace and in the home, as a consumer, as an employee, how AI impacts you and what the future's going to look like.

I feel like we're maybe going to enter the era of experiential.

As a consumer, I love the idea of having a smart fridge that knows that my milk has run out and that my coffee's running low, and so it automatically sends a signal to my supermarket and it gets delivered in my next order.

Fern Potter: Dreamy.

Rowena Humby: Thank you. My morning coffee is a guarantee.

But I wouldn't want it to stop me spending on the things I love. Interiors, I love buying things for my home. I would hate to have that replaced by automation.

So the things that we love as consumers, I think, will remain.

And then as employees, to your point, I love using AI now as part of my daily work. I love using it to optimise how quickly I can get the more repetitive or production-led tasks done.

But my goodness, the creativity that comes from working with an actual colleague and being there in person with a client and listening to what they're going through, those are the moments that really push the business forward and make sure we're always growing, rather than the fact that we're optimising everything to the point that it's just a better P&L or whatever it may be.

Fern Potter: Yeah, that makes sense, doesn't it?

It's almost like you don't want to commoditise your own thinking or your own business IP and intelligence within that, because it's as much about the people within your organisation as the technology that exists as well.

I do find myself, I love having spent this time with you, it's brilliant, because I do find myself talking to AI a lot and I'm like, “Shit, is this good for my mental health? I don't know.”

Rowena Humby: And have you noticed that AI will tell you whatever you want to hear?

And if you let it know a tiny bit of your emotion, if you say, “I'm frustrated that this has happened,” or, “I'm excited about this,” it goes, “Well, you're right to be frustrated and you're right to be excited.”

Depending on how you prompt it and start it, it can.

So having conversations with it is dangerous. Whereas I'm more likely to challenge you and say, “Well, I disagree. I think that...”

And that's so important, to be challenged in that way.

Fern Potter: So true. That kind of human context.

It does. It has such, I can't remember whether it was Anthropic or OpenAI that did the positivity bias, like, “Yeah, great job.” It's like, “Oh no, this isn't what I wanted.”

But the positivity bias within it, and I think on top of that there's gender bias. There's all sorts of inherent bias.

These tools have not been built for the customer. They've been built for the next, I mean, you might appreciate my reference here, I feel like it's the next space race of frontier LLMs.

It's not about humanity, it's about who gets to do it politically.

And that's what I do love about businesses like ours and like yours and several businesses that we partner with across the UK that are going, right, how do I really help grow the economy and pick the right models and the right technology and work with business and consumers in the right way, kind of ethical and have those principles in place?

Rowena Humby: Definitely. No, I'm totally with you.

And a huge part of my role at The Female Lead and being a Trustee there is championing the importance of listening to women, both as consumers and as employees and as business founders. It's a huge passion of mine.

And to your point, I think AI is, well, there was a study done recently where they let AI basically train a model to suggest what the best candidate was.

They worked with a CV company and it ingested all the CVs and all the successful placements globally.

It was having a look at everyone who'd applied for jobs, everyone who'd got those jobs, all the CVs that were out there.

And then it said, right, now create a CV recommendation piece for the job.

And what do you think was the indicator of a successful recruitment? Is it a law degree at Harvard or a science degree at Cambridge?

No, it was if your name was like John or Steve.

Fern Potter: Oh, cool.

Rowena Humby: Yeah. So the machine had learned that that was the best indicator of a successful CV.

Fern Potter: Because it's just looking at patterns, isn't it?

Rowena Humby: Exactly.

Fern Potter: You have to have those guardrails to go, “Well, actually, let's normalise this index of the data.”

Rowena Humby: Exactly, which is a terrifying concept.

And it's just perpetuating the challenge that we've seen with the saying that there's more Johns on a FTSE...

Fern Potter: I was just thinking the same thought. Was it more Daves?

Rowena Humby: Yeah, Daves. That was it.

Fern Potter: In the FTSE.

Rowena Humby: Oh God, I should have researched it. We'll edit this.

Fern Potter: Fact-checking it.

Rowena Humby: It was more Daves than there were women, basically.

Fern Potter: That's right. And I remember the movement of us all changing our name to Dave on LinkedIn, I think, was the activism that came out.

But to your point, it's not new, inherent bias. And it's really sad that actually we're accelerating it through these platforms.

Rowena Humby: Yeah, that's right.

And because, you know, as women, we're less likely to invest, that means that the investment isn't going to female-led businesses.

I think it's less than 2% of funding in the UK goes to female-led businesses. But women are the majority customer. We make 80% of the purchasing decisions.

The world is changing as well. We're breadwinners, we're leading teams, we are choosing to be child-free, we are getting divorced more. There is such a shift in this.

