Due to the COVID-19 pandemic, we saw dramatic changes to in-store visitation this past year. It was also a time of transition for Cuebiq as companies across all industries were compelled to pivot their strategies and find new opportunities for growth.
In developing our 2022 Attribution Benchmarks report, we reviewed the past few years and produced benchmarks that mitigate the impact of COVID-19 by taking a longer view. Despite an unusual few years, our benchmarks can be used to inform decisions and measure campaign effectiveness against others in your industry.
Now more than ever, location data and attribution metrics are essential to evaluating the success of your campaigns. Using these tools, you can understand actual consumer actions, tie them to ad exposure, and utilize those insights to fuel your strategies moving forward in a post-pandemic world.
Metrics for Attribution Benchmarks
Here are the key metrics you need to know for understanding attribution benchmarks:
- Brand uplift — the impact of ad exposure in driving visits to store; the ratio of visitation between exposed and unexposed groups
- Visit rate — identifies the percentage of customers who visited the store of all exposed customers
Use Case Examples
Our report pinpoints the average range for brand uplift and visit rate across 18 different industries. Therefore, if your visit rate is higher than the average for your industry, you can conclude that your campaign has performed exceptionally well. For example, if you are a brand marketer at Chipotle and your visit rate for a buy-one-get-one-free burrito campaign is 4%, which is well above the QSR industry average of 2.04–3.51%, your campaign is successfully driving customers to store. This could be because you targeted the right audience or because your ad caught them at the right time of day.
The same goes for other industries, such as big-box retailers like Walmart. If you are the brand marketer at Walmart and your visit rate is under 0.5%, so below the industry average of 0.51-0.61%, this indicates that you should adjust your campaign. For example, you could be neglecting to target young parents in your back-to-school campaign or you could be running ads on a platform with the wrong age demographic.
Equipped with this information, you can then upgrade your campaign by customizing your queries, which will allow you to learn more about your customers and make your campaign more applicable to your respective use cases.
For more insights, be sure to check out the full Attribution Benchmarks report.