did this campaign give me, and what’ s my return on investment?” If the marketing didn’ t deliver tangible sales or at least pipeline growth, I often lost that client.
That’ s why I’ ve often clashed with agencies. Agencies love to pitch with glossy decks full of engagement numbers. But when you’ re sitting across from a small business owner deciding whether to pay school fees or run another ad, those metrics don’ t hold water. ROI does.
And this is where the distinction lies: actionable metrics vs. vanity ones. Repeat purchase rates, churn levels, customer lifetime value, Net Promoter Score. They may not look as impressive in a pitch, but they tell you whether your brand is building staying power. They may be harder to track, but they cut closer to the bone of consumer behavior. They answer not just what happened but signal what’ s next.
I have also been involved with an e-commerce platform that reported a 40 % spike in website visits and nearly doubled the sales during a Black Friday campaign. The dashboards were great, the team had a party, but buried in the data was something more important: delivery and quality complaints were soaring. The traffic didn’ t matter too long. What ultimately mattered was that over 30 % fewer customers returned the following quarter. Vanity masked a looming problem.
The uncomfortable truth is that many organizations still celebrate the numbers that make them look good, not the ones that tell them the naked truth.
The reality is that misaligned measurement is a nuisance, and it’ s expensive. Campaigns optimized for the wrong goals can erode brand equity even as they deliver shortterm wins.
If you think about it, you know FMCG companies in Kenya that obsessively track unit sales during promotions but fail to notice that consumers revert to competitors once the discounts end. The numbers looked suitable for the quarter, but loyalty wasn’ t built- it was borrowed.
The Missing“ Why”
Marketing and sales data are fantastic at telling us what happened. Sales are down 8 %. Campaign A outperformed Campaign B. Repeat purchases are slipping. But when it comes to the question that matters most- why- the numbers often go silent.
Take a bank that notices a sudden drop in the uptake of its new digital loan product. The dashboards will confirm the decline, possibly even pinpointing the exact week it began. However, they won’ t tell you if consumers were deterred by hidden fees, if the app was too complex to navigate, or if cultural stigma surrounding debt played a role. Only research can peel back those layers.
This is the blind spot of data abundance: numbers describe symptoms, not causes. And when brands don’ t invest in asking the deeper questions, they risk fixing the wrong problems, or worse, declaring success while consumers quietly drift away.
Going back to the Wells Fargo example, the bank celebrated account growth for years, convinced by its own KPIs. But no one was asking why consumers were opening so many accounts or whether they even wanted them. By the time it was revealed that millions of those accounts were fake, created by employees desperate to meet sales targets, trust had already collapsed.
What do you do when sales dip? You will probably adjust distribution, run more
The uncomfortable truth is that many organizations still celebrate the numbers that make them look good, not the ones that tell them the naked truth. The reality is that misaligned measurement is a nuisance, and it’ s expensive. Campaigns optimized for the wrong goals can erode brand equity even as they deliver shortterm wins. promotions, maybe cut prices. But when you actually ask consumers, the problem turns out to be more basic- the packaging size doesn’ t fit the kadogo economy I discussed in this column in the previous edition. Families can’ t afford the large packs being pushed onto shelves. Without consumer feedback, that truth would have stayed buried under the weight of“ sales trend analysis.”
This is why research, both qualitative and quantitative, earns its seat at the strategy table. It bridges the gap between what and why. Without mentioning names, from my work in Research at GeoPoll, I have seen a situation where sales graphs suggested declining interest but the actual issue was availability: shelves were empty because of a disrupted distribution chain. Without directly asking consumers, leadership would have misdiagnosed the problem entirely.
And it wasn’ t for a shortage of data. The team was swimming in data but starving for meaning. That’ s the danger: when we confuse measurement with understanding, we risk making decisions that are datadriven but consumer-blind. Going to the next layer, actually asking customers, completes the equation.
So, get a good research partner, ask customers. Then put that data together with your sales and marketing data and the truth comes out.
The Human Side of Data
If the“ why” behind numbers is often missing, there’ s another equally important truth: every data point is a human being. Behind each transaction, abandoned cart, or churn statistic is a consumer with motivations, frustrations, and aspirations that no dashboard will ever fully capture.
The danger of data overload is that it can turn people into faceless aggregates. A marketer will say,“ We had 50,000 impressions last week,” and forget that those impressions represent 50,000 individuals with very different lives. When you lose sight of the human behind the metric, you start designing campaigns for numbers instead of people.
Think of streaming platforms like Netflix. They don’ t just count viewing hours; they study behaviors at a human level: when do people pause, when do they quit, when do they binge. These subtle patterns reveal more than the topline metrics. If a large share of viewers abandon a show 15 minutes in, it tells you something about storytelling, not just statistics. The lesson
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