And yet, still, from a business perspective, that change isn't keeping up with the changes in society.

And so some stuff that I'm doing at the moment, some work on the side, is very much looking at how can we celebrate female founders? How can we find the ones paving the way?

And I think AI, whilst that example was an example of how it could create a greater divide, I do think it's also an empowerment and enablement tool.

And there are more female-led businesses now that don't require the funding because they are able to use AI to fill in the skills that typically would only be possible with a huge amount of funding.

I don't know for you, Fern, as a female founder, was that something that, I don't know, has gender ever been a consideration for you in taking that step?

Fern Potter: Yeah. It's interesting, actually.

So there's myself, Sarah and James. So we're predominantly female-founded. James is an incredible ally. And we always say we've got two dogs, so we've got more dogs than men on the team. We like this ratio.

Rowena Humby: They're not coding.

Fern Potter: They're learning. They've got to get the funds.

But it was definitely a conversation that we all had when we set the business up. And it was very intentional, I think, for all of us to go, okay, how do we make sure we're representing in the right way?

Because we're all passionate feminists, James as well. Especially in technology and AI, as you said, there's still limited representation, there's still a bias.

There's a lot of organisations that are coming through because AI is lowering that barrier to entry and to build. But there's so much inherent bias that exists and a lot of men still in the room.

So I think doing what we can to be able to raise the voices of women and work into the right groups is where we need to be.

Rowena Humby: Yeah, it's so important.

And actually, that's the mission of The Female Lead.

So The Female Lead is sort of a two-part business. It's a charity and a not-for-profit. And it started with, it was actually a charity set up by my mum, Edwina Dunn, when she left dunnhumby.

She basically was like, “Wow, I was the only woman in the boardroom for the last 30 years.” She only ever had conversations at really senior levels with other men, she felt like.

So she wanted to say, “How can I get more women to take a similar path?”

The Female Lead started as a book. She celebrated 60 women who shaped the world. It was everything from cosmetic scientists to activists to campaigners to celebrities.

And she got brand sponsorship to get a book into every school in the UK and US, which was amazing.

But then when she was speaking to the girls in these schools, they were basically like, “I mean, it's great. But then when I go online, I feel really shit about myself,” and social media and all of this kind of thing.

And so we decided to create a social campaign and we did Disrupt Your Feed, which is if you follow six new amazing women in a field that you are inspired by, your algorithm changes and it enables you to get more content like that.

And so we did this big sort of paying it forward of amazing women to follow if you care about swimming or science or tech or whatever it might be.

But today, what's incredible about how that's then grown is that we have over 9 million followers. We have a monthly reach of 45 million.

And we are basically now using that data to understand what do women care about? What unites them? What divides them? What are the topics that get them all lit up and positive? What are the topics that make them frustrated?

So that's the media and charity side.

And then we've set up a partnerships agency, which is all about how can we then help brands use that information to really create female-first products and basically start to understand, as women, as consumers, what is it that they care about at the moment? How are these cultural moments affecting brand choice?

I think our aspirations are to bring a bit of Starcount and The Female Lead together on that.

Fern Potter: I see where they actually really fit.

What a beautiful way of being able to use information and data, turn it into real human insight and actually be female-first.

We need to be loud and proud about that. I think, as you said, the data's showing that we are the power that are purchasing.

So let's tailor, as opposed to taking something and tailoring it towards women, let's be female-first from the ground up and actually grow business as well as consumer product.

That insight, that's really fantastic.

Have there been challenges to The Female Lead role? How do you balance it? You're not doing a lot. You just don't want to sleep at night.

Rowena Humby: Well, do you know what, actually, Fern? The opposite. My secret weapon is the amount of sleep I get. That is how I keep going.

Fern Potter: Everyone's got jealousy. If you've got all of this ability that puts you on, you want to get up at five so that you've got more of the day.

Rowena Humby: I'm like, no, get your eight hours if you can.

From a Female Lead perspective, I love the fact I still get to work with Mum. It's brilliant. The fact that we get to do that together is super special to me.

We've obviously both got a love of data and understanding people, and then it manifests itself in that more retail consumer world that she's from in The Female Lead, and then the brand and agency world that I love with Starcount.

But yeah, from a balancing workload perspective, I mean, it's a lot.

I'm technically with The Female Lead a sort of day a week, but in all honesty my time ebbs and flows depending on where it is.

But I think, as we can see them going into a similar direction and starting to speak to even media agencies and media-owner partners about The Female Lead, it's starting to feel more like one thing.

This is about behavioural change for all consumers and all brands. And this is if you want to deep dive specifically into female-first products or whatever.

