Jun 4, 2025 | Category, Customers, Demand chains, Marketing, retail
Mass market retailers all use the same, or very similar metric to measure store performance: Dollars revenue and/or margin per square foot, or linear shelf metre. In addition, they track the size and content of the customer ‘basket’ to optimise product range against those key performance measures.
This leads to a mindset of short term profit maximisation in the buying office, at the expense of everything else. Only senior levels talk about strategy, and then in most cases, they fail to grasp the qualitative reality of ‘strategy’ and fall back on the numbers.
Shoppers do not care about your margins/sq metre, irrespective of how you generate it (price, stock turn, or supplier ‘shelf rentals’) they care about range convenience, on shelf availability, and of course, price.
But price is only one of the considerations, an important one, but only one.
Ignoring the others is asking for trouble in the medium term
Trouble is what the Australian gorillas now have.
Their domestic supplier base has been brutalised, and the leverage they can exert on international suppliers is way more limited, simply because they do not have the scale to apply the pressure. Now in the absence of a high $A, they are suffering, and that suffering is unlikely to ease any time soon as the economy is likely to flatten in the wake of the ‘stupidity blanket’ being thrown over world trade by the US administration.
In addition, they now have become populist targets for a body politic that has no idea of the economics and dynamics of the ‘paddock to plate’ supply chain.
The marketing default has become loyalty cards, an added incentive to shop at the same chain, as they will give you something in return. Trouble is you cannot buy loyalty, you can only earn it. How many do you know with a wallet stuffed with ‘loyalty cards’ who are not in the slightest ‘Loyal’?
Jun 2, 2025 | AI, Communication, Governance
Analysis implies the intelligent interrogation of data, the use of differing ‘frames’ through which to see the data, and to enable those non obvious connections to be made.
First you need ‘clean’ data, without which, nothing that follows will be worth much.
Thoughtful, critical analysis of data leads to insight, from which comes that elusive lightbulb moment.
Reporting is the opposite, it simply requires the cleaning, summarising and posting of the data without the critical thought from which real insight evolves.
No lightbulb.
AI is good at that, while not being good at generating insight.
Being data rich but insight poor is now a very common problem.
AI will not solve it for you, people are needed. Not just any people, seat warmers, but the right people with the curiosity and ‘why not’ attitude of youth, combined with the wisdom of experience and domain knowledge.
Unfortunately, these people do not grow on trees, ready for the picking. You have to grow and nurture them yourself, while recognising that many will move on at some point. The old adage of a rising tide lifts all boats is nowhere more relevant.
May 30, 2025 | AI, Marketing
The market research industry turns over big dollars by providing reassurance to marketers that when they are wrong, they have an acceptable excuse.
The recent election campaign and associated polls demonstrate comprehensively how broken market research can be. It should have been simple. Is Labor going to win, will the conservatives take the lollies, or will it be a split result? It was almost a binary choice, but no poll I saw was even close.
Given that failure, how in heaven’s name can we reasonably expect such a broken system to deliver reliable answers to challenging questions about the future behaviour of customers and potential customers in a competitive and volatile environment? Add into the mix the inability of most marketers to understand the competing forces in their market sufficiently well to ask good questions and therefore write quality research briefs. That delivers a perfect recipe for pissing money against the wall in pursuit of reassurance.
Over the years as a much younger marketer, I spent a lot of money on market research. It took a while, but I did come to realise the data was only a tiny proportion of the game. The real challenge was building the wisdom, insight, and market gutfeel to be able to ask those really good questions. Then, when a surprising response emerged, have the curiosity to further interrogate it from a positive and genuinely inquisitive perspective to get an answer to the eternal question: Why is it so?
In the last year or so, and accelerating at an astonishing rate, is the ability delivered by AI to gather and process market and behavioural information that can be used to ask those challenging; why is it so’ questions.
The process of market research has been totally up-ended. No longer do you need to spend tens or even hundreds of thousands of dollars over months to get shallow and often dated results. Now you can replicate the task quickly and cheaply with superior results using AI, and what is emerging as ‘synthetic research’.
