“There have been a lot of advancements in metrics capture in recent years. What are the new metrics being used to support the ROI for a digital signage implementation?”
Metrics for ROI is not something so easily obtained. It is called the Holy Grail for a reason. If everyone can nail their ROI and maximize their investments, the marketing world would be the model of efficiency.
Unfortunately, people have been hunting for the Holy Grail for years. Even Monty Python had difficulties here …
So many factors come into play when determining ROI, or as people have been using more lately, KPI. First, you really need to define your KPI. What are you looking for? What are you trying to understand? Secondly, you need to set realistic goals on this. How will you read the results? How will you measure them? Are they truly from your marketing efforts? Third, you need to gather the correct data. What did you learn, and how did it tie into your end need?
All of this comes with the metrics you gather. So, how do we gather metrics to ensure you can capture points one through three above? It all has to do with the cell phone and other mobile GPS data. The latest and most comprehensive data source allows marketers to understand how consumers act after being exposed to your ad campaign. Yes, there are other ways to understand people’s behavioral activities outside of cell phones. Surveys have existed for years and continue to provide valuable information; contact someone pre-campaign, understand their needs, and understand their desires. Then, take that and match it up to a post campaign survey to see if their opinions and such changed.
But these surveys and models, always laborious, costly, and hard to define, needed a boost. The cell phone, mobile apps, and websites were born to do this. The very expensive and long-term market mix models have been used to determine ROI, but OOH including Digital OOH, is rarely properly reflected in these models. Some of that is due to the lack of very specific seasonal/hourly data needed for these models.
The current ROI market mix models don’t account for OOH because we have not been able to provide real-time data. We were so thrilled that we could at the very least provide GRPs/Impressions as most models are based on that. However, OOH is based on annual averages, and many models cannot or will not accept that.
The location-based data that exists in our industry (i.e. MORE) will give us the ability to provide the modelers with hourly data, which is critical for digital OOH. We can now actually pinpoint how many impressions were generated based on when the digital OOH spot ran. So we can at least be included in the models and show a level of sensitivity never before seen in OOH.
Mobile data allows us to get a larger sample pool. That data also allows us to be selective by providing the ability to hone in on a specific target or look-alike audience to be better aligned with our consumer. It also tracks us. Scary as it is, mobile data knows where we start, where we were and where we went.
With this data, we can start to paint the picture of our journey. We can see that a specific consumer (anonymous of course) saw or passed our digital screen, then went to our store or competitor’s store, and entered. We now have a measure of foot traffic in our targeted areas.
What happens after that is the missing piece. Do they make a purchase? Did they decide on something else? If they did make a purchase, was it because of our ad?
Without the ability to tie in a specific purchase to a specific consumer, this is still not a perfect science. But that part is on the horizon. With the advancement of cell phone payments (like Apple Pay), we can now track a specific device to a specific purchase and have the closing loop in our life cycle. It is the best way we can determine if our ad could have possibly created the sale outside of someone paying directly from the phone via a link or direct app.