The Making - Episode 3

The data said the campaign succeeded. The behaviour says otherwise. So what was the campaign actually testing?

In Episode 3 of The Making, Abeiku takes on Part Four of Rules for the Marketing Communication Executive by Prof. Robert Ebo Hinson & Joel Nettey: Consumer Insight Development and Data Interpretation.

If you've ever watched a campaign hit every metric and still wonder why nothing changed, this one's for you.

📖 Get the book: Rules for the Marketing Communications Executive by Prof. Robert Ebo Hinson & Joel Nettey — 0591343421

Watch Episode 1 and Episode 2 if you missed them.

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Chapters:
0:00 – Why the first answer is never the insight
0:00 – Rule 33: The question behind the question
9:05 – Rule 39: Every campaign tests a hypothesis
11:12 – The promotion that worked every time and changed nothing
16:48 – Reframing failure as data
18:20 – Synthesis: ask deeper, then test what you find

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Transcript

SPEAKER_00 0:00

Have you ever been in a room where someone made a presentation on a research finding and the whole room went quiet, nodded, and moved on. No one really questioned anything, no one pushed deeper. So the finding became the strategy, and six months down the line, the campaign doesn't work. Nobody can explain why either. If this sounds familiar, um, this episode is for you. Welcome to the making right here on Mad Conversations. And this is where I sit with the book, Rules of the Marketing Communications Executive, by Joel Netty and Professor Henson. And in this book, they share 150 rules that they believe should guide every marketing communications executive on their journey, on their professional journey. So in episode one and two, we've already dealt with parts one, two, and three. And in this episode, we are dealing with part four, where the authors talk about consumer insights development and data interpretation. I mean, if you don't have this book, you should go get it. Uh, the details would be in the description, and further details would be at the end of the episode. So uh do grab the book. If you don't have it now, maybe grab a cup of coffee, uh, sit with me, uh, let's go through it together. In this episode, we are discussing two rules: the rule 33 and rule 39. Rule 33 says the question you are asking in your research is probably not deep enough. And the real insights live underneath it. In the question you didn't think to ask, and rule 39 says every campaign is a test of a hypothesis. And if you don't know what your hypothesis is, you can't really learn from your results whether they are good or bad. So here's the thread. If you ask shallow questions, you get shallow insights. We've spoken about insights in the previous episode. We are going to get deeper here. If your insights are shallow, your hypothesis is shallow. And if your hypothesis is shallow, your campaign will produce data without understanding, and history will simply repeat itself. Questions, hypothesis, questions, hypothesis, questions, hypothesis, right? But we want to go deeper than that. So let's get into it. Rule 33. The question behind the question is where the real insight lives. Every research brief contains a stated question. What do consumers think of this product? How is brand awareness performing in this segment? What are the barriers to trial? These are legitimate questions and they will generate legitimate findings. They will not, on their own, generate the deepest insights because they are designed to confirm or measure what is already suspected rather than to discover what is not yet known. The question behind the question is the one that goes deeper, that asks not just what the answer is, but why the answer is what it is, and what the structure of the situation is that makes the answer inevitable given the conditions. The question behind what are the barriers to trial is what is it about how consumers experience this category that makes engagement feel risky? And is that risk perception accurate? Or is it based on misunderstanding that communication could correct? The question behind how is brand awareness performing is was it about the brand's presence in the market that is producing this level of awareness, or what would need to change about the communication environment to move it? These deeper questions produce deeper answers, and deeper answers produce stronger insights. Ask the question behind the question. Then ask the question behind that. The deepest insight is really on the surface of the research brief. It is what emerges when the questioning goes far enough. The stated research question produces findings. The question behind it produces insight. Ask deeper. It is where the real strategy lives. Wow. You know, most research in this market stops at the first answer. And I don't think it is because people are lazy. It's because people the very first answer feels like it's enough. It sounds definitive, it's it fits on the slide. It's everyone in the room is ready to move on to execution with it. Their client asks, why aren't people buying? Their team runs a survey. The survey says price. Everyone nodes, okay, let's do a promotion. So the strategy becomes run a promotion. Brief goes out, campaign launches, and six months down the line, you are back to the same room discussing the same question because price was the finding. There was never the insights. There's a framework called the five whys, and it's simple. I'm sure you've heard it in communication. You take the first answer and you ask why. And then you ask again why and again until you get to the thing underneath the thing. Why aren't people buying price? Why is price the barrier? Because they don't see enough value to