Like all budgets, the marketing budget is a reflection of a plan — the marketing plan. And as we know, a plan is a priority task list which is based on forecasts of the key parameters.
In this case, the key parameters are:
How much to spend is a function of how much sales we want, while accounting for the competitor’s performance, as well as the volume of their ‘marketing noise (& to what extent we want to counter it!)
Where to spend must acknowledge the alternative options available, their cost, importance & efficiency. As also, which market(s) there’re opportunities / threats.
Given the huge volatility of the above parameters, it stands to reason that marketing budgets must be validated frequently!
Just like an engineering system constantly hunts for equilibrium,
so also a marketing budget must hunt for its right level
as frequently as possible.
From a corporate control angle, you must benchmark spends vis a vis your peers. And also track spends-as-a-percentage-of-revenue to compare with your category & industry. This could act as the first trigger for under- as well as over-spending.
The above approach must involve a multidisciplinary team of specialists from marketing, finance & specialists.
With this approach, the marketing budget can be built & regularly revised — including reallocation between brands & markets.
Execution Is As Important As Planning
A plan can only be as good as its implementation. And given the dynamic nature of the market, executing a marketing plan itself involves constant evaluation & planning at a micro level.
On completion, the plan is usually found to have undergone significant changes. Hence it needs rigorous monitoring prior to bill-passing. At one level, it’s monitoring which highlights a lot of discrepancies, which yields real savings. (Not enough can be said about the cost-saving effects of monitoring in passing advertising & marketing bills.)
At another level, plan performance is dissected to learn from each plan execution in an exercise generally referred to as post-implementation evaluation or ‘post eval’.
Given that plans cut across multiple markets, regional offices, budget heads & myriad activities, all this is far from easy.
Marketing Data Visibility
It’s essential to review marketing budgets vis a vis performance. And the competition will continue to innovate — both product as well as marketing — so it’s best to keep a close watch using syndicated competitive intelligence. Regular reviews of marketing performance, ROI & the competition is mandatory to increase or decrease spends.
If ‘post eval’ is the micro-component of ‘hunting for equilibrium’ in marketing budgets & plans, then regular review is the macro component.
Both need free flow of data. ‘Post eval’ is currently executed in a somewhat ‘painful’ manner because plan data is usually scattered over multiple spreadsheets. The second is also done infrequently because marketing data is notorious for being ‘invisible’ to the C Suite!
To achieve this, it’s mandatory to make your marketing data more ‘visible’, which by the way is notorious for being practically invisible to the C-Suite!
Merge The Data Silos
One of the obvious reasons behind ‘invisible marketing data’ is the existence & promotion of data silos! Take plan data which lies scattered in individual spreadsheets — these must typically be aggregated from individual spreadsheets to a central sheet before processing for reporting.
Analytics : Frequency vs Accuracy
Marketing data along with sales & other data must be rendered on real time dashboards which are designed to promote analysis & review by the multidisciplinary team of marketing, finance professionals along with specialists.
Use analytics to recalibrate your marketing spends.
The above exercise is just the starting point and needs to be refined with regular analysis of market trends, forecasts & deep business insights for accurate budgeting. (This actually means managing flexible marketing plans which change with the latest insights — on a regular basis.)
This is why analytics exercises must update models every few weeks to help confirm trends & re-chart the course. A lower accuracy is acceptable when the frequency is high.
This also includes building attribution models in the short term for assessing impact of various media, promotions & other factors. The basic idea is to use data sources quickly to test if they exhibit any significant divergence from current understanding.
Need for Ready Data
Assessments & insights may not be perfect, but speed is of the essence.
To get speedy insights on a sustainable basis, clean data must be readily available without much ‘struggle’.