Data is not insight

Imagine this…

You’re handed a 50-page report filled with charts, graphs and metrics.

You scan the numbers, review the percentages and pick out what appear to be the key insights and insert them into your next presentation.

Job done!

Except, it’s not. Because, here’s the thing: data is not insight.

And in finance, we’re especially guilty of confusing the two.

We obsess over conversion rates, click-throughs, AUM inflows, performance growth.

But those numbers are like footprints in the sand. Most of the time, they show you where someone walked, not why they walked there in the first place – or even what they were feeling along the way.

That’s where the psychology comes in.

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Why your content products flop (even with all the numbers)

I’ve seen financial businesses spend tons of $$$ collecting data, only to ask the wrong questions.

Or worse, none at all.

• Collecting nothing? You’re making decisions in the dark.
• Collecting everything? You’re drowning in noise.
• Analysing badly? You’re telling yourself the wrong story.

Take attribution modelling. It’s supposed to tell you which marketing touchpoint drove the lead. But in practice, it may only tell you what was clicked first or last.

It misses the emotional triggers.

It misses the trust that was built over months.

It misses the quiet reassurance of repeatedly seeing your brand in safe contexts.

It misses the relief that nudged someone to act when markets turned shaky.

The real insight isn’t that your ‘Google Ad drove the lead’. The insight is that your prospect finally felt confident enough to click because they trusted your voice over the noise.

According to a 2022 Gartner survey, marketing analytics only influence 53% of marketing decisions.

That leaves a big gap. And the gap isn’t in data collection, it’s in human interpretation.

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The problem nobody likes to admit

Even when data is clean, analysis isn’t neutral.

Humans interpret. And humans are biased.

• Confirmation bias means that you’ll find the story you’re already looking for.
• Regency bias means last month’s spike seems more important than it is.
• Anchoring bias means you stick too closely to one figure, even if the market has moved on.

I’ll say it again. Humans are biased.

In finance, we like to think we’re rational. But the reality is that we’re as swayed by psychological shortcuts as much as the people we’re trying to market to.

And if we don’t challenge our interpretation of data, we risk building campaigns on sand.

Before long, you’ll start to get a horrible sinking feeling.

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Numbers need context

As an ex-financial equity analyst, I spent many years analysing company, industry and market data. Every piece of information told me what happened in the past.

None of it explained what was going to happen tomorrow.

But to make forecasts, the trick was always about context: layering the ‘what’ with the ‘why’.

1. What was sentiment doing?
2. What were the incentives?
3. What were the unseen pressures?
4. What was behind the decision-making?

It’s exactly the same in marketing. Numbers show the trend. Psychology explains the behaviour behind it. Put them together and you’ve got something powerful:

real insight.

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Turning data into insight

So, how do you get beyond numbers? Here’s a bit of a breakdown:

1. Ask the human question first. Instead of simply asking “what’s our CTR?” ask “what emotional state drives someone to click at all?”

2. Challenge your biases. Get someone outside your team to review your conclusions. It’s harder to see your own blind spots.

3. Layer psychology onto metrics. Don’t just measure churn. Ask what loss aversion, fear or inertia kept clients from staying.

4. Tell a story. Data alone doesn’t persuade. Data with narrative moves people.

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Final thought

The marketers in finance who win aren’t the ones with the fattest dashboards.

They’re the ones who can interpret the numbers with empathy, challenge their own assumptions and explain the why behind the what.

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Speak soon

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