Great data needs a storyteller. That is not a soft skill. It is the skill.

When you work for a brand or for clients, you are always trying to find something that gives you an advantage. Marketing has many initiatives that deliver value, but gaining a slight advantage means you are always looking at different data signals: quantitative, qualitative, direct responses, customer stories.

When you create content, you cannot decide that it is engaging. Your audience decides. Collecting data signals is really listening. You listen to the audience, treat the signal as feedback, and ask how you scale what worked and do it better next time, in a way that genuinely resolves the audience's pain points and helps them hit their goals. That is the discipline.

Technology in marketing has never been better. We are in something of a golden age for those who value good data and strong data foundations, because the technology lets you collect, automate, and scale ideas and performance much faster than was possible before.

The implication is that industry benchmarks on ad performance or engagement rates are being rewritten in real time. We are writing the new benchmarks rather than chasing the old ones, and no one knows for sure what is coming next. Anyone claiming they do is either lying or making a lucky guess at best.

For me right now it is a springboard for ideas. Like having an extra person in the room to bounce ideas off, with a wealth of experience and expertise. The limits are how quickly we can think and how creative we can be with what these tools enable. A bigger palette and a bigger canvas.

We respect the existing funnel but we follow a flywheel model: attract, engage, delight, with the customer at the centre. The shortcoming of a funnel is that you have to keep feeding the top of it to get anything out the bottom, and the returns diminish. The flywheel gives sustained momentum.

If you listen to your audience and your customers properly, they will recommend you to others. That is how a great deal of buying happens these days. People value the recommendation. The momentum from that recommendation engine is what makes growth genuinely sustainable and efficient.

I am nothing if not a hypocrite. The flywheel is accurate, but buying processes are also complicated, long, and rarely involve a single buyer. No team operates in isolation. So sometimes it is less of a flywheel and more of a pretzel, with twists and turns and several stakeholders folded into the same shape.

A quote I find myself repeating from Chekhov: do not tell me the moon is shining, show me the glint of light on the broken glass. Show, do not tell. The most powerful way to bring a prospect along is to ask directly what they need, then show them the value, rather than telling them and hoping it lands.

There are many metrics one can talk about, and the danger is analysis paralysis. The one I look at most is self-reported attribution, the practice of asking people directly how they heard about you. The metric for me is not really a number. It is a story.

It tells us how they heard about us, yes, but more importantly why they decided to engage at that point. That is the bigger picture, beyond the logistics. It points to what to do more of, and it surfaces overachievers that we may not have noticed in the standard data. It is the antidote to analysis paralysis.

There are different metrics for different purposes. Sourced is one, and it has problems: it is all-or-nothing, and it can disproportionately favour either marketing or outbound prospecting. I look at influence models too: W-shaped, linear. Combined they give me cost per demo, cost per sales-accepted opportunity, cost of acquisition, and how much we are influencing each stage. The board-level report uses those.

The underlying question we care about as a scale-up is what the data tells us about the future. How do we forecast from it? Where are buying cycle lengths going? What should we lean into? Rather than obsessing about the past, what is the action we can take next.

The main thing is a spark of curiosity, more than specific tool experience, because tools can be taught. The desire to challenge silent assumptions in the team and ask what else we could be doing. Beyond that, the willingness to come without ego or sense of entitlement.

I want an environment where people feel comfortable being honest, brutally so. I want to hear what is not working, what is a waste of time, what we should be doing more of, what trend we should be leaning into. The best version of that culture is a safe space where people can speak their minds regardless of personality type, introvert or extrovert.

A mentor of mine pointed out that working hard to create that honest environment has a cost: people may have opinions on you, and that can throw decision-making off course. She used an analogy. If you drove a Ford or a Fiat, no one would have an opinion. If you drove around in a pink Ferrari with white spots, everyone would have an opinion.

The advice was to get comfortable being uncomfortable. You cannot control people's perceptions of you. Internalising that has helped my decision-making considerably.