Spiketrap 101: Defining Contextual Analysis

Published On: April 21, 2022By Categories: Learn, Spiketrap 101Tags:

The Value of Contextual-Based Marketing Solutions

As marketers, building genuine connections with our audiences can often involve chasing the answers to big, sometimes even ambiguous questions. 

However, perhaps the most important question to ask while seeking authentic understanding looks for the context behind audience behavior, and that question is simply: “Why?”

The Big Questions The Context
How is our brand being discussed? Why is our brand being discussed?
What inherent value do our users derive from our products? Why do users find any given value?
Where are our users, and how can we reach them in new and innovative ways? Why are our users where they are?

Contextualization companies like Spiketrap exist to help brands connect in a more genuine manner with their customers – all by searching for the why behind online consumer interactions.

By understanding our audience in context, we’re able better discover motivations and interests – and more successfully market in a way that is compelling, authentic, and relevant.

We don’t notice ads that aren’t contextually relevant to our interests and our needs. AI-powered contextualization helps marketing feel more authentic and genuine – because it actually is.

Breaking Down Contextual Analysis

What is contextualization?

Most simply defined, contextualization is the act of putting things into context. 

More specifically, contextualization within analytics is the act of taking data – whether numeric, text, or another expression – and analyzing it based on the environment in which it is found and the concepts surrounding it. In other words, contextual analysis derives insights from a dataset based on frames of reference specific to the included data points, and contextualized data is data that provides a relational and illustrative understanding of that analysis.

How does contextual analysis enrich data?

In short, contextual analysis shows greater insight for a given dataset. To illustrate this, let’s look at a bare-bones example of two completed marketing campaigns. 

Scenario 1: Your campaign drives 10,000 pieces of audience engagement, 100 of which are impactful and have a positive sentiment. Reactions to the campaign saw an overall community brand safety score of D.

Scenario 2: Your campaign drives only 500 pieces of engagement, 300 of which are impactful and have a positive sentiment. Reactions to the campaign saw an overall community brand safety score of A.

Without context, Scenario 1 would be seen as arguably more successful than Scenario 2, based on engagement numbers alone. 

However, through contextual analysis, you discover qualitative insights that reveal a different picture of campaign performance. Metrics like audience sentiment, impact ratio, and brand safety show that the 10,000 pieces of engagement in Scenario 1 tell a less than positive story about campaign value and ROI. 

If the campaign goal is purely awareness, and not audience retention, affinity, or loyalty, the first scenario could be considered more successful with or without context. However, is audience retention, affinity, and loyalty ever not the ultimate goal of what we do as marketers? 

Contextual analysis delivers a deeper understanding of why your audience is engaging, and an arguably more accurate understanding of campaign performance and brand loyalty.

Contextual audience analytics provided by Spiketrap include audience sentiment, community safety ratings, conversation trends, impact engagement, and more.

How does contextual analysis increase data?

Along with providing deeper insights into audience motivations and helping build connections, contextual analysis also delivers an expanded breadth of discoverable audience engagement.

The way our audiences talk online is often ambiguous and disjointed, bursting with emojis, memes, ever-evolving inside references, and more. For this reason, unstructured user-generated content is often disregarded — or woefully misunderstood — by audience insights providers. Direct references to specific entities are not always used within organic conversation, and naturally-occurring ambiguous references remain unidentified by keyword-based tools.

However, with highly-trained advanced tech like Spiketrap’s Clair AI — which is designed to identify, understand, and accurately attribute indirect references — discovering insights within unstructured content is possible, even within high-velocity environments like Twitter, Discord, Reddit, and Twitch.

Why is data contextualization important?

Context removes ambiguity and promotes understanding, increasing the depth and breadth of our available insights and allowing us to better understand and reach our audiences. 

Better contextual advertising with Spiketrap AI-powered insights

Contextual Advertising in Real-Time

Seeing into the NOW

To effectively navigate ever-changing digital audiences, contextual marketing must also happen with real-time perspective. 

As language evolves and new social channels continually appear, the need to communicate, and to understand that communication, grows. This is why being able to see into the now, stay ahead of trends, and answer why based on real, reliable data is more important than ever.

