Amplify Out-of-Home | Reporting and Analysis

Overview

There are a number of different comparisons and decisions people want to make when pre-testing ads. Most brands need at least some media support, so ‘using nothing’ is often not an option.

There are two ways to analyze your Out-of-Home ad. You can compare against a norm, which is the default view for any chart, or you can compare to another ad.

Compare to the norm:

• Is this ad strong enough for good ROI?
• Is the ad good or great?

Compare to other ads:

• Which executions or creative routes are strongest?
• Is this new ad stronger than the most recent advertising I’ve invested in? Is this new ad stronger than my competitor’s ad?
• Which iteration of the ad is strongest? (recommended for meaningful differences between creative, not small iterations).

Quick Reports^AI

Amplify TV supports Quick Reports^AI. Automated reporting is generated upon the completion of a survey which provides a concise summary of results and reasons. It’s produced by combining human expertise in response interpretation and diagnosing consumer responses from your survey with AI. 

Select one or more projects, then click ‘Generate Report’ to get a clean, editable analysis of your data. Learn more about Quick Reports^AI.

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To compare two or more concepts

From the Analysis section, select two or more concepts to compare. You can only compare concepts tested in the same market.

Click ‘view analysis’. Select the Expanded Metrics at a Glance chart.

Charts default to comparing to the norm. To compare the concepts to each other, go to the configuration settings on the right and under ‘Significance Testing’ select ‘Stimuli’

The concept to concept comparison significance test shows differences between all the stimuli on each measure. 

• Where a measure for a specific concept is significantly above another concept, the color is bolded to draw attention to this strength.
• In place of showing the norm under the achieved score, there is a letter which denotes which column this concept is stronger than (for example it says B, it means the concept in this column is stronger than the concept in column B). 
• For sales/brand impact, you will still see the percentile score for each concept but we are using the absolute sales/brand impact score (from which the percentile is calculated) to inform whether one concept is significantly above another on the summary metric.

Learn more about making decisions with Amplify.

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Understanding metrics that matter

Reporting deliverables focus on the “Metrics that matter” to drive short-term “Sales Impact” and long-term “Brand Impact”. Based on performance on these metrics, users are guided to the linked diagnostic sections of the report to better understand how they can improve their ads.

Learn more about Brand and Sales Impact.

Cultural Sensitivity Question

You can choose to add the Cultural Sensitivity question during configuration. This can give you some insight into how consumers view your product or idea, and allows you to catch any issues before you go to market.

Learn more about the Cultural Sensitivity Question and how to interpret the results.

Creative potential

The Creative Potential Score is a summary measure which looks holistically at the potential of the idea to be translated into a successful finished execution. It summarises whether the idea has potential to:

• Reach people by breaking through the clutter and bringing the brand to mind
• Resonate to hold attention, be relevant, relatable and make people feel good
• Create a response by making people more likely to consider and feel good about the brand.

Learn more about the Creative Potential score and how it’s calculated.

Audience and sample

What is our approach to sample? Who are we interviewing? 

We interview a Representative Audience that reflects the real market for your category. Having Profiles (subgroup norm) analysis available means that we are able to check resonance with narrower audiences, but defaulting reporting to category consumers/users ensures that we are both benchmarking consistently, and providing a high threshold for creating great advertising.

While other testing approaches allow a user to configure a sample each time and database everything together, Zappi Amplify applies a standard approach to sample, based upon consistent quotas and broad category relevant sampling. This consistent sample means: 

1. Any category will find its target audience in a dataset and understand a broad consumer reaction.

2. Any test can be compared, confidently, to any other test at a total population and sub-group level.

   
   

How do we ensure the sample composition of each test is comparable?

We apply several different weights to our data to ensure consistency across studies. The weighting reflects the actual makeup of the relevant country so the sample remains consistent.

Sampling:

Data for Amplify OOH is collected with sample targets set for age nested within gender, and socio-economic class (SEC).

For age and gender we ensure that within each age group there is a 50/50 M/F split based upon census data. 

Weighting:

Weighting is applied on four axes: Age nested within gender, socio-economic class, brand usage, and category usage.

The targets for category and brand usage are calculated dynamically based on a norm:

• Category usage targets are calculated independently and across different customers for each category within a country. A norm is created for each usage frequency response option for all cells in the database.
• Brand usage targets are also calculated independently, In this case for each brand within a country/category combination. A norm is then created for each usage frequency response option for all cells in the database.

Our sampling and weighting approach means that every comparable project has the exact same weighted fallout of each of our 5 variables: Age, gender, SEC, Category Usage, Brand Usage.

Norms and interpretation

What is a percentile?

A percentile score is a method of ranking that takes the score for an ad, and reports back where the results for that ad sit within the total distribution of the norm that it is being compared to. For example a score in the 70th percentile suggests that the ad has performed in the top 30% of ad scores.

The norm that is being used is an important part of this calculation, and changing the norm will change the percentile scores.  An ad may be in the 50th percentile when looking at all ads in the market but in the 99th percentile when looking at ads for a specific category. 

At Zappi, we perform a specific type of norms calculation that smooths out the database and removes any skews. We take the mean and the standard deviation of the norm, and use them to create a normative database that follows a normal distribution. Each ad’s performance is then plotted against this distribution. This is known as a cumulative distribution function.

Norms 

Definitions for norms:

1. Country level - Ads can be compared to the norm for the country in which it was tested.
2. Language - The language that the fieldwork for the ad was done in. This can be different from the language of the ad itself, since you can test an English ad with Spanish-speaking respondents. 

3. Parent Category - The vertical or industry the brand is from (ie. fast food company would go in the restaurant parent category). This norm includes the data from all our other Zappi customers in the category. 

4. Child Category - This norm will encompass all the ads tested within the narrower category. For example, within beverages the children categories would be.

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