Applying the first principles concept to your marketing strategy, challenging all underlying assumptions and conventions before rebuilding, can help you make better decisions. Nick Garner runs through the basics.
Reasoning from first principles is a process where you break down complex problems into the most basic elements and rebuild. As a scientist might say: “What are we absolutely sure is true? What has been proven?”
Reasoning by analogy
‘This’ is like ‘that’, therefore ‘that’ is like ‘this’. A good example of reasoning by analogy can be seen in the phrase “in my experience”. This new executive says confidently: “You should run your campaign with this partner, because in my experience this will work.” We all value experience, but does it necessarily represent good judgment?
Going back to what a scientist might ask: “What are we absolutely sure is true? What has been proven?”
The new executive wants to sign off a large budget against ‘experience’.
“What are we absolutely sure is true? Well, that an executive ran a campaign with a media partner that was successful for a different brand than ours.”
What has been proven? Nothing. What about the creative? Was it different? And in what way? How is that other brand different to yours?
The point about experience: it’s the accumulation of years of knowledge that gives somebody a holistic overview of what is ‘best’. It’s a refined version of reasoning by analogy.
How to reason by first principles
Have you ever asked yourself, “Why do I think this?”
‘This’ could be a strategic view on a market place. It could be an opinion of somebody. It could even be a deeply held long-term belief you treasure.
I repeat: have you ever asked yourself why you think ‘this’?
How do you know this is true? What if you thought the opposite?
Let’s say you assume Google AdWords does not convert well. Why do you assume that? Was the creative good enough? What about the landing pages, what about the competitiveness of the offer?
Now let’s imagine the opposite: “AdWords works very well for me”. What works well? Maybe you have organised your keyword selection more efficiently, modified your offer or tried a different landing page.
By asking yourself, “What if I thought the opposite?” you are looking at an old problem in a new way.
Looking for evidence
How can you back this up? What are the sources?
You’ve got a marketing campaign that’s been very successful. The next question should be “what went right?”
Let’s say you assume what went right. How did you validate this assumption? What sources did you use for the validation? Were the analytics correct? Are you sure?
If you have important decisions to make, it’s important to never assume anything until you can back up assumptions with valid information.
Considering alternative perspectives
What might others think? How do you know you are correct?
A way of thinking in opposites is to consider alternative perspectives. That marketing campaign was a success… for you. It generated a high conversion rate, but right now we don’t know the long-term revenue per customer.
What would the data analyst think about the campaign? The analyst has more information on the long-term revenues from certain customer groups. Would the analyst be happy with this group of converting customers?
If the analyst went through the demographics/interest groupings on this batch of conversions, how would that match up with previous players from similar player segments?
Did those previous segments go on to produce on or above target revenues?
If so, great. If not, time to change that marketing campaign.
What if I am wrong? What are the consequences if I am wrong?
What if the conversions were excellent, but the expected return on investment was poor based on player segment analysis?
You’ve been telling everyone how the campaign conversion rate was way above average. You did the segment analysis and found out these players are likely to be bonus hunters.
You have a choice. You can either admit you are wrong or be defiant and hope people don’t know the truth. If you are wrong, what are the consequences?
You’re expected to run the same campaign again since the numbers were above average and everyone believes you’ve got a magic ‘touch’.
The consequences: you have short-term gain with above-average conversions, but long-term loss once player revenues start to come through.
Questioning the original questions
Why did you think that? Were you correct? What conclusions can you draw from the reasoning process?
You believed the marketing campaign was a success because conversion rates were high.
Subsequently you talked to the data analyst and realised the customer segment you attracted were bonus hunters. And it’s likely they will produce poor long-term revenue.
High conversion rate is a good thing. It’s just you have to have the revenue to support the cost of the marketing campaign.
You might lower the cost per acquisition in the marketing campaign. You reduce conversion rates but you increase potential return on investment…
You might find your business is being driven by fundamentally weak assumptions.
“What are we absolutely sure is true? What has been proven?”
Nick Garner is a marketing strategist and founder of RIZE digital, the igaming marketing consultancy and web development agency. Nick uses his knowledge to help clients deliver successful web development and earned media marketing projects.