Semasio Solution Toolbox
The choice is yours: whether you want to target a certain audience, deliver your campaign on relevant web-pages or exclude specific page contexts that are not suitable for your brand, the Semasio Solution Toolbox enables you to combine and extend the different solutions in an easy way to execute a Unified Targeting Strategy across users and pages.
Audience Targeting
If you want to reach your target audience directly independently of the page they are on the solution is Audience Targeting.
Learn more
Contextual Targeting
If you want to reach your target audience through the pages they consume the solution is Contextual Targeting.
Learn more
Brand Fit Targeting
If you want to avoid pages with specific content the solution is Brand Fit Targeting.
Learn more
Audience Targeting
If you want to reach your target audience directly independently of the page they are on the solution is Audience Targeting.
This can be created in two ways:
This can be created in two ways:
In the words of our CEO (1.05 mins)
Replay GIF
Keyword-based
Targeting users by the terms they consume
Electric car example
Targeting users by the terms they consume
Electric car example
When a user visits a page its Semantic Page Profile is integrated into the user’s Semantic User Profile. These Semantic User Profiles thus dynamically evolve over time by constantly aggregating the most significant terms and phrases consumed by each user.
In this example, keywords and phrases like “electric car”, “family car”, and “car seat” are selected to form an audience target with an affinity towards family-friendly electric cars. The platform automatically identifies more targeted criteria, including which terms and phrases to add and exclude, and returns a continuously updated list of users who have consumed these keywords. You can then dynamically trade off reach against affinity based on your unique marketing goal.
In this example, keywords and phrases like “electric car”, “family car”, and “car seat” are selected to form an audience target with an affinity towards family-friendly electric cars. The platform automatically identifies more targeted criteria, including which terms and phrases to add and exclude, and returns a continuously updated list of users who have consumed these keywords. You can then dynamically trade off reach against affinity based on your unique marketing goal.
High Affinity
BALANCED
HIGH reach
Reach : 355,842 unique users
Reach : 905,216 unique users
Reach : 4,234,000 unique users
Seed Audience-based
Semantic Extension from a Seed Audience
Boutique Hotel example
Semantic Extension from a Seed Audience
Boutique Hotel example
A Seed Audience is a group of users that is a good example of those you are trying to reach. You can reach more of the same users by letting our platform identify the semantic similarities in their browsing habits.
In this example, a Boutique Hotel chain has extracted their best customers from the CRM system and onboarded them to our platform.
The platform automatically identifies what the Seed Audience semantically has in common that differentiates it from the rest of the population and returns a list of similar users, or Semantic Twins, of the Seed Audience. You can then dynamically trade off reach against affinity based on your unique marketing goal.
In this example, a Boutique Hotel chain has extracted their best customers from the CRM system and onboarded them to our platform.
The platform automatically identifies what the Seed Audience semantically has in common that differentiates it from the rest of the population and returns a list of similar users, or Semantic Twins, of the Seed Audience. You can then dynamically trade off reach against affinity based on your unique marketing goal.
High Affinity
BALANCED
HIGH REACH
Reach : 4,412,481 unique users
Reach : 8,824,961 unique users
Reach : 26,474,884 unique users
Keyword-based
Targeting users by the terms they consume
Electric car example
Targeting users by the terms they consume
Electric car example
When a user visits a page its Semantic Page Profile is integrated into the user’s Semantic User Profile. These Semantic User Profiles thus dynamically evolve overtime by constantly aggregating the most significant terms and phrases consumed by each user.
In this example, keywords and phrases like “electric car”, “family car”, and “car seat” are selected to form an audience target with an affinity towards family-friendly electric cars.
The platform automatically identifies more targeted criteria, including which terms and phrases to add and exclude, and returns a continuously updated list of users who have consumed these keywords. You can then dynamically trade off reach against affinity based on your unique marketing goal.
In this example, keywords and phrases like “electric car”, “family car”, and “car seat” are selected to form an audience target with an affinity towards family-friendly electric cars.
The platform automatically identifies more targeted criteria, including which terms and phrases to add and exclude, and returns a continuously updated list of users who have consumed these keywords. You can then dynamically trade off reach against affinity based on your unique marketing goal.
High Affinity
BALANCED
HIGH reach
Reach : 355,842 unique users
Reach : 905,216 unique users
Reach : 4,234,000 unique users
Seed Audience-based
Semantic Extension from a Seed Audience
Boutique Hotel example
Semantic Extension from a Seed Audience
Boutique Hotel example
A Seed Audience is a group of users that is a good example of those you are trying to reach.
