CX

Alex Murphy shares a behavioural science and innovation-led approach to delivering customer-first experiences

Following a career at iconic New Zealand brands such as The Warehouse Group, Mercury and 2degrees, Alex Murphy now spearheads CX at Livestock Improvement Corporation (LIC), a world-leading agritech. In this interview, she shares a unique behavioural science and innovation-led approach to delivering customer-first experiences.

What are the unique aspects of customer experience where the customers are farmers?

Earlier in my career, I worked in telco, retail and utilities. Those environments are high volume and highly transactional. You are often optimising for speed, scale and channel efficiency. The goal is usually convenience. Short interactions. Repeat behaviour. Clear conversion metrics. Moving into a genetics and a science-based co-operative serving farmers was a real shift.

What struck me first was the level of environmental complexity. Farmers operate inside biological systems, weather volatility, regulatory pressure and seasonal cash flow cycles. Their day is already cognitively demanding before they even consider interacting with us. So, when we design an experience, we are entering a context that is inherently uncertain and effortful. That changes what matters.

In retail, you might win with delight. In telco you might win with digital convenience. With farmers, competence wins. Reliability wins. Accuracy wins. If something does not work properly, it is not an inconvenience. It can have operational and financial consequences.

There is also a strong culture of autonomy. Farmers are independent operators. They value tools that help them make better decisions. They are not looking to be entertained. They are looking for clarity, dependability and reduced friction. Many of these businesses think in decades not seasons. Trust is cumulative. You do not win with a single great interaction. You win by consistently reducing hassle over time.

For me, the biggest shift has been from designing for transaction efficiency to designing for resilience.

In agriculture, customer experience is not about being impressive. It is about being dependable in a world that is unpredictable.

How are you incorporating behavioural science into your approach to CX?

Behavioural science underpins almost everything my team and I do. Not in a theoretical way, but as a customer design discipline. The first shift is moving from opinion to behaviour – far too many organisations operate with ‘me-search’ instead of research. At LIC we have segmented customers based on what they actually do, not who we imagine they are. We look at task engagement, service engagement and the complexity of the environment they operate in. That allows us to see real patterns. Who engages deeply. Who drops off. Where assisted service compensates for broken self-service.

Behaviour is evidence. Sentiment is descriptive.

The second focus is effort. Behavioural science shows very clearly that effort predicts action. So we map cognitive load, perceived risk and points of uncertainty. We ask where effort outweighs reward. Where perceived loss spikes. Where inertia wins. If customers are not adopting something, I am less interested in how they feel about it and more interested in whether we made the rational next best action too hard.

And finally, we design for the environment rather than trying to change the customer. Customers behave rationally within the constraints we create. If behaviour is not moving, it usually means the exchange is misaligned. Our job is to redesign the decision architecture, so the right action is obvious and low effort.

That is applied behavioural science in practice.

What are your priorities in terms of AI? Can you speak to any interesting use cases?

I think one of the risks right now is that many organisations are jumping to AI as the answer before they have properly defined the question. There is a lot of excitement about capability, but not always enough clarity about the problem it is meant to solve. My starting point is simple. If we are going to use AI, it must reduce cognitive load. If it adds novelty but increases effort, then it is theatre. The best AI is invisible. It removes friction quietly and makes the right action easier. The most interesting use cases for us are behavioural rather than cosmetic. For example, we are looking at how AI can identify early shifts in engagement patterns that predict churn or disengagement. Instead of waiting for a complaint or a cancellation, we can detect subtle behavioural changes and intervene structurally.

Another area of interest is detecting rising complexity in specific behavioural cohorts. If engagement drops under certain environmental conditions, we want to know early and simplify proactively. That is far more powerful than reacting after frustration has already set in.

I am much less interested in using AI to generate better recovery scripts or more personalised empathy messages. Technology should eliminate repeatable failure patterns, not decorate them. If we use AI well, the experience becomes simpler, more predictable and less effortful. That is where the real value sits.

How do you drive a culture of innovation?

There’s a great quote that says “innovating, and building something that customers have no interest in, looks identical at first.” I think this is very true. For me, the customer team should never innovate for the sake of innovating, and it should never be a substitute for fixing fundamentals. If the login is broken, if the billing is inconsistent, if the core service is unreliable, then launching something shiny is not innovation. It’s distraction.

Fixing the basics will always create more value than layering novelty on top of friction.

That belief shapes the culture I am trying to build. I want a culture where solving real customer problems is more important than launching visible initiatives. Where people feel safe to say, this is not working, even if it disrupts the narrative. Innovation dies in organisations where dissent is punished and internal applause becomes the metric of success. I work very deliberately against that.

The cultures where Customer teams thrive is one where external validation matters more than internal validation. Where behaviour is the proof. Where fixing friction is celebrated as much as launching something new. Innovation should create traction in the customer’s world, not just energy inside the building.

What are the KPIs you are most focused on?

I think there has been a shift in CX and we realise that traditional measures like NPS no longer cut it. There are so many traditional CX measures that are fundamentally flawed. They tell you how someone says they feel in a moment. They do not tell you what that person will actually do next. Sentiment is interesting. Behaviour is consequential. I focus primarily on behavioural and effort-based metrics.

The first thing I look at is engagement shift by cohort. Are customers moving into higher engagement with lower environmental complexity? Are we seeing increased self-directed completion where that makes sense? Are they adopting more deeply, more consistently? If engagement rises while friction falls, that is a very strong signal that we are creating real value.

The second area is effort reduction. Completion time. Repeat contact rates. First call resolution. Abandonment at key decision points. Variability in experience. Effort is a leading indicator. Satisfaction tends to lag behind behaviour.

If effort is high, churn is coming, whether the survey says so yet or not.

And third, I care about behavioural outcomes over sentiment alone. Retention. Adoption. Cross-service engagement. Reduced dependency on assisted channels where self-service should work. If customers are choosing to stay, engage and deepen the relationship, that matters more to me than a score out of ten.

For me, the critical distinction is this. Sentiment tells you how someone felt. Behaviour tells you what they decided. And in the end, decisions are what move the business.

What do you think organisations most often misunderstand about their customers?

I think organisations most often misread behaviour by interpreting it as opinion rather than response. When adoption is low, they assume customers are resistant to change. When churn rises, they blame competitors or price sensitivity. When engagement drops, they conclude customers are disengaged.

But behaviour is rarely about attitude. It’s about effort and context. Most customers are not sitting there making emotional judgments about brands. They are making practical decisions under constraint. If something feels too complex, too uncertain, or too effortful, they exit. Not dramatically, but quietly.

Another common misread is over-indexing on what customers say instead of what they do. Surveys might show satisfaction holding steady, but repeat contact rates are climbing. NPS might look fine, but assisted service is compensating for broken self-service. The sentiment can lag the behaviour by months. For me, the key shift is this. Customers do not behave “badly.” They behave rationally within the conditions we create. If behaviour is not moving in the direction we want, that is usually feedback on the design, not the customer.

Once you start seeing behaviour as a response to effort, risk and clarity rather than personality or attitude, the conversation changes. It becomes less about persuasion and more about redesign. And that is a far more powerful place to operate from.