Charting the budget course in stormy weather
Opinion
The way budgets are set needs to reflect the turbulent times marketing finds itself in. Old tools are no longer equipped to do the job.
One of the more challenging questions asked by a client of their media agency planning team is the one that begins: “We need to review how much we spend against how much you think we should spend…”
It lays bare a number of agency shortcomings.
First, the lack of a relationship between the agency and the client’s finance director (FD), which is where the majority of any budget decision sits.
Secondly, the narrowness of the agency’s expertise, focused as it must be on the issue of how different channels work on consumers.
Back in the last century, Carat produced something called The Carat Sphere Guide, subtitled The Way We Work. This contained details on Carat’s tools and how to access and use them.
Reliance on output
One of Carat’s tools was called Budget Bearings, created by Carat UK’s resident genius Phil Gullen. The idea was to gather as many pieces of information relevant to the task of budget-setting as possible and plot them within the tool.
The more information or points of reference, the better. The more bearings you took, the more accurate the plotting of your position.
Budget Bearings relied primarily on output measures, calculated from available data.
It was a brilliant idea from a time when marketing — and, within that, advertising — was seen as a short-term cost with few, if any, long-term business success metrics attached to it.
Investment, not a cost
Things have moved on. Slowly, and unevenly, but changes are afoot.
The analyst Ian Whittaker makes the point that big companies in their earnings statements and calls with analysts are increasingly saying: “We believe in the ability of brands to build business, to grow revenue and profit.”
In other words, building brands through marketing and advertising is an investment, not a cost.
This shift from cost to investment should be reflected in the way budgets are set. Focusing on what others are doing, or setting budgets around a task like achieving a certain level of reach, is no longer good enough.
When paid-for and measured media forms are taking a smaller and smaller share of the cake, basing any financial recommendation around concepts the industry either does not measure or can’t define makes no sense.
To persuade the FD, we need to learn FD-speak, and to be precise and consistent. FDs are unaware of the metrics used within planning and buying. They’re a currency; nothing to do with business.
We buy audiences because of the correlation between how many people sees the advertising and financial results.
But the numbers are neither reliable nor accurate. We can’t even agree among ourselves.
A new kind of modelling
We should use modelling, taking in all communication channels. Marketing budgets are larger than ad budgets and there is an upside in modelling effect.
My Crater Lake colleague and co-founder of the analytics business Navigation ME, David Beaton, makes the point that, in over 20 years building brand models, most underspend against their market opportunity.
He believes this is because of a lack of reliable, accurate, consistent tools not only to measure this underspend, but also to predict and optimise the effect of any increases.
Many econometric and marketing mix models limit themselves to attempting to explain paid-for as opposed to all communication forms.
Plus, most only look backwards, using limited inputs. Most don’t consider consumer research data, as if how consumers think has no impact on what they eventually do.
A how-to guide
Here’s David’s advice to anyone considering modelling to justify budgets.
Build models that cover a holistic list of factors that drive or suppress sales. Not only paid media, but also earned and owned; and baseline factors that are important to the category and brand.
Insist that any statistical model can demonstrate accuracy. Aim to explain over 90% of variation in sales over the last three years. This will help persuade the CEO and FD, and reduce the risk of misattribution and poor outcomes.
The model must be able to use optimisation and simulation to estimate the gains to be had from budget increases. These models typically yield a diminishing return curve; as spend increases, incremental sales lift falls.
At some point, any further spend increase yields no sales increase at all — this is where marginal benefit equals marginal cost. Given the current situation, this is the maximum level of sales that marketing communications can drive.
This is not the same as “maximising marketing return on investment” (ROI). In optimised campaigns, marketing ROI falls as spend increases, so “maximum ROI” happens at low spend levels; chasing marketing ROI leads to undesirable cuts in budget.
Combine both prediction and optimisation at different spend levels. This is because, as spend increases, the channel mix should change, as different channels have different effect curves.
Test alternatives. Work your way up the spend curve over time; controlling for both your own spend risk and factoring in likely competitor reaction.
Specialists required
Agencies (and their holding companies) like to believe they can do anything related to comms. But this isn’t true when it comes to building complex models.
An advertising-centric group will always see advertising as the solution to any question. If you call in a plumber, he’ll find you a leak.
They cannot be considered unbiased. Agencies aren’t keen on models that demonstrate that their recommended channel mix failed to deliver a desired outcome.
Modelling is a specialist area. Just as ad creation is best done by creatives, modelling budget scenarios needs specialists.
When all anyone had was output data, the agency could plot the position.
Now we have storms, choppy seas and an under-equipped boat. It’s not the weather to be out with amateurs.
Brian Jacobs is founder of Crater Lake and BJ&A. He has spent over 35 years in advertising, media and research agencies including Leo Burnett, Carat and UM.