By staying abreast of what is relevant to our users, and understanding consumers in real-time, we’re able to establish a more immediate and deliberate connection between our marketing and our audience engagement.

This connection allows us to identify opportunities and risks as they appear within our communities – and subsequently spark greater joy, satisfaction, and loyalty.

Spiketrap: Contextual Solutions for Gaming and Beyond

From day one, our mission has been to unlock audience understanding by creating a contextual analytics platform and contextual marketing solutions that help brands, game publishers, developers, and streaming platforms make better decisions through otherwise unknowable insights.

Our real-time data provides understanding at the genre, brand, and franchise-level, but it doesn’t stop there – think character, patch, and even item-level insights based on real-time, organically-generated discussions happening all across the internet.

Spiketrap contextualizes what others can’t, delivering insights that include:

  • How people are actually talking about a given topic or brand
  • What the sentiment is behind those conversations and engagements
  • Where the conversation is flourishing, and what the top conversations are
  • What affinities of cross-interest can be found
  • Which environments are safe — or not — to advertise on
  • How visual expressions such as emotes, emojis, and emoticons

Accessing Spiketrap’s Contextual Insights

Contextualization is the future of ad targeting – and we deliver contextual analysis that is built upon a foundation of deep, AI-powered understanding, an unparalleled knowledge graph, and industry expertise.

gaming analytics platform and insights dashboard

Insights Platform

Visual analytics dashboards, competitive intelligence, trending stories, and more.

advertise to gamers with contextual ad gaming target segments and media solutions

Contextual Targeting

Including gaming-specific target segments, available through major DSPs.

API Integration

Integrate our data and insights directly into your preferred dashboard.

Let’s Chat

Contact us to see how we can provide your brand with deeper audience insights.

Discover More

Spiketrap 101s

Discover the fundamentals behind Spiketrap’s contextual solutions.

Learn More

Feature Updates

Browse blog posts to see the latest updates and innovations to our tools and features.

Read More
[fusion_builder_column type=”1_3″ layout=”1_3″ align_self=”stretch” content_layout=”column” align_content=”space-between” valign_content=”flex-start” content_wrap=”wrap” spacing=”4%” center_content=”no” target=”_self” hide_on_mobile=”small-visibility,medium-visibility,large-visibility” sticky_display=”normal,sticky” elegant_backgrounds=”gradient” gradient_type=”linear” gradient_direction=”0deg” gradient_force=”yes” animation_mode=”normal” enable_background_slider=”no” elegant_transition_effect=”fade” elegant_background_scale=”cover” elegant_transition_delay=”3″ elegant_transition_duration=”750″ type_medium=”1_1″ order_medium=”0″ order_small=”0″ spacing_left=”5px”

Recent Posts

Spiketrap 101: Defining Contextual Analysis

Published On: April 21, 2022By Categories: Learn, Spiketrap 101Tags:

The Value of Contextual-Based Marketing Solutions

As marketers, building genuine connections with our audiences can often involve chasing the answers to big, sometimes even ambiguous questions. 

However, perhaps the most important question to ask while seeking authentic understanding looks for the context behind audience behavior, and that question is simply: “Why?”

The Big Questions The Context
How is our brand being discussed? Why is our brand being discussed?
What inherent value do our users derive from our products? Why do users find any given value?
Where are our users, and how can we reach them in new and innovative ways? Why are our users where they are?

Contextualization companies like Spiketrap exist to help brands connect in a more genuine manner with their customers – all by searching for the why behind online consumer interactions.

By understanding our audience in context, we’re able better discover motivations and interests – and more successfully market in a way that is compelling, authentic, and relevant.

We don’t notice ads that aren’t contextually relevant to our interests and our needs. AI-powered contextualization helps marketing feel more authentic and genuine – because it actually is.

Breaking Down Contextual Analysis

What is contextualization?

Most simply defined, contextualization is the act of putting things into context. 

More specifically, contextualization within analytics is the act of taking data – whether numeric, text, or another expression – and analyzing it based on the environment in which it is found and the concepts surrounding it. In other words, contextual analysis derives insights from a dataset based on frames of reference specific to the included data points, and contextualized data is data that provides a relational and illustrative understanding of that analysis.

