The freedom of choice
Our demographic segments enable you to target campaigns based on gender, income, etc. But not only that. As segment accuracy determines segment size, a common problem is that one segment variant doesn’t fit all campaigns. That’s why our Demographic segments come in multiple affinity variants - which means you have the freedom to pick the hit rate and reach in target group, that best fit your campaign size, budget and plan.
How can I use Demographic segments?
The Demographic segments can be used in multiple ways depending on the purpose of your campaign. Maybe you want to increase brand awareness in a group of young males or maybe your want to advertise a product towards people with a high income, because you know they’re more likely to purchase that product. In other words, our demographic segments can be used for both branding and performance campaigns.
How are Demographic segments built?
The Demographic segments are built on the foundation of our huge first party deterministic data pool. This forms the basis for the predicted segments. In other words, the Demographics segments are based on a massive amount of information about people that we trust are 100% true. This information is used as a training set to optimize the algorithms that our predictions rely on – creating targeting data with high reach and high precision.
Which Demographic segments are available?
|Age 18-24||dk||- devices|
|Age 18-30||dk||- devices|
|Age 18-40||dk||- devices|
|Age 20-50||dk||- devices|
|Age 25-34||dk||- devices|
|Age 35-44||dk||- devices|
|Age 41-99||dk||- devices|
|Age 45-54||dk||- devices|
|Age 51-99||dk||- devices|
|Age 55-64||dk||- devices|
|Age 65-120||dk||- devices|
|College or University degree||dk||- devices|
|High School education||dk||- devices|
|Primary School education||dk||- devices|
|Technical Education||dk||- devices|
|University Preparatory education||dk||- devices|
|Have Children||dk||- devices|
|Household Size of 1||dk||- devices|
|Household Size of 1||dk||- devices|
|Household Size of 2||dk||- devices|
|Household Size of 3||dk||- devices|
|Household Size of 4||dk||- devices|
|Household Size of 5||dk||- devices|
|High income||dk||- devices|
|Low income||dk||- devices|
|Medium income||dk||- devices|
Superior segment quality
Our segments are based on some of the strongest, most reliable algorithms in the market and some of the largest online panels. We strive to provide 100% transparency in all aspects, including our methodologies, data origin and – whenever possible – expected campaign performance and cost reduction. On top of that, we also take user privacy extremely seriously. The result: safe segments with superior quality and a great balance between hit rate and size.
Why introduce segments with multiple affinities?
Advertising is in essence, reaching an audience with a pervasive message in order to achieve certain goals. A traditional planning process carefully defines a target audience, analyze their online behaviour and identifies the full universe of online media properties and placements that are capable of reaching the target group. Another often more efficient option is to leverage data to help you to reach your target audience.
AudienceData enables you to spend your marketing budget on the right consumers directly, reducing the amount of impressions that are wasted. In order to pick the right strategy for any campaign you need to be able to measure and compare the effectiveness of different strategies.
Measuring the effectiveness of online media properties and placements have for years been defined by well-known metrics like affinity and reach. Measuring the effectiveness of data have however been more ambiguous. One problem that is increasingly present in many of the data audiences being offered is that behavioral data is used for classifying visitors into different demographic, interest or intent categories using increasingly complex machine learning algorithms.
The challenge with machine learning is that data scientists sometimes decide to rely on complex unsupervised learning models and end up releasing new data audiences where the algorithm that created the output is more or less impossible to understand for humans. A black-box approach. When that approach is used, the data output will often fall under Clarke’s third law:
“Any sufficiently advanced technology is indistinguishable from magic”.
And it is hard to sell ‘magic’ in an increasingly data-driven world where we rely on validation, performance-KPI’s and hard facts. Given the fact that all data are not created equal, AudienceProject has decided to add a declaration of content to our available demographic data segments. Moving forward our demographic audience segments will be rated by affinity.
Why rate probabilistic data segments using affinity?
Affinity is the definition of a data segments performance against a particular target audience versus the performance if you target the average population. Affinity is the metric that allows you to compare the performance of programmatic data driven strategies versus traditional media placement planning. A data driven strategy should only be pursued when it delivers more value than the traditional approach.
Affinity is also the metric that quantifies the reduction in wasted impressions on any given campaign. It puts a very tangible monetary value on the value that a skilled planner can add to an online campaign.
If you want to learn more about AudienceData segments, we recommend checking out the tour page or visiting our Helpdesk. Also feel free to get in touch with us if you want to have a chat about how your business can benefit from using AudienceData.