You can reach more of the same users by letting our platform identify the semantic similarities in their browsing habits.
In this example, a Boutique Hotel chain has extracted their best customers from their CRM system and onboarded them to our platform.
The platform automatically identifies what the Seed Audience semantically has in common that differentiates it from the rest of the population and returns a list of similar users, or Semantic Twins, of the Seed Audience. You can then dynamically trade off reach against affinity based on your unique marketing goal.
You can reach more of the same users by letting our platform identify the semantic similarities in their browsing habits.
In this example, a Boutique Hotel chain has extracted their best customers from their CRM system and onboarded them to our platform.
The platform automatically identifies what the Seed Audience semantically has in common that differentiates it from the rest of the population and returns a list of similar users, or Semantic Twins, of the Seed Audience. You can then dynamically trade off reach against affinity based on your unique marketing goal.
High Affinity
BALANCED
HIGH REACH
Reach : 4,412,481 unique users
Reach : 8,824,961 unique users
Reach : 26,474,884 unique users
Contextual Targeting
If you want to reach your target audience through the pages they consume the solution is Contextual Targeting.
This can be created in two ways:
This can be created in two ways:
In the words of our CEO (50 secs)
Replay GIF
Keyword-based
Targeting pages based on the terms they contain
Cinema Chain example
Targeting pages based on the terms they contain
Cinema Chain example
Our platform constantly analyzes pages and identifies their most significant terms and phrases to form Semantic Page Profiles. This allows us to extract much more information from each page, enabling you to define virtually any Contextual Target you need.
In this example, a cinema chain wants to find the pages that users with interest in epic fantasy might read. Keywords and phrases like “fantasy movie,” “Tolkien” and “fiction” start to form a Contextual Target, which identifies pages dealing with the topic epic fantasy movies. The platform identifies more targeted criteria including which terms and phrases to add and exclude and returns a dynamic list of relevant pages. You can then freely trade off reach against affinity based on your unique marketing goal.
In this example, a cinema chain wants to find the pages that users with interest in epic fantasy might read. Keywords and phrases like “fantasy movie,” “Tolkien” and “fiction” start to form a Contextual Target, which identifies pages dealing with the topic epic fantasy movies. The platform identifies more targeted criteria including which terms and phrases to add and exclude and returns a dynamic list of relevant pages. You can then freely trade off reach against affinity based on your unique marketing goal.
High AFFINITY
BALANCED
HIGH reach
High Affinity: 9,429 pages
Balanced: 142,812 pages
High Reach : 312,342 pages
Seed Audience-based
Cookieless Extension from a Seed Audience
Cruise Line example
Cookieless Extension from a Seed Audience
Cruise Line example
A Seed Audience is a group of users that is a good example of the those you are trying to reach. You can reach more of the same users using Cookieless Audience Extension by having our platform automatically identify the pages your Seed Audience visit the most.
In this example, a cruise line has identified purchase intenders through a panel-based survey and onboarded them to our platform. The platform automatically identifies on which pages their potential clients are more likely to be found, creating and maintaining a Contextual Target based on the Seed Audience. You can then dynamically trade off reach against affinity depending on your unique marketing goal.
In this example, a cruise line has identified purchase intenders through a panel-based survey and onboarded them to our platform. The platform automatically identifies on which pages their potential clients are more likely to be found, creating and maintaining a Contextual Target based on the Seed Audience. You can then dynamically trade off reach against affinity depending on your unique marketing goal.
High Affinity
BALANCED
HIGH REACH
Reach : 1,089,000 unique users
Reach : 2,678,000 unique users
Reach : 5,234,000 unique users
Keyword-based
Targeting pages based on the terms they contain
Cinema Chain example
Targeting pages based on the terms they contain
Cinema Chain example
Our platform constantly analyzes pages and identifies their most significant terms and phrases to form Semantic Page Profiles. This allows us to extract much more information from each page, enabling you to define virtually any Contextual Target you need.
In this example, a cinema chain wants to find the pages that users with interest in epic fantasy might read. Keywords and phrases like “fantasy movie,” “Tolkien” and “fiction” start to form a Contextual Target, which identifies pages dealing with the topic epic fantasy movies. The platform automatically identifies more targeted criteria including which terms and phrases to add and exclude and returns a dynamic list of relevant pages. You can then freely trade off reach against affinity based on your unique marketing goal.