How does contextual analysis enrich data?

In short, contextual analysis shows greater insight for a given dataset. To illustrate this, let’s look at a bare-bones example of two completed marketing campaigns. 

Scenario 1: Your campaign drives 10,000 pieces of audience engagement, 100 of which are impactful and have a positive sentiment. Reactions to the campaign saw an overall community brand safety score of D.

Scenario 2: Your campaign drives only 500 pieces of engagement, 300 of which are impactful and have a positive sentiment. Reactions to the campaign saw an overall community brand safety score of A.

Without context, Scenario 1 would be seen as arguably more successful than Scenario 2, based on engagement numbers alone. 

However, through contextual analysis, you discover qualitative insights that reveal a different picture of campaign performance. Metrics like audience sentiment, impact ratio, and brand safety show that the 10,000 pieces of engagement in Scenario 1 tell a less than positive story about campaign value and ROI. 

If the campaign goal is purely awareness, and not audience retention, affinity, or loyalty, the first scenario could be considered more successful with or without context. However, is audience retention, affinity, and loyalty ever not the ultimate goal of what we do as marketers? 

Contextual analysis delivers a deeper understanding of why your audience is engaging, and an arguably more accurate understanding of campaign performance and brand loyalty.

Contextual audience analytics provided by Spiketrap include audience sentiment, community safety ratings, conversation trends, impact engagement, and more.

How does contextual analysis increase data?

Along with providing deeper insights into audience motivations and helping build connections, contextual analysis also delivers an expanded breadth of discoverable audience engagement.

The way our audiences talk online is often ambiguous and disjointed, bursting with emojis, memes, ever-evolving inside references, and more. For this reason, unstructured user-generated content is often disregarded — or woefully misunderstood — by audience insights providers. Direct references to specific entities are not always used within organic conversation, and naturally-occurring ambiguous references remain unidentified by keyword-based tools.

However, with highly-trained advanced tech like Spiketrap’s Clair AI — which is designed to identify, understand, and accurately attribute indirect references — discovering insights within unstructured content is possible, even within high-velocity environments like Twitter, Discord, Reddit, and Twitch.

Why is data contextualization important?

Context removes ambiguity and promotes understanding, increasing the depth and breadth of our available insights and allowing us to better understand and reach our audiences. 

Better contextual advertising with Spiketrap AI-powered insights

Contextual Advertising in Real-Time

Seeing into the NOW

To effectively navigate ever-changing digital audiences, contextual marketing must also happen with real-time perspective. 

As language evolves and new social channels continually appear, the need to communicate, and to understand that communication, grows. This is why being able to see into the now, stay ahead of trends, and answer why based on real, reliable data is more important than ever.

By staying abreast of what is relevant to our users, and understanding consumers in real-time, we’re able to establish a more immediate and deliberate connection between our marketing and our audience engagement.

This connection allows us to identify opportunities and risks as they appear within our communities – and subsequently spark greater joy, satisfaction, and loyalty.

Spiketrap: Contextual Solutions for Gaming and Beyond

From day one, our mission has been to unlock audience understanding by creating a contextual analytics platform and contextual marketing solutions that help brands, game publishers, developers, and streaming platforms make better decisions through otherwise unknowable insights.

Our real-time data provides understanding at the genre, brand, and franchise-level, but it doesn’t stop there – think character, patch, and even item-level insights based on real-time, organically-generated discussions happening all across the internet.

Spiketrap contextualizes what others can’t, delivering insights that include:

  • How people are actually talking about a given topic or brand
  • What the sentiment is behind those conversations and engagements
  • Where the conversation is flourishing, and what the top conversations are
  • What affinities of cross-interest can be found
  • Which environments are safe — or not — to advertise on
  • How visual expressions such as emotes, emojis, and emoticons

Accessing Spiketrap’s Contextual Insights

Contextualization is the future of ad targeting – and we deliver contextual analysis that is built upon a foundation of deep, AI-powered understanding, an unparalleled knowledge graph, and industry expertise.

gaming analytics platform and insights dashboard

Insights Platform

Visual analytics dashboards, competitive intelligence, trending stories, and more.

advertise to gamers with contextual ad gaming target segments and media solutions

Contextual Targeting

Including gaming-specific target segments, available through major DSPs.

