When it comes to forecasting campaign ROI, how do you avoid misplaced optimism?
Here’s the rub.
As a marketer, you’re now under more pressure than ever to prove your worth – and demonstrate ROI.
Your budget is under scrutiny – and no doubt, you need to put forward a strong case to justify your spend.
So what do you do?
Be bullish about the potential return – ever optimistic about your ability to deliver the goods, but knowing it’s the only way you’ll get go-ahead.
Or take a more bearish approach – assuming a more grounded, perhaps pessimistic view (clearly with the aim of exceeding expectations) - but at the same time, risking the powers that be pulling the plug on your grand plans.
Well, at a guess, we’d probably say you’re predisposed to be more bull than bear.
It’s something psychologist Daniel Kahneham in his fine and highly recommended book ‘Thinking, Fast and Slow’ describes as the ‘Planning Fallacy’.
When it comes to forecasting, he argues misplaced optimism pervades.
One of the examples he cites is a study examining rail projects undertaken worldwide over a 30 year period: In more than 90% of the cases, the number of passengers projected to use the system was over-estimated. And despite these shortfalls being widely publicised – forecasts simply did not improve. In fact, planners over-estimated passenger numbers by 106%.
The Planning Fallacy is about making plans and forecasts that are based on the information we have in front of us (at best) – and failing to allow for the ‘unknown unknowns’. It’s about us tending to unrealistically base our forecasts on the best-case scenario.
So what’s the cure?
While we can’t foresee the unknowns, Kahneham argues that to overcome the Planning Fallacy and improve our forecasts, we need to consult the statistics of similar cases – where possible referring to distributional information. He calls this the outside view.
In simple terms:
i) Identify your reference class (Earnest view: business-to-business reference classes will clearly provide a better reference point than B2C if you’re in the B2B game)
ii) Obtain the statistics of the reference class to provide a base line prediction (Earnest view: okay, can be tricky to come by but there are more and more B2B benchmarking studies available)
iii) Use specific information about your project to adjust your baseline prediction (Earnest view: look at the variables you’re playing with, what you’ve learned from previous campaigns and in particular what you don’t know – for instance, if you’re using a new unproven data set – then err on the side of caution and adjust your predictions downwards).
Adopt this approach and chances are your forecasts will be more accurate and less risky, but ultimately it’s over to you to determine how you set the expectations of your stakeholders.
However, continuing to over-promise and under-deliver can only prove more damaging for your reputation within the organisation.
We’d argue the case for realism.
Some campaigns will no doubt deliver way above forecast, some less so. But by demonstrating more rigour in your planning – and building the confidence of stakeholders by delivering on your promises – the more marketing will show its worth and gain the respect it truly deserves.
CC Image courtesy of sunnyUK on Flickr.