justify the cost. Why don't they see the value? Because they don't fully understand what the product does for them. Why don't they understand? Because our communication has been focused on features, not the problem, the product source. Why have we been focused on features? Because the brief was written by the product team and not the strategy team. That's the five whys. So you see how we went? Look how we ended up. We started at price and we landed at the brief was wrong. Those are the completely different problems. The first one leads to a discount, the second one leads to a fundamental rethink of how the brand communicates. One is a tactic, the other is a strategy. You can also think of it as what? So what? Now what? The services price is the barrier. That's the what. So what does that mean? It means perceived value isn't landed. That's the so what. Now what do we do? We don't run a promotion, we redesign the communication to address the value gap. That's the now what. Most teams stop at their what's, right, at the beginning and jump straight to the tactic. They skip the so what entirely, and the now what becomes a reaction instead of a strategy. Here's the part that should make a lot of us very uncomfortable. The book calls it confirmation research. Research designed to justify a strategy that's already been decided. The most expensive form of self-deception, you can call it. And I need us, you and I, to sit with this because how many times have we been in a room where the strategy was decided before the research came back? The research wasn't there to discover anything, it was just there to give the design or decision a slide in the deck. That's no research, that's decoration. And we've dealt, we've talked about it, right, in episode one. Ask the question behind the question. And when you think you've gone deep enough, go one more level deeper. The deepest insights is really on the surface of the research that you're looking at. It is what emerges when the question goes far enough. So always try to go deep, deep, deep, deep, deep. I'm gonna borrow some um lyrics from Pear's music. In his song Deeper, he says the surface is bleak and uh deeper is sweet, so please take me deeper. Deeper is where I belong, deeper is where I'm strong. As marketing professionals, uh, we should understand that the surface is always bleak, it's shallow, and deeper is where we belong, and deeper is where we are strong. We know that the deeper you go, the stronger your insight. You know, the strategy is to go deeper. And so he says the stated research question produces findings, the question it produces produces insights. Ask deeper, ask deeper, ask deeper, always ask deeper. Why? Because it is where the strategy lies. Well, let's get into rule 39. Every campaign tests a hypothesis. Know what yours is. This is interesting. The campaign that does not know what hypothesis it is testing cannot learn from the results. It can measure performance, it can know whether awareness went up, whether sales increased, whether engagement improved, but it cannot know why these things did not happen or actually happened, because it never made explicit what causal mechanism it was relying on to produce the effect. The data accumulates, the understanding does not. Every campaign built on genuine insights is as at its foundation a causal hypothesis. If we communicate X to this audience in this way through these channels, it will address the behavioral mechanism identified by the insights and produce wide change in their behavior. The hypothesis makes explicit the causal logic that connects the communication strategy to the expected outcome. And this explicitness is what makes the campaign's results intelligible because it defines in advance what it would mean for the hypothesis to have been confirmed, partially confirmed, or refuted. Knowing your hypothesis also allows you to learn why the campaign does not perform as expected. If the communication was well executed, the media was efficiently delivered, and the target's audience was reached. But the expected behavioral change did not occur. The most useful question is not why did the campaign fail, but what does the campaign's failure tell us about the hypothesis we were testing. The hypothesis may have been wrong, the insights may have been incomplete. Know your hypothesis, test it consciously, learn from the results, especially when the results is not the one you expected. Every campaign is a test of a causal hypothesis, know what is yours, or your results will produce data without understanding, and history, as they say, will simply repeat itself. Let me give you a scenario. A telco runs a data bundle promotion, three weeks, discounted bundles, and sales spike, 40% uplift. The report comes back and everyone is celebrating. Promotion ends, uh, sales drop back to baseline within a week. Next quarter, someone in the room says, let's run it again. Some the same promotion, same spike, same drop-off. Nobody in the room ever asked, what was our hypothesis? What were we really actually trying to test? If the hypothesis was price-sensitive non-users will trial mobile data through this promotion and convert to regular usage, then the post-campaign uh data is telling you something important. The hypothesis was wrong. So you got the trial, but not conversion. People bought the discounted campaign. People bought the discounted bundle, used it, and uh went back to their normal behavior. Their barrier to regular usage isn't price, it is something else. Maybe it's a habit, maybe it's perceived usefulness, maybe it's network quality in their area. The promotion didn't fail as a result. It did what promotions do. It failed as a hypothesis about what drives long-term adoption. But because nobody stated the hypothesis