API Integration

Integrate our data and insights directly into your preferred dashboard.

Let’s Chat

Contact us to see how we can provide your brand with deeper audience insights.

Discover More

Spiketrap 101s

Discover the fundamentals behind Spiketrap’s contextual solutions.

Learn More

Feature Updates

Browse blog posts to see the latest updates and innovations to our tools and features.

Read More
[fusion_builder_column type=”1_3″ layout=”1_3″ align_self=”stretch” content_layout=”column” align_content=”space-between” valign_content=”flex-start” content_wrap=”wrap” spacing=”4%” center_content=”no” target=”_self” hide_on_mobile=”small-visibility,medium-visibility,large-visibility” sticky_display=”normal,sticky” elegant_backgrounds=”gradient” gradient_type=”linear” gradient_direction=”0deg” gradient_force=”yes” animation_mode=”normal” enable_background_slider=”no” elegant_transition_effect=”fade” elegant_background_scale=”cover” elegant_transition_delay=”3″ elegant_transition_duration=”750″ type_medium=”1_1″ order_medium=”0″ order_small=”0″ spacing_left=”5px”

Recent Posts

Spiketrap 101: Defining Contextual Analysis

Published On: April 21, 2022By

The Value of Contextual-Based Marketing Solutions

As marketers, building genuine connections with our audiences can often involve chasing the answers to big, sometimes even ambiguous questions. 

However, perhaps the most important question to ask while seeking authentic understanding looks for the context behind audience behavior, and that question is simply: “Why?”

The Big Questions The Context
How is our brand being discussed? Why is our brand being discussed?
What inherent value do our users derive from our products? Why do users find any given value?
Where are our users, and how can we reach them in new and innovative ways? Why are our users where they are?

Contextualization companies like Spiketrap exist to help brands connect in a more genuine manner with their customers – all by searching for the why behind online consumer interactions.

By understanding our audience in context, we’re able better discover motivations and interests – and more successfully market in a way that is compelling, authentic, and relevant.

We don’t notice ads that aren’t contextually relevant to our interests and our needs. AI-powered contextualization helps marketing feel more authentic and genuine – because it actually is.

Breaking Down Contextual Analysis

What is contextualization?

Most simply defined, contextualization is the act of putting things into context. 

More specifically, contextualization within analytics is the act of taking data – whether numeric, text, or another expression – and analyzing it based on the environment in which it is found and the concepts surrounding it. In other words, contextual analysis derives insights from a dataset based on frames of reference specific to the included data points, and contextualized data is data that provides a relational and illustrative understanding of that analysis.

How does contextual analysis enrich data?

In short, contextual analysis shows greater insight for a given dataset. To illustrate this, let’s look at a bare-bones example of two completed marketing campaigns. 

Scenario 1: Your campaign drives 10,000 pieces of audience engagement, 100 of which are impactful and have a positive sentiment. Reactions to the campaign saw an overall community brand safety score of D.

Scenario 2: Your campaign drives only 500 pieces of engagement, 300 of which are impactful and have a positive sentiment. Reactions to the campaign saw an overall community brand safety score of A.

Without context, Scenario 1 would be seen as arguably more successful than Scenario 2, based on engagement numbers alone. 

However, through contextual analysis, you discover qualitative insights that reveal a different picture of campaign performance. Metrics like audience sentiment, impact ratio, and brand safety show that the 10,000 pieces of engagement in Scenario 1 tell a less than positive story about campaign value and ROI. 

If the campaign goal is purely awareness, and not audience retention, affinity, or loyalty, the first scenario could be considered more successful with or without context. However, is audience retention, affinity, and loyalty ever not the ultimate goal of what we do as marketers? 

Contextual analysis delivers a deeper understanding of why your audience is engaging, and an arguably more accurate understanding of campaign performance and brand loyalty.

