Three Levels of Social Media Sentiment Analysis - it goes far beyond just Brand Sentiment

Varun Sharma
Co-founder, CEO
January 12, 2023

Social media platforms are our equivalent to the modern-day town square. Users catch up on the news, share laughs, and have real-time discussions about the products they use in their everyday life. They complain when an in-app video freezes or an airline loses their bags. So there’s no shortage of data you can scour to understand how customers feel about your products. They’re willingly sharing it on social media for everyone in the world to see.

A typical social media sentiment analysis uses natural language processing (NLP) and machine learning to categorize the prevailing emotion in a user’s post about your company. Posts are rated as positive, negative, or neutral. The NLP or listening tool can rate your overall brand or product sentiment from there.

Social media sentiment analysis tools can help you understand how users feel about your brand and products, but you shouldn’t stop there. Simply finding out if customer feelings are positive or negative won’t give your product team enough to act on.

But this base layer of sentiment analysis, which consists of social listening, will only get you so far. Let’s say your analysis shows your company has received 63% positive mentions, 24% negative mentions, and 13% neutral mentions in the last three months. 

You’re now confident in your customer sentiment, but these metrics don’t offer anything actionable. There aren’t any insights you can use to turn the negative sentiment around for that 24% — nearly a quarter of your social media audience. An effective social media analysis lends tangible ways for your product team to change your customer experience and improve your sentiment score.

Go deeper to understand what’s driving sentiment and turn it around

True sentiment analysis should also seek out the reasons behind consumers’ feelings — positive or negative — and provide insights for you to incorporate in product development.

Basic sentiment analysis can give you a pulse of how users feel about your brand and products. Still, when you don’t consider the reasons for customer feedback, you risk making all the wrong inferences of the true “why” behind positive and negative sentiment.

The qualitative feedback left by users on social media contains trove of insights in both positive and negative mentions, provided you are able to do two things -

  • Go beyond just brand sentiment and dig deeper into not only specific keywords, but also semantically summarized insights or ‘reasons’ for the feedback.
  • You can actually quantify both keywords and ‘reasons’ to find spikes/dips to help prioritize what to act on.

Successful social media sentiment analysis tracks both keywords and motivation

Using an artificial intelligence (AI)-based analysis tool, you can track social media sentiment at three different levels: for your overall brand, for individual keywords, and by breaking it down into actionable reasons. Here are the three levels of social media sentiment analysis -

Level 1 - Capture overall sentiment

Track audience sentiment across all social media mentions you’re receiving to see if users are happy with your product or experience any unexpected issues.

This is only the first layer of sentiment analysis you’ll conduct. It’s another form of social listening; you’re just applying it directly to your mentions and replies instead of brand sentiment as a whole. Still, it’s helpful for understanding broad trends and seeing immediate changes in real-time, such as after a product release.

Any social listening tool, like Brandwatch, Hootsuite Insights, and Talkwalker, can report on the general sentiment around your brand on social media. But you should focus on product mentions and feedback specifically to equip your product team with valuable insights.

Level 2 - Track sentiment by keywords and topics

Your users will naturally bring up their favorite features and the peskiest bugs in your social mentions. You can track the keywords and sentiment around each keyword to understand specific pain points and opportunities.

In the example below, we are looking at some specific keywords and the distribution of sentiment for each of those keywords. Which keywords get talked about the most positively for the product, and which most negatively impact the overall sentiment?

A customer insights person can see that Application Performance(crashes/glitches) have a large percentage of negative mentions compared to positive mentions.

Level 3 - Track granular `reasons` for social media feedback

Level 3 is when you get quantified and specific reasons for feedback and can quickly and confidently prioritize what needs to be fixed.

We can see here that “unable to register” is spiking month over month on the trendline, along with “want to customize background”. This is even more specific than “login - negative sentiment” and far more specific than just “negative sentiment tweet”.

Source feedback proactively

It’s always a good idea to check in with users and ask them directly what they want to see from your product. Take the findings of your sentiment analysis and use that to shape your direct outreach to users since you understand what they’re looking for.

Talk about how you’re gearing up for your next product planning or launch or you want to hear what needs improvement. Figma’s VP of Product Tweeted out a great example of how to do this by asking his audience what should be included in 2023 planning.