Fern Potter: I love that.

Bringing it back to the Starcount business, if clients want to work with you, what are the common questions that you're answering where you go, right, Starcount's the solution?

If I'm listening to this conversation, I'll be like, that's what I need. Let's bring it into a bit of your customer profile.

Rowena Humby: Yeah, brilliant.

So we primarily work with media agencies. That's both the holding groups and the indies. But we also work with media owners and advertisers.

I think what unites the work that we do is all around understanding audiences, customers, understanding how you reach them in the moments that matter and how you tap into their current spending behaviours and make a shift.

So because we are basically bridging that online intent and interest data to understand what that audience currently cares about, why is it relevant to them now, and then blending that with their spending behaviours to understand what brands are they currently shopping with.

A lot of the work we're doing is, how can I grow my share of wallet as a brand? How can I tap into a new audience or new market? How can I reach younger audiences? That's a huge one that we support with.

Where are my audiences when they're not with me? Where else are they spending?

Fern Potter: How dare they?

Rowena Humby: Yeah, exactly.

We've done a few projects for brands direct and for media owners. We do first-party data enrichment.

So if you're a publisher or you're an advertiser, we can match our data to yours and show you who they are demographically, what they're interested in and where else they spend.

For media owners, it gives their inventory non-endemic spending power because we can show not just what they're reading about or doing on that inventory, but also where else they're spending.

And then, from a first-party data enrichment perspective for a brand, it's: what is my share of wallet? Where else are my customers spending their time? Are they shopping with my competitors as well as me?

And then using that to shape a growth strategy, understanding who are your loyal customers, who are your cross-category customers, and then, of your lapsed customers, where have they gone, and being able to use that as a way to drive them and bring them back.

And then, with the agencies, I love working with the agencies because every day they're working on a different brand challenge.

Fern Potter: Brilliant, isn't it? It really is, how much variety you get within those groups is incredible.

Rowena Humby: Yeah. In the morning, you're talking about how you get people to shift into, I don't know, animal-free products. And in the afternoon, you're talking about how you can, I don't know, get someone to change the way that they dress or whatever. It's like a real shift.

Fern Potter: I'm here for it. I've got the taste. What do you want?

Rowena Humby: Exactly. I've got the data.

But how our tool manifests itself is we are actually a data-as-a-service, software-as-a-service business. So we have a platform. We have a tool.

It's beautiful. I can say that because I didn't build it. My Co-founder, Mike Field, did.

Fern Potter: If you've seen it, I will confirm it.

Rowena Humby: Thank you.

It's very straightforward to use, which is important in what is becoming a huge SaaS market.

So people can either bring our data into their tools or licence our product and essentially be able to build and explore audiences, understand those rich insights, but then, very importantly, directly plug that into their activation tools, whether that be DV360, their out-of-home provider, connected TV, whatever it may be.

Fern Potter: That's a huge benefit, isn't it? Because it just then becomes intrinsic in the workflow as opposed to another step.

Rowena Humby: Exactly.

Fern Potter: You can build into, as you were talking about before, being able to actually have that insight and start developing that return path is going to be incredible.

So, we talked about the return path. Is there any other part of the business and this cohesion of maybe The Female Lead and Starcount? Where do you think you're going to get to? Where do you want to go? What's your vision for the next...

Rowena Humby: Yeah. Actually, I was talking about this earlier. I was like, does anyone have a five-year plan anymore? Is it literally a 12-month vision because everything's moving so quickly?

Fern Potter: I know. It does feel, I think we can have a five-year plan and then be like, well, but maybe that'll be next year.

Rowena Humby: Yeah, exactly.

Although if I look back five years ago, you think you know where you're going and then the pivots happen.

But I would say, as I said in my story, I've had a huge amount of pivots and it feels like they've slowed down, which I think means that we've finally got to where we're supposed to be.

Fern Potter: You're ready for it.

Rowena Humby: Yeah. I mean, I'm coming to you for advice if there is, like they were saying, this humanitarian crisis through AI. But, you know, you're ready for it.

I think where I'd like us to go, so where we're focused at the moment is, as I mentioned, we built this tool. We are doing a huge amount of work with amazing logos, agencies, brands, media owners, in using that data to be able to find high-value audiences, growth audiences, based on intent, interest and spend.

Where we are growing is, as I mentioned, Battlegrounds.

So how can you be more strategic before you go after those audiences?

A lot of the work that we get is, “I've already been told what audience I'm going after.”

We're starting to play more in the sort of, who should you be going after? And how can we help you by understanding the whole category you're competing in, the competitive spend across that and therefore who are the likely to switch? Who are the ones that are most likely to be valuable to you? And what messaging and targeting is going to help you find those people?