Contextual audience analytics provided by Spiketrap include audience sentiment, community safety ratings, conversation trends, impact engagement, and more.

How does contextual analysis increase data?

Along with providing deeper insights into audience motivations and helping build connections, contextual analysis also delivers an expanded breadth of discoverable audience engagement.

The way our audiences talk online is often ambiguous and disjointed, bursting with emojis, memes, ever-evolving inside references, and more. For this reason, unstructured user-generated content is often disregarded — or woefully misunderstood — by audience insights providers. Direct references to specific entities are not always used within organic conversation, and naturally-occurring ambiguous references remain unidentified by keyword-based tools.

However, with highly-trained advanced tech like Spiketrap’s Clair AI — which is designed to identify, understand, and accurately attribute indirect references — discovering insights within unstructured content is possible, even within high-velocity environments like Twitter, Discord, Reddit, and Twitch.

Why is data contextualization important?

Context removes ambiguity and promotes understanding, increasing the depth and breadth of our available insights and allowing us to better understand and reach our audiences. 

Better contextual advertising with Spiketrap AI-powered insights

Contextual Advertising in Real-Time

Seeing into the NOW

To effectively navigate ever-changing digital audiences, contextual marketing must also happen with real-time perspective. 

As language evolves and new social channels continually appear, the need to communicate, and to understand that communication, grows. This is why being able to see into the now, stay ahead of trends, and answer why based on real, reliable data is more important than ever.

By staying abreast of what is relevant to our users, and understanding consumers in real-time, we’re able to establish a more immediate and deliberate connection between our marketing and our audience engagement.

This connection allows us to identify opportunities and risks as they appear within our communities – and subsequently spark greater joy, satisfaction, and loyalty.

Spiketrap: Contextual Solutions for Gaming and Beyond

From day one, our mission has been to unlock audience understanding by creating a contextual analytics platform and contextual marketing solutions that help brands, game publishers, developers, and streaming platforms make better decisions through otherwise unknowable insights.

Our real-time data provides understanding at the genre, brand, and franchise-level, but it doesn’t stop there – think character, patch, and even item-level insights based on real-time, organically-generated discussions happening all across the internet.

Spiketrap contextualizes what others can’t, delivering insights that include:

  • How people are actually talking about a given topic or brand
  • What the sentiment is behind those conversations and engagements
  • Where the conversation is flourishing, and what the top conversations are
  • What affinities of cross-interest can be found
  • Which environments are safe — or not — to advertise on
  • How visual expressions such as emotes, emojis, and emoticons

Accessing Spiketrap’s Contextual Insights

Contextualization is the future of ad targeting – and we deliver contextual analysis that is built upon a foundation of deep, AI-powered understanding, an unparalleled knowledge graph, and industry expertise.

gaming analytics platform and insights dashboard

Insights Platform

Visual analytics dashboards, competitive intelligence, trending stories, and more.

advertise to gamers with contextual ad gaming target segments and media solutions

Contextual Targeting

Including gaming-specific target segments, available through major DSPs.

API Integration

Integrate our data and insights directly into your preferred dashboard.

Let’s Chat

Contact us to see how we can provide your brand with deeper audience insights.

Discover More

Spiketrap 101s

Discover the fundamentals behind Spiketrap’s contextual solutions.

Learn More

Feature Updates

Browse blog posts to see the latest updates and innovations to our tools and features.

Read More
[fusion_builder_column type=”1_3″ layout=”1_3″ align_self=”stretch” content_layout=”column” align_content=”space-between” valign_content=”flex-start” content_wrap=”wrap” spacing=”4%” center_content=”no” target=”_self” hide_on_mobile=”small-visibility,medium-visibility,large-visibility” sticky_display=”normal,sticky” elegant_backgrounds=”gradient” gradient_type=”linear” gradient_direction=”0deg” gradient_force=”yes” animation_mode=”normal” enable_background_slider=”no” elegant_transition_effect=”fade” elegant_background_scale=”cover” elegant_transition_delay=”3″ elegant_transition_duration=”750″ type_medium=”1_1″ order_medium=”0″ order_small=”0″ spacing_left=”5px”