Most marketers agree measurement is crucial to understanding and optimizing digital advertising.
Fortunately, a variety of measurement tools exist to help advertisers understand the quality of their content, the impact to brand awareness, and the efficiency of their execution.
There also are tools to help verify the return on investment (ROI)—and hopefully provide some insight into what worked and what didn’t to inform the next campaign.
However, when offline sales are the KPI, marketers often wait weeks or months after their digital campaign ends to gain insight into performance.
By that time, brand teams have moved on to the next season or year of planning. New strategies are in place. Platforms have changed, and the learnings might not feel relevant any more.
To optimize the media before the entire campaign budget is spent, marketers often have to rely on online KPIs as proxies for business results. This is where inflight measurement comes in.
Inflight measurement tied to offline sales is becoming available in the industry and will play an increasingly large role in digital measurement going forward.
The use case for inflight measurement is different from end-of-campaign evaluation. It’s less about understanding exact return on investment (ROI) and more about evaluating the levers within the campaign.
For most campaigns, the core strategy, activation channels, and creative content cannot be changed on a whim.
Rather than evaluating the overall success or failure of this strategy based on early indicators, advertisers should instead focus on what they can change and make the most of what they have.
For these use cases, the measurement needed is not the exact incremental sales during the first few weeks of the campaign, but a gauge of which tactics are driving results and which are not.
It’s also important to know to what degree that performance differs, so any variations in media cost can be considered before action is taken.
Being able to act on these signals requires organizational buy-in. If decisions can’t be made quickly, the value is lost. Here are some tactical steps to have in place to remain nimble.
Let’s look at a two examples of CPG campaigns measured by Oracle Data Cloud where end-of-campaign ROI revealed certain tactics performing better than others.
Then let’s consider what could have happened if those insights were known when the campaign was only 50 percent complete and optimizations could be made.
The ROI report showed Audience B drove the strongest RPM (incremental sales per 1,000 impressions), but had the lowest allocation of impressions.
Audiences C and D received nearly 50 percent of the campaign impressions, but were the lowest performers.
If we assume Audience B is large enough that incremental reach is possible, and the impressions allocated to Audiences C and D in the second half of the campaign switched to Audience B, this campaign may have realized an estimated 77% increase in incremental sales*.
This campaign tested generic vs. personalized creative, with equal budget allocation to each. Though both drove penetration lift, the personalized creative drove stronger penetration results and also drove sales lift.
Had the advertiser shifted to 100 percent personalized creative halfway through the campaign and continued to see that level of sales lift, the total incremental sales could have increased up to 57 percent**.
*Assumes 24.5 percent of campaign impressions originally allocated to Audiences C and D could achieve the same RPM observed for Audience B as a result of mid-campaign reallocation.
**Assumes 50 percent of the household reach from generic creative realized the same lift performance as personalized creative as a result of changing the creative content mid-campaign to be 100 percent personalized.
The days of test-and-learn media strategies dragging out for months, or even years, will soon be behind us.
While using insights from one campaign to advise the execution of future campaigns is certainly valuable, it doesn’t compare to using that same measurement to optimize the media being measured before it concludes.
Oracle Data Cloud is excited to join you on this journey to measure media faster, optimize toward what’s working, and ultimately deliver better business results.
About Beth Evenson
Beth leads CPG Measurement Strategy for Oracle Data Cloud and is focused on bringing fast, reliable, and actionable digital measurement solutions to advertisers.
She earned her B.S. from University of Minnesota and was a part of Oracle’s (formerly Datalogix) Data Science team prior to taking on product strategy.