And then the final piece, so that's the very start, I guess, to your human start, human end, is how can we understand people's emotions at their start and then also the outcomes that happen at the end?

We're very focused at the moment on using our data to look at how that has shifted behaviour.

So whilst a brand is able to measure the success of a campaign from their own customer perspective, do I have new customers? Did I see an uplift in spend amongst existing?

What we're able to do is contextualise that in the market.

We've had a few agency partners come to us and say, “Well, we used your data to run the campaign, but it doesn't look like it performed very well.”

And then when we've looked in the data, we're like, “Well, the whole category was down, but your client was down a hell of a lot less.”

So it's enabling you to contextualise behaviours in the whole market. And I think that's super important because it can be easy to just focus on your internal understanding of the world rather than looking at what's going on elsewhere.

Fern Potter: And that's beautiful, having that holistic picture.

I think traditionally, you said search is one component, but search has been disintermediated.

So when you can start bringing a whole real-world example in with the open banking and the three pillars that you have, that really gives a true picture of what's going on, as opposed to probably what we've seen previously, where you don't have that macro context of what's going on in the environment.

Rowena Humby: It does.

And it's amazing to see. We work on some really tricky briefs about getting people to shift bank accounts. That's a huge thing for a customer to overcome.

And we're looking at how people spend.

The beauty of the open banking data is that it connects all your bank accounts into one place. So it's used for things like money-monitoring apps or investment apps.

So you connect your Amex, your Monzo, your Nationwide, your NatWest account, and your spending is all in one place so you can track it.

And that means that we can see what you're spending online versus offline, when you're actually going in store versus doing something more conveniently, when you do shift those brand spends.

So it's an amazing behavioural panel to understand not only what people do, but then look at the factors that happen around that moment to see what are the triggers and things that influence that change.

Fern Potter: Yeah. And then capitalising on that moment.

Rowena Humby: Exactly.

Fern Potter: And I love that bridging of the MarTech and the adtech data together, that first enrichment piece, because that's human, isn't it?

That's going beyond looking at pixels and cookies or referrals now. It's really about that human element and how you can track across the whole spectrum.

Rowena Humby: Absolutely. But sorry, your question originally was asking me where I want to be in five years.

Fern Potter: Oh, sure.

Rowena Humby: And I guess where I want to be in five years, the journey that I saw that Mum and Dad did with dunnhumby and Tesco, the amazing stories they used to tell me, is starting with Tesco.

Apparently, they got Tesco's data for three months. And then Lord MacLaurin, who was running Tesco at the time, said, “Show me what you can understand about my customers. Show me you know them better than me.”

And they came back and they put 12 baskets on the board table and they filled those baskets with products.

And they were like, “These are your 12 types of customer.”

And he was like, “Oh yeah,” looking at each basket, “that makes sense. That's me. That's my neighbour.”

And then when they took the basket off, they said, “This is how many of these customers you've got and how much it'd be worth if you got them to buy one more item or shop one more time.”

And that was the moment that dunnhumby won Tesco as a client.

Fern Potter: I love it. It's more like creative agency pitching, isn't it?

Rowena Humby: I love that.

And then they went on to developing things like Tesco Value, Tesco Finest, by finding gaps in data.

But the big moment was when they realised they could help the CPGs benefit from the retailer data and start selling it out to them.

And I guess where I'd like to be in five years' time is that this sort of human context, emotion data, people's behaviours, is underpinning every part of the ecosystem.

We are not just working in silos on one brand with each part, but actually the data is the fuel that's helping make those smart decisions, not just to help brands grow, but to help consumers get connected with in a way that they want to.

The advertising ecosystem got better when we could be targeted the things that we love.

It then went a little bit too far when we felt retargeting, we are followed by the internet.

But I feel now we're back in a space where the world has become sophisticated enough to have genuine brand-to-customer connections that are relevant and proper conversations rather than broadcasting.

Fern Potter: Yeah, that's beautiful, isn't it?

I think, as you said, we went too far, to bring it back now into being able to have a really meaningful brand experience as an individual.

That really matters to me because it's at the right time and in my right need state.

I think that's where advertising can just really help connect people again, which we kind of lost, as you said, in this broadcast space.

So I love the value and the work that you're doing at Starcount and The Female Lead piece and your role in being a Trustee there.

Please keep doing it on behalf of all women.

Rowena Humby: Thank you.

Fern Potter: Thank you for presenting and sharing all of that wealth of knowledge because I think your experience, in knowing you and having our conversations, has inspired me and given me some strength to tackle challenges as a female founder.

So keep doing the same, and thank you.

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