"Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Mark Syal, joint managing director and director of media practice, EMEA, at Essence.
Averages can hide a multitude of sins.
As a media planner, you need to know that every dollar spent is invested in the most effective channel possible. If you only look at high-level performance, at least some of your budget is likely being spent where the marginal return is simply not good enough.
Even looking at the performance of each channel is not enough. Your ROI in search might seem fine on average, but the averages can hide what’s really going on.
For example, say your pure brand terms are driving many sales at $1 CPA, but your generics only drive a small number of sales at $100 CPA. If your break-even point is $50 CPA, why would you continue investing in generic search? The channel average performance would appear excellent, but a portion of the activity would not be cost effective.
If averages are insufficient and channel spend analysis lacking, marketers should focus on granular performance data when measuring performance media.
It all starts with sound planning.
First, you need a goal and to consider goal constraints. For example, the average performance needs to be at or just under goal, but it makes no sense to have any one line on the plan drastically above that target, even if it’s proposed as a test. Many brands will cap this at two times the goal cost per action (CPA).
To maximize profitable performance, there would ideally be no budget cap. You would spend up to the available profitable opportunity. But in reality there may be a budget cap that will constrain activity.
All previous performance data at hand would be needed. Hopefully it would reveal the channel or supplier of diminishing returns. If not, tests can establish this, starting with the most profitable channels or suppliers.
From there, it’s possible to create a waterfall plan. This has to be granular, down to placement by placement, with an estimated CPA or ROI by channel based on historic data, with any seasonality or estimates of other factors applied. It will also feature any new tests, with an estimated CPA.
I find it good practice to plan line by line until the CPA is some way above the maximum allowable CPA. That way, if the goal changes up or down, it’s very easy to replan by just moving the cut-off point up or down. Doing this will ensure that every next dollar is spent in the most effective place. There will be nowhere for averages to hide any ineffective spend.
This basic approach provides a great platform from which to manage media investment. But the digital world is steadily getting more complex, and any approach will need to take this complexity into account.
As suppliers develop their offerings and audiences expand, the level at which marketers can profitably invest in suppliers will increase. They will constantly need to test at higher spend levels to understand how the elasticity of those channels is evolving. In addition, new creative formats will perform differently and will respond differently at a variety of frequency levels. This also needs to be understood over time.
As we start to get more targeted with our digital activity, we need to constantly ask: Is that activity truly incremental? The ultimate in targeted activity is arguably remarketing. But were individuals going to purchase anyway, and which segments of our audience should we be retargeting? We can test for this using control and exposed A/B testing methodologies.
The industry itself has produced many unanswered questions. Should we look at viewable impressions only when we examine frequency? Is there even a useful definition of frequency for this? What if my customer’s path to purchase starts on mobile and follows via their laptop to a purchase in-store? Can I track any of that? Can I look at visible frequency of exposure across device, with cross-device attribution?
The answer is that you can, with the right tracking set up and for a portion of your sales and customers. As these issues are gradually resolved, so emerges a bright future for performance marketing.
My final point is about the complications that agencies and suppliers can add to the picture. Some agencies and suppliers complicate things by having less than transparent remuneration structures and pressures to deliver on agency deals from internal trading teams. This runs counter to the objectives of waterfall planning and can have an impact on effective performance media planning.
Closed suppliers also confuse the picture. Suppliers that mix targeting techniques in a less-than-transparent manner or aggregate different forms of RTB buying cannot supply data in a fashion that’s granular enough for the buyer to be certain that they are spending every dollar in the wisest, most incremental fashion possible.
Just like averages can hide the true picture, failing to have a full view of investment can damage the effectiveness of performance media.
It’s time to rise above the average.