Statistical modelling can provide an overall picture of how well a campaign is performing. It along with attribution modelling can reveal insight in the data to assist with future planning decisions.

Types of advert response.

There are three main types of respondents to an advert:

1. Direct Response

These are people who respond to the advert immediately upon viewing.

This could be via visiting the website or invoking a call to action that appeared on screen. The direct response can be measured accurately using Adalyser’s attribution models as it appears as a clear peak in the traffic. See Diagram 1.

Understanding the level of direct response in detail enables clients to identify inefficiencies in your media planning.

2. Indirect Response

An indirect response is someone who responds to the advert at some point in the future, at least 5 minutes after the advert has been shown. Perhaps they see the advert in the morning and make a mental note to visit the website in the evening.

Since the density of indirect response is much less than direct response, it is not directly measurable. Indirect response is indistinguishable from noise fluctuations in the baseline traffic.

3. Brand Response

These are people who saw one or more adverts but have no need to respond at this time. Due to repeated exposure they will recall the brand when they eventually respond. This also encompasses repeat customers who have seen adverts. This is a type of indirect response.

To get a complete picture of campaign performance we need to find the effect of indirect response in addition to the direct response. We need to look at the campaign from the top down rather than at the individual spot level.

This is where statistical modelling in Adalyser comes into play.

How to measure indirect response.

Adalyser has a suite of statistical models designed to simplify the rigorous data analysis required to measure indirect response.

Simply select a statistical model from Adalyser and a full report is generated containing campaign performance metrics.

The simplest way to determine the indirect response is to look at how many extra visits are generated on days with advertising spend compared to those with no spend.

Adalyser automatically fits the data and crunches the numbers to provide a detailed breakdown of the uplift generated. See Diagram 3.

What else can we infer?

Statistical modelling can be used for a variety of tasks not limited to:

1. Predicting future performance.

2. Spending efficiency cut-offs.

3. Spot type performance.

4. Day of week performance.

Adalyser

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