Context is king. When you take the time to understand the why behind words and actions, you can unlock insights that completely change your perspective—and your marketing approach.
When you have the right context about a review, customer feedback, or even a comment posted online, you can respond in a way that resonates. Every interaction transforms from mere chatter to valuable insights that can empower your business decisions.
That’s why conducting contextual analysis of your marketing metrics is so important. With AI and data analytics, you can dig deeper to learn the why behind the what and show your audience you get them.
Here’s what contextual analysis is, why it matters, and how you can harness it to improve your marketing and branding.
Contents:
Contextual Analysis Meaning: What Is Contextual Analysis?
How to Conduct Contextual Analysis
When to Use Contextual Analysis
Applications of Contextual Analysis
Conducting Contextual Analysis with Meltwater
Contextual Analysis Meaning: What Is Contextual Analysis?
Contextual analysis definition: The process of breaking down a complex topic into smaller components to understand it better.
We define contextual analysis as the process of learning the meaning of something beyond the surface. You might also hear it called context analysis.
Let’s look at a contextual analysis example: You look at a piece of artwork or hear a song by your favorite musician. If you were to do a contextual analysis, you’d peel back the layers to understand why the art or song is in its final form.
It’s not just about what’s being said, but also how it’s being said, who created it, where it came from, and how it influences others.
A single sentence can be taken out of context. For example, what would you think if someone wrote, “I can’t believe she did that!”?
Without hearing a person’s tone or knowing the context of a situation, this statement might be one of surprise, awe, or disbelief.
That’s why contextual analysis matters. It helps us understand what people are talking about and how they’re talking about them, which can make a big impact on your marketing and brand reputation management.
How to Conduct Contextual Analysis
In marketing, context analysis can surface insights into online reviews, customer feedback, social media comments, and even trending topics.
Here’s how you can conduct contextual analysis, step by step.
1. Choose a topic
Decide on a direction for your contextual analysis. For example, if you are getting a neutral or bad Net Promoter Score (NPS), you might dig deeper into customer feedback to find the root causes.
2. Gather the data
With a goal in mind, start choosing the data sources that will give you the context you need. Data may come from a variety of sources, such as online reviews, social media comments, customer feedback surveys, help desk tickets, CSAT surveys, or even your CRM. If you’re using a consumer intelligence platform like Meltwater, you can collect essential data in one place for easier review.
3. Pre-process the data
In some cases, you may need to clean and organize your data to make it easier to review. For example, you might exclude certain comments, nonsensical text, emojis, or outdated feedback.
4. Apply sentiment analysis
Brand sentiment analysis tools like Meltwater dig into emotional cues to help you uncover context behind the content. These tools use natural language processing, an AI-powered technology, to get a better understanding of what’s being said.
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5. Extract keywords and identify themes
Tracking keywords and grouping them into themes will help you zero in on specific topics or issues. Meltwater looks for term frequency along with how terms are used to give you a comprehensive look at a given theme.
6. Put it all together
Combine your new insights to gain a better understanding of your topic, whether it’s a series of bad reviews or what people love about a specific product. Take action based on your findings, such as refining a campaign or even an entire marketing strategy.
When to Use Contextual Analysis
There are lots of ways you can analyze your marketing data, including market analysis or SWOT analysis. Context analysis makes the most sense when you want to dig deeper into customer behavior and market trends.
You already have some data in your sights, such as a sentiment score or conversion rate. You can use context analysis to learn why those numbers are the way they are.
Applications of Contextual Analysis
Now that you know more about how to define contextual analysis, it’s time to apply it.
Here are some examples to get you started.
- Learn what works and what doesn’t from past product launches before launching a new product. Pay special attention to timing, messaging, audience, and culture.
- See how customer behaviors shift during seasonal or holiday campaigns.
- Discover how brands are using specific hashtags (and avoid ending up like the failed DiGiorgno #WhyIStayed campaign).
- Identify language nuances in customer reviews or social media comments.
- Gain insights into product development requests or feedback.
- Know what elements of an ad (e.g., imagery, colors, message, offers) resonate best with an audience.
- Find trending topics and interests that you can use in your marketing campaigns.
- Uncover pain points in customer feedback that could cause them to churn.
- Analyze competitor reviews to learn why customers choose or reject them.
- Identify inflammatory language that could indicate a crisis is brewing.
Brand monitoring tools can do most of the work for you. You can set up keywords to track and receive alerts when someone mentions that keyword or when you receive a negative review. Using context analysis, you can get the full meaning behind those words and decide the best way forward.
Conducting Contextual Analysis with Meltwater
Meltwater combines social listening with consumer intelligence to help you get inside the minds of your customers. Rather than simply collect data, we add context to content so you can understand how people are discussing your brand, a competitor, or a trend. Using the power of AI and natural language, we deliver done-for-you insights so you’ll know why the data matters and what you can do with it next.
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