Traditional research is good at telling you what has happened. It is good at counting. However, if you need to know what will happen in the future, and you use yesterdays tools, good luck!
May 16, 2025 | Marketing
Unfortunately, there is no single silver marketing bullet.
There are hordes of so-called marketing experts out there who will flog you a package of promises, digital and otherwise, that almost always end up being hollow.
Marketing success evolves from strategy, making really tough choices in the absence of perfect information, then implementing, learning, and going again.
It requires you to make choices about the future, and how you will face it, shape it and leverage it.
You cannot look at the numbers, they do not exist yet.
You cannot look to the success of others, and successfully copy and paste, as every challenge and context is different.
You must forge your own way, while learning the lessons of others and applying them to your situations.
The only silver bullet in marketing, just like every other field of endeavour, is time, energy, focus, compounding domain knowledge, and perseverance.
Get those five factors aligned, and you will have a good chance of winning.
Apr 24, 2025 | AI, Marketing, Strategy
‘Lean thinking’ is a mindset and toolbox to drive optimisation. Little more, beyond the use of common sense and humanity.
Prominent amongst the tools, and the one I probably use the most is ‘5 why’.
AI has given us an entirely new use case that leverages the insights that a 5 why process when done thoughtfully can deliver.
Prompt development.
There are now hundreds of prompt templates and mnemonics emerging from the woodwork, many claiming to be ‘the one’.
All I have seen use a variation of the Lean ‘5 why’ tool.
Most AI users look at the first output of a prompt into any of the LLM tools, and it is sub-par. Generic recitations of what the trained information base reflects as best practice. The beauty of these data driven assistants is that you can push back as much as you like without them taking it personally.
You can point out areas of failure, misinformation, gobbledy-gook, or imagined fairy tales. You can ask for specifics, deeper analysis, sources, or give it examples. The output then improves with each iteration.
You can also ask it what you might have forgotten to ask, or has been missed for some reason, and ask for suggestions. This interrogation of the tool can reveal things you would not have thought of under normal circumstances.
Go through that process 5 times, and in all likelihood, you will not only have something entirely different to the first response, but it will also be infinitely better, and tailored to the need. You will have cleared away the unnecessary, banal, insignificant, and generic, leaving a response that equates to a first principle response to your evolved prompting.
Continuous improvement by AI driven lean thinking.
What a boon!
Apr 14, 2025 | Change, Communication, Governance, Leadership, Marketing, Strategy
When you look you see Hofstadter’s law around you everywhere, every day.
We all understand Murphy’s law, which accurately states that is something can go wrong it will, probably at the worst time. Murphy has a sibling, articulated by Douglas Hofstadter which states: ‘A task always takes longer than you expect, even when you take into account Hofstadter’s law’.
Planning is a part of our lives. Some things are easy to plan, the consistent characteristic of these is that there are very few variables over which you do not have control. For example planning a trip to the supermarket, you can check what you need you control the time, the choice of supermarket, where you park, how you work the store, the choices you make between brands. Very few uncontrolled variables.
By contrast strategy is an exercise not just in predicting the future, but then making choices how best to deploy your resources in a way that enables you to shape the future to your benefit by exerting some influence over the range of variables over which you have no control.
Entirely different challenge, as there is never an explicit ‘right’ answer.
When we talk about strategic planning we are effectively mixing two incompatible factors. The uncertainty of the future and the forces over which we have no control, and the certainty of the resources we have to deploy, with uncertain outcomes.
Currently in this country we have a huge black hole called defence planning into which billions of taxpayers dollars are being poured, in the mistaken view that we are able to predict the future and therefore plan as if we could control the variables.
The better way is to have a robust strategy which enables flexibility in the way assets are deployed short term.
Projects tend to expand to fill a time available, while at the same time we habitually underestimate the time that is required to complete any given task, no matter how rigorous we are in the planning.
