Jun 25, 2020 | Branding, Communication, Customers
Kids understand stories, it is the way they learn, the way they absorb the lessons of the past for later use.
Why don’t we use this instinctive capability more often in our marketing?
Take your kids to the pantomime, they love it.
They get excited every time the villain comes on stage. They boo, yell warnings to the hero, and hop up and down in frustration when the hero looks around as the villain hides.
Why does this matter?
When building a brand, you have to make choices. Who is your brand for, and just as importantly, who is it not for?
If you can explicitly state who your brand is not for, then those for whom it is for, will rally around and support it against the villain.
Simple stuff, hidden in the instinctive responses in our brains.
Watch your kids at the panto, and learn how to build a brand.
Define the villain, and the kids will cheer for you.
Jun 22, 2020 | Analytics, Customers, Marketing
One of the questions occupying my newly monastic mind over the past few weeks has been: ‘what changes can we expect in the revenue generation processes as a result of the ‘Bug?’.
In the lead up to this crisis, I have been considering how automated everything was becoming, at the expense of humanity.
There is an inherent conflict between the centralising force that is the ‘Martech’ (marketing technology) automated decision making processes, and the front line sales function. Martech investment requires that a range of decisions to buy and install various combinations of software be made that automates a selling relationship. The decentralised nature of the sales front line does not benefit from such automation, as people still prefer to buy from people, particularly in cases where the investment is large, or there is an emotional element to the purchase.
To my mind, it has become too clinical and automated in most large businesses. This creates opportunities for smaller businesses whose niche is perhaps more clearly defined, and who lack the resources and capability to leverage an integrated ‘Martech stack’.
The Bug has brought the question to the fore.
On one hand, we are now compelled by circumstances to interact using the digital tools, but there is a steep learning curve for many, and SME’s are rapidly discovering their capability shortcomings. On the other, human contact will become more valuable than ever, and those same SME’s may be in a better position than most large companies to be ‘Human’.
Where on the scale does your business fit?
Jun 19, 2020 | Marketing, Strategy
‘The bug’ has given us a once in a generation opportunity to make change. Things that may not have been possible, have suddenly become not just possible, but necessary.
While most of the focus is automatically on cutting costs, the greater long term benefit is in the optimising of current expenditure. Arbitrarily cutting costs, as often happens in extreme circumstances, always results in throwing out a few babies with the bathwater.
Revenue generation, the combination of sales and marketing budgets, is usually the first to feel the knife when times get tough.
However rather than just ‘cutting’ across the board, or making the obvious decisions by cutting the biggest items first, consider the opportunity to optimise, and how this will deliver cost savings. More importantly, such an exercise can increase the productivity and long term impact of the investments you make, as well as reducing costs.
Classifying all expenditure into ‘buckets’ so that you can then allocate a weight to their relative value, and concentrate on those from which you can extract productivity increases, is a sensible first step.
All expenses can be classified in two major axes:
- Fixed to variable or discretionary expenses. Those that are not able to be reduced or improved, to the extreme of expenses which are entirely discretionary, such as media spend.
- The second axis is tactical to strategic. The short term expenditure which can reasonably be expected to deliver a return in a very short term, to the other end of the scale, the strategic expenditures which are normally those that appear to be in the ‘important but not urgent’ pile.
The manner in which you go about optimising your expenditure will be a function of your competitive context, the financial and strategic position you are in, and the strategic priorities in place. It will also reflect the attitude of the person delivering the instructions. Therefore, it is also a measure of your effectiveness at arguing the role that investment in marketing has to the health of the enterprise.
Your fixed marketing costs are items like employee costs, marketing software licences, retainers paid to service providers, and are often overlooked, or just cut arbitrarily. In the absence of a critical review, mistakes will be made.
Discretionary costs are often heavily weighted towards media, and they are very easy to cut. This will deliver a short term cost saving while often compromising the commercial sustainability of the enterprise.
History shows us that those who continue investing thoughtfully in the tough times, benefit hugely as the better times return.
