Norms answer the question: How is my campaign performing relative to similar campaigns? 

Upwave norms always include a mean and a confidence interval. In the example below, the norm for Recommendation Intent is +1.53%, with a confidence interval of +0.17% to +2.89%. 

There are (2) types of norms:

This norm accounts for seasonal effects. Campaigns that are run during a holiday season, or during a period of unrest, would not be expected to perform the same as campaigns run during other times. Real Time Norms control for seasonality. Upwave reports Real Time Norms for all Brand KPIs.

This norm also factors in attributes of your campaign or brand, in addition to seasonality. Currently, Real Time Plus Norms factor in the baseline level of your brand for each Brand KPI. For example, brands with low baseline levels of awareness are likely to be new entrants, and should expect higher average awareness lift than mature brands with over 80% baseline awareness. Real Time Plus Norms are available for most Brand KPIs.

Upwave currently factors in those drivers that, according to our data science team, appear to have the highest impact on the average expected lift of a campaign. Baseline levels, and seasonality, on average have a higher impact than industry category. Upwave may add industry in the future. In addition, industry selection has been found to be subjective for many brands, resulting in an arbitrary inclusion of "peer" brands and exclusion of all other brands, that increase the confidence interval of the norm. It's important to always ask for the confidence interval of the norm, as it is typically not included from other companies.

Yes. That's because the lift one should expect varies with seasonality. For example, a 4Q campaign should expect different lifts in each KPI before and after the holiday season.