In this example, a cinema chain wants to find the pages that users with interest in epic fantasy might read. Keywords and phrases like “fantasy movie,” “Tolkien” and “fiction” start to form a Contextual Target, which identifies pages dealing with the topic epic fantasy movies. The platform automatically identifies more targeted criteria including which terms and phrases to add and exclude and returns a dynamic list of relevant pages. You can then freely trade off reach against affinity based on your unique marketing goal.
High AFFINITY
BALANCED
HIGH reach
High Affinity: 9,429 pages
Balanced: 142,812 pages
High Reach : 312,342 pages
Seed Audience-based
Cookieless Extension from a Seed Audience
Cruise Line example
Cookieless Extension from a Seed Audience
Cruise Line example
A Seed Audience is a group of users that is a good example of the those you are trying to reach. You can reach more of the same users using Cookieless Audience Extension by having our platform automatically identify the pages your Seed Audience visit the most.
In this example, a cruise line has identified purchase intenders through a panel-based survey and onboarded them to our platform. The platform automatically identifies on which pages their potential clients are more likely to be found, creating and maintaining a Contextual Target based on the Seed Audience. You can then dynamically trade off reach against affinity depending on your unique marketing goal.
In this example, a cruise line has identified purchase intenders through a panel-based survey and onboarded them to our platform. The platform automatically identifies on which pages their potential clients are more likely to be found, creating and maintaining a Contextual Target based on the Seed Audience. You can then dynamically trade off reach against affinity depending on your unique marketing goal.
High Affinity
BALANCED
HIGH REACH
Reach : 1,089,000 unique users
Reach : 2,678,000 unique users
Reach : 5,234,000 unique users
Brand Fit Targeting
If you want to avoid pages with specific content the solution is Brand Fit Targeting.
In the words of our CEO (45 secs)
Brand Fit Targeting
Avoid pages containing specific topics
Fast Food Chain example
Avoid pages containing specific topics
Fast Food Chain example
The Semantic Approach to Brand Fit allows you to define topics you do not wish your campaign to be associated with and enables you to dynamically avoid content which is dissonant with your unique brand and message.
In this example, a fast food chain plans a launch of its new triple-patty burger. Keywords and phrases like “vegetarianism”, “veganism”, “beef production” and “CO2 emissions”, begin to form a Brand Fit Target of topics that don’t resonate well with the marketing message around a triple-patty burger. The platform identifies more targeted criteria including which terms and phrases to add and exclude and returns a list of continuously updated pages, which can be used as a real-time updated blacklist for your campaign.
In this example, a fast food chain plans a launch of its new triple-patty burger. Keywords and phrases like “vegetarianism”, “veganism”, “beef production” and “CO2 emissions”, begin to form a Brand Fit Target of topics that don’t resonate well with the marketing message around a triple-patty burger. The platform identifies more targeted criteria including which terms and phrases to add and exclude and returns a list of continuously updated pages, which can be used as a real-time updated blacklist for your campaign.
High AFFINITY
BALANCED
HIGH reach
High Affinity: 561 pages
Balanced: 4,847 pages
High Reach : 12,501 pages
Brand Fit Targeting
Avoid pages containing specific topics
Fast Food Chain example
Avoid pages containing specific topics
Fast Food Chain example
The Semantic Approach to Brand Fit allows you to define topics you do not wish your campaign to be associated with and enables you to dynamically avoid content which is dissonant with your unique brand and message.
In this example, a fast food chain plans a launch of its new triple-patty burger. Keywords and phrases like “vegetarianism”, “veganism”, “beef production” and “CO2 emissions”, begin to form a Brand Fit Target of topics that don’t resonate well with the marketing message around a triple-patty burger.
The platform automatically identifies more targeted criteria including which terms and phrases to add and exclude and returns a list of continuously updated pages, which can be used as a real-time updated blacklist for your campaign.
In this example, a fast food chain plans a launch of its new triple-patty burger. Keywords and phrases like “vegetarianism”, “veganism”, “beef production” and “CO2 emissions”, begin to form a Brand Fit Target of topics that don’t resonate well with the marketing message around a triple-patty burger.
The platform automatically identifies more targeted criteria including which terms and phrases to add and exclude and returns a list of continuously updated pages, which can be used as a real-time updated blacklist for your campaign.
High AFFINITY
BALANCED
HIGH reach
High Affinity: 561 pages
Balanced: 4,847 pages
High Reach : 12,501 pages