When instructed to cut costs, do so with an intensive focus on the relative revenue and margin generating productivity of the cost you are about to cut, and to the long term impact that will have on the enterprise.
Jun 15, 2020 | Management, Operations
Metrics at their best deliver game changing insight and wisdom. At their worst, they are misleading , irrelevant and a pain in the arse to collect.
So, what are the two characteristics that make a great metric?
The metric is a leading indicator.
A Leading indicator is a reliable measure of what will happen.
For example, if you have the data that shows that for every lead you generate, you convert 5% at an average purchase price of $50, and those customers buy twice a year for an average lifetime of 3 years, you can calculate with some confidence what each lead is worth to you. In this case, it would be: 100 leads X 5% X $50 X twice a year X 3 years = $1500.
The metric is causal.
The most common mistake I see, is metrics that confuse cause with correlation. There are many things that correlate, despite the fact that there is no relationship between them. One does not cause the other.
For example, there is a correlation between ice cream sales and drownings, which on a graph looks identical, but there is no causation between the two. Look deeper, and you might see that on sunny days, more people eat ice cream, and more people also go to the beach, swim, and therefore risk drowning. There is also a close correlation between ice cream consumption and a shark attack. This second correlation would also suffer from very ‘thin’ data, which make any sort of causal relationship even further from the truth. However, a glance at a graph, which takes on some credibility as someone has actually created a graph, would suggest there is some causation.
For a metric to be of any real use, it has to be the catalyst that changes behaviour, and delivers a predictable result. It is not always easy to sort the causal from the correlative. When you need some experienced wisdom, give me a call.
Jun 12, 2020 | Governance, Management
Preparing forecasts is an integral part of most jobs these days, even if it is just how much available capacity there might be on the machine tomorrow, and how best to fill it.
Most forecasting I see is based on the financials, and is one of two methods: The ‘spreadsheet method’, where 4.5% is added across the board, and bingo, a forecast. Easy. The second method is driven by numbers of a different sort: the Net Present Value equation, the present discounted value of forecast future cash flow, which is more often than not driven by spreadsheets with hurdles imposed.
Neither is much good by themselves.
More recently, a range of pretty sophisticated modelling tools have become generally and cheaply available, which despite their sophistication, still have to be fed data and assumptions to spit out an answer.
Effective forecasting takes in a range of qualitative factors, some of which can be massaged into the algorithms, with the caveat that they then have some sort of relative weight applied.
- A realistic assessment of the resources required to reach an objective. Of increasing importance in this calculation are the capabilities of the people required to deliver the outcome.
- An assessment of the strategic, competitive and regulatory environment in which the forecast lives. Generating forecasts without due consideration of a range of factors external to the business, over which they have little if any control, becomes little more than wishful thinking.
- An assessment of the impact the successful initiatives will have on the external environment, particularly competitors. I see way too many forecasts that ignore the simple fact that competitors will not sit still while you eat their lunch. Failure to adequately anticipate and accommodate their reactions in the tactics to be deployed, and their forecast outcomes, is just plain dumb.
- A continuous and rolling After Action Review process. This process ensures the impact of tactical actions can be assessed, and the lessons applied to following forecasts. A forecast should be a ‘living’ document, something that accommodates, adjusts and builds on the facts and changing circumstances as they emerge.
Back in the day when I ran large marketing departments, forecasting was a key part of any project plan. When product managers came to me with their forecasts, I was not so much concerned with the numbers, as I was with the assumptions included and the relative weights of those assumptions. I also insisted that any forecast had three components, a best case, worst case, and forecast case, prepared separately, with different weights allocated to the variables. This gave us a range with which to work, and importantly, ensured some thought had been put into the implications of the ‘pear-shaped’ outcome.
The disturbing thing was always how inaccurate our forecasts were, no matter how hard we worked. This does not mean we did not try hard enough, simply that telling the future is a challenging task, not to be undertaken lightly.
Once again, my thanks for the header to Scott Adams and Dilbert.
