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A new year, a new set of targets. Depending on how things went you’ve either given you and your team a slap on the back or a regroup and teamtalk about things will be different this year. The level of sophistication between setting targets differs wildly from business to business but it doesn’t necessarily track that larger businesses will be more complex. The complexity tends to depend on how involved the marketers are in setting the targets, the more they’re involved, the more nuance generally can be applied.
One defining factor that separates businesses, is whether those targets are dictated bottom-up or top-down. That is to say, is it historical market performance influencing targets, or is it a leadership team/board/investor group? There’s bound to be a little overlap, but most businesses will be rooted more in one than the other and it can have a big impact on the specific nature of the challenge facing the respective marketing teams.
Bottom-Up Targets
Chances are you’re not in an aggressive growth mode. The first stop for your targets is an analysis of the previous 12 months. If it’s an involved process it’ll involve a significant deep-dive into search impression share and identifying where opportunities exist in-platform. With some luck those enhanced targets will come with a larger budget, if you’re unlucky you’ll be set the challenge of “making the existing budget work harder”.
Either way you’ll need to be able to confidently forecast what additional budget (or improvements in performance) will return as results. Ideally you’ll be able to incrementally increase budgets and maintain your ROAS – but often that’s not the case. It’s important to factor the inevitable diminishing returns as you increase spend across your existing platforms so you can see how far they’ll go before you need to consider additional platforms.
As soon as you’ve exhausted what’s reasonable in terms of expectation from your current platforms the question of which additional platforms to add can be vexing. Without historical performance you can’t be certain what to base your expected returns on. Utilizing industry relevant benchmarks will be crucial here. As soon as you move outside of the highest intent platforms/tactics it becomes a question of whether you can find and leverage a positive ROAS or if the evaluation of your new platforms will have to be based on the improvement to the performance of your existing platforms.
Top-down Targets
Whether this is presented as an annual revenue number to hit or just a monthly X% lift on performance from the previous year, this top-down targeting is often informed by growth targets or investor demands. Often these targets will push beyond anything that can be achieved exclusively with incremental increases in existing budgets.
Very quickly the conversation shifts to one of modeling. What are the opportunities available within existing platforms? How far can we move into projected diminishing returns and still be comfortable with the invest to return ratio? Where are there opportunities to just lift performance? What are the new platforms that could contribute? And, once high intent (and easy positive ROI) platforms/campaign types have been exhausted, where are the areas of expansion?
The challenge with modeling in this way is accurately guessing at the kinds of results net new platforms and/or campaign types will bring. This is where a good benchmarking tool is crucial. Get good insights into a) where other people are investing, and b) what kind of results others in your industry are getting.
Regardless of how your targets are being set, it is important to seek out the data that will help you make accurate estimates. The data is out there and without it you’ll just be putting a finger in the air. While forecasts and benchmarks won’t be able to predict your specific experience exactly, it could well be the difference of a few percentage points of accuracy. When that kind of margin is extrapolated over an entire year – with an entire year’s budget – being that much closer in your estimates will make a substantial difference.