upfront, nobody learned anything. They just repeated the same campaign and got the same temporary results. Quarter after quarter. The data is accumulated, the understanding, no. Now, here's a second scenario. A consumer goods uh brand runs a three-month brand awareness campaign. Awareness score, awareness scores go up. Let's say by eight points, the report says there's a success, but purchase intent doesn't really move. Without a hypothesis, the team's conclusion is awareness worked. Now we need a separate conversion campaign, more budget, more activity. But the hypothesis had been stated. The barrier to purchase is unfamiliar, and increasing awareness will shift consideration. Then the data just told you the hypothesis was wrong. People know your brand, they just don't want it. That's a completely different problem and a much harder one. But you see, you only learn that if you knew what you were doing or what we were testing in the first place. And this is where I need you to connect back to rule 33 because these two rules are actually an argument. Rule 33 told us that most research stops at the surface question. Remember? Rule 39 is telling us that most campaigns launch without a clear hypothesis. But the second problem is caused by the first. If you didn't dig deep enough, especially at the research stage, if you stopped at the first answer instead of asking questions beyond the question, then the hypothesis your campaign is built on is shallow. And a shallow hypothesis produces campaigns that can measure activity but can't really explain an outcome. So let's go back to the telco. Why did they default to a price promotion in the first place? Because the research said price is a barrier. That was the surface question, producing a surface finding. Now, nobody asked the question behind the question, is price actually the barrier? Or is it that people don't see enough value in the mobile data to justify any price? If someone had applied the five Y's, if someone had pushed past the first answer, the hypothesis would have been slightly different, or completely different. Instead of reduce the prices and they'll buy it, it might have been demonstrate the daily utility of mobile data in their specific context and they will see the value. That's a completely different campaign, right? A completely different hypothesis, and it would have been produced, it would have produced results you you could actually learn from, whether it worked or not. That's the chain the book is laying across these two rules. Shallow question leads to shallow insights. Shallow insights leads to shallow hypothesis. Shallow hypothesis leads to a shallow campaign that produces data without understanding. And without understanding, history simply repeats itself. You run the same campaign next quarter, you launch another awareness campaign, you keep doing the same thing that didn't work because you never really understood why it didn't work. And here is where uh the book says about failure that I think is the most important shift in the entire chapter. When a campaign doesn't perform as expected, the useful question is not why did the campaign fail? The useful question is what does the campaign's failure tell us about the hypothesis we were testing? That reframe changes everything completely because now failure isn't a dead end to anything, it's data. The hypothesis may have been wrong, the insights may have been incomplete, the mechanism you are trying to identify may have been insufficient. Each of these conclusions points toward a more refined understanding that makes the next campaign even better. But you only get that learning if you knew what you were testing. If you launched without a hypothesis, all you have is a bad quarter and a room full of people pointing fingers at each other. So know your hypothesis, test it consciously, learn from the results, especially when the result is not the one that you expected. What is part four telling us? It is essentially telling us to stop accepting the first answer. The stated question in your research produces find it. You know that the question behind it produces insight. And the distance between those two are the distance between a campaign that generates activity and a campaign that changes behavior. Once you have that insight, don't waste it. Turn it into a hypothesis, state it clearly, test it consciously because a campaign without a hypothesis is a campaign that can't teach you anything, not when it works, and especially not when it doesn't. The discipline is simple to describe and quite difficult to practice. So ask deeper, then test what you find. That's two out of ten rules in part four: consumer insights, development, and data interpretation. And honestly, these two alone could change how your entire team approaches research and campaign planning. But there are eight more rules in this chapter, including how qualitative research finds truth that numbers obscure, and why insights must travel from research all the way through execution without getting lost along the way. So let me ask you: when was the last time you stated your campaign? Or you stated a hypothesis for your campaign before you launched it? When was the last time you pushed past the first research finding and asked the question behind it? And if you can't remember, uh, this episode just showed you why that matters. So do get the book, right? Do get the book. I'm dropping the details in the description. Share this episode with someone who needs it. Drop a comment, tell me which of the rules changed, challenged you the most or changed your thinking. And please don't forget to subscribe so you don't miss what's coming next. This has been the making, right? Here on Mad Conversations. I've been your mad friend, Abeku. See you in the next one.