Published on September 22nd, 2016 | by Stephen Freitas0
Understand How ROI Models Interpret OOH Contributions
At the beginning of this year, OAAA conducted surveys and interviews with hundreds of members. We wanted to gage the collective viewpoint of stakeholders on the greatest opportunities and threats facing the OOH industry. A recurring topic consistent among the membership was the need to better define OOH return on investment (ROI) measures.
To address the need, OAAA has created an ROI committee. The group is currently working on a plan to educate the industry about ROI multi-mix models (what they are and how they work), learn about model inputs and the outputs they generate for OOH, and understand the limitations of some models in the evaluation of OOH.
The committee investigation has uncovered several factors that impact how OOH is represented in some media mix models.
- OOH doesn’t have established ROI benchmarks to be used as inputs for third-party optimizer platforms.
- OOH ratings and impressions are currently annualized, and ROI models require discrete weekly inputs.
- OOH is more than what is measured and includes cinema, place-based media, and more, so the very definition of what is going into the model is not clear.
- Normalization is a big challenge that involves determining how to convert OOH measures into CPM’s when OOH is often a small part of national ad campaigns.
- Optimizers were built to evaluate TV campaigns and are national in scope, but OOH generates a higher percentage of local ad spend.
- OOH spend is typically smaller compared to a national TV buy, so the overall impact OOH contributes is smaller in comparison to an overall national ROI analysis.
- There is often confusion about the terms attribution and ROI, with attribution being the impact from one medium in a mix that leads to assumptions about ROI and future investments. OOH is often put into models inaccurately, because there is no clear understanding about how to correctly use its data. (Ratings are not necessarily accepted ROI inputs since they do not provide attribution).
While there are many challenges to address, the ROI committee is formulating a plan that could better integrate OOH measures into media mix optimizers.
- Use mobile to measure OOH impact the same way Nielsen uses mobile panels to measure TV exposure.
- Use spot fill for local ROI models in an approach similar to spot TV.
- By providing weekly data, Project MORE will solve some of the problems related to national vs. local inputs.
- Use foot traffic lift to provide another metric beyond sales.
- Establish which cross-media KPIs the OOH industry should address.
- Identify guidelines all stakeholders can agree on as rules, and then begin to standardize inputs (or benchmarks).
- Convince the biggest brands to put pressure on modeling partners to recalibrate platforms for OOH.
Educating the industry about ROI is important. The committee has a plan:
- Work with modelers to determine what the OOH industry could do to help improve model outcomes.
- Update the 2012 OAAA ROI study conducted by Brandscience, and include local market information and channel-specific data.
- Host a workshop and produce supporting collateral that informs OOH media company account executives and others about OOH ROI and how to overcome doubts.
- Address how to collectively tell the “ROI story” as an industry.
- Collect and package best practices in a standardized format.
- Present OOH ROI case studies at ad industry events attended by major brands.
The ROI committee will continue to develop plans for improving the way OOH is represented with media mix models. If you have good examples to share, please let me know. You can reach me at firstname.lastname@example.org or at 202-833-5566.