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Audience Segmentation

Everything about Audience Segmentation


What is audience segmentation?

Audience segmentation is simply the process of dividing people into meaningful and manageable groups – or segments – so that products and services, as well as communication efforts, are designed and tailored to satisfy the targeted groups. Audience segmentation assumes that different groups of audiences have different needs and characteristics that influence the extent to which they pay attention to, understand and act on different messages. By segmenting the audience in this way, a brand can get a clearer understanding of who it needs to target and how.

In general, audience segmentation works in the following way:
A car company might segment people based on their age so that it can offer certain deals to new drivers. A retail company might segment people based on their past purchases so that it can tailor deals based on their past purchasing behavior.

How to do audience segmentation

Audience segmentation relies on developing criteria that can be used to form a segment. The criteria could be based on information such as: whether someone is a male or female, how old the person is, and his or her permanent address. Essentially, it is a process of grouping people based on a combination of shared characteristics. Below are the many ways audiences can be segmented.

Demographic segmentation
– Age
– Gender
– Education level
– Income

Geographic segmentation
– Place where people live
– Place where people work

Psychographics segmentation
– Attitudes
– Aspirations
– Values

Behavioral segmentation
– Purchasing habits
– Usage habits (product or services)
– Spending habits (time, money, and other resources)
– Benefits sought

Getting information for audience segmentation

Consumer insights are needed for audience segmentation. Information can be collected through primary audience surveys or from external secondary sources. In the digital signage and retail industries, advertisers can harness the power of real-time audience analytics to get a better understanding of the customer. By integrating analytics to digital signage, businesses can get a more detailed look into the individuals who come into contact with the displays. Analytics, processed through face analysis technology for instance, can capture human faces and recognize demographic information such as age, gender and emotions. Other contextual information captured as insight through face analysis include people counting, time, location, weather etc.

Why audience segmentation

There are many benefits to dividing people into meaningful segments and coming up with a targeted audience for digital signage.

Segmentation ensures that content has value:
For content to be target and have value, advertisers need to know which audience segment is consuming it. When the segment is known, ads or messages can be optimized and personalized to audience preferences.

Segmentation Ensures That Your Content Is Relevant
By knowing and understanding the targeted segment, messages can be delivered directly to the consumer in a manner that is comfortable and unobtrusive. For a message to be relevant, it needs to relate to the consumer’s interest and be part of the consumer’s “lifestyle”.

Segmentation Ensures That You Don’t Waste Your Resources
Through audience segmentation, resources can be applied more effectively. By having a clearly defined audience, advertisers can reach out directly to a particular demographic or niche, which means that less of the marketing budget is spent on trying to attract and convince people to buy, and more of it used in transforming visitors into customers.

Audience Segmentation is all about defining the target audience. By breaking the audience down into smaller groups, businesses can build a stronger relationships and ultimately drive revenue through target advertising.

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Technical Specifications

The table below shows how FaceMatch SDK performs on the Labelled Faces in the Wild (LFW) dataset:

FPRTPRThreshold (Inverse of distance)
0.10.99900 ±0.002130.55448
0.010.99667 ±0.005370.59791
0.0010.99367 ±0.006050.62989

FPR = False Positive Rate
TPR = True Positive Rate

These results are an indication only and are based on the specific dataset Labelled Faces in the Wild. Customers can expect similar performance, with possible variations due to hardware and the availability of annotated data.