Close the loop and update customers when you’ve acted on their feedback

Users aren’t shy about telling you when they’re experiencing problems, so don’t keep it a secret once you’ve finally fixed them. Let your customers know about product releases that address their concerns and ease their pain points. They’ll appreciate you’ve been listening carefully to their feedback and you’re building products with their needs in mind.

Measuring customer satisfaction is a continuous process made more accessible with automation. Book a demo with Enterpret to see it in action.
Get a demo with your data
Wisdom saves me hours every week. With 'Summarize with Wisdom,' I can condense feedback with a single click, replacing the tedious process of reading through hundreds of tickets. It’s life-changing!
Jil McKinney
Director of Customer Support, Descript
Before Enterpret, organizing research data took an entire day. Now, research synthesis is 83% faster - it takes just 15 minutes to pull the data and another 15 minutes to start synthesizing. Enterpret removes the manual work, allowing me to focus on strategic thinking with a clear mind.
Mike McNasby
User Research Lead, Descript
We are laser-focused on giving customers more than they expect through a hospitality-first, individualized approach to drive retention and loyalty. Enterpret has allowed us to stitch together a full picture of the customer, including feedback and reviews from multiple data points. We now can super-serve our loyal customers in a way that we have never been able to before.
Anna Esrov
Vice President of Customer Experience & Loyalty
Enterpret allowed us to listen to specific issues and come closer to our Members - prioritizing feedback which needed immediate attention, when it came to monitoring reception of new releases: Enterpret picked up insights for new updates and became the eyes of whether new systems and functionality were working well or not.
Louise Sellars
Analyst, Customer Insights
Enterpret is one of the most powerful tools in our toolkit. It's very Member-friendly. We've been able to share how other teams can modify and self-serve in Enterpret. It's bridged a gap to getting access to Member feedback, and I see all our teams finding ways to use Enterpret to answer Member-related questions.
Dina Mohammad-Laity
VP of Data
The big win-win is our VoC program enabled us to leverage our engineering resources to ship significantly awesome and valuable features while minimizing bug fixes and" keep the lights on" work. Magnifying and focusing on the 20% that causes the impact is like finding the needle in a haystack, especially when you have issues coming from all over the place
Abishek Viswanathan
CPO, Apollo.io
Since launching our Voice of Customer program six months ago, our team has dropped our human inquiry rate by over 40%, improved customer satisfaction, and enabled our team to allocate resources to building features that increase LTV and revenue.
Abishek Viswanathan
CPO, Apollo.io
Enterpret's Gong Integration is a game changer on so many levels. The automated labeling of feedback saves dozens of hours per week. This is essential in creating a customer feedback database for analytics.
Michael Bartimer
Revenue Operations Lead
Enterpret has made it so much easier to understand our customer feedback. Every month I put together a Voice of Customer report on feedback trends. Before Enterpret it would take me two weeks - with Enterpret I can get it done in 3 days.
Maya Bakir
Product Operations, Notion
The Enterpret platform is like the hero team of data analysts you always wanted - the ability to consolidate customer feedback from diverse touch points and identify both ongoing and emerging trends to ensure we focus on and build the right things has been amazing. We love the tools and support to help us train the results to our unique business and users and the Enterpret team is outstanding in every way.
Larisa Sheckler
COO, Samsung Food
Enterpret makes it easy to understand and prioritize the most important feedback themes. Having data organized in one place, make it easy to dig into the associated feedback to deeply understand the voice of customer so we can delight users, solve issues, and deliver on the most important requests.
Lauren Cunningham
Head of Support and Ops
With Enterpret powering Voice of Customer we're democratizing feedback and making it accessible for everyone across product, customer success, marketing, and leadership to provide evidence and add credibility to their strategies and roadmaps.
Michael Nguyen
Head of Research Ops and Insights, Figma
Boll & Branch takes pride in being a data driven company and Enterpret is helping us unlock an entirely new source of data. Enterpret quantifies our qualitative data while still keeping customer voice just a click away, adding valuable context and helping us get a more complete view of our customers.
Matheson Kuo
Senior Product Analyst, Boll & Branch
Enterpret has transformed our ability to use feedback to prioritize customers and drive product innovation. By using Enterpret to centralize our data, it saves us time, eliminates manual tagging, and boosts accuracy. We now gain near real-time insights, measure product success, and easily merge feedback categories. Enterpret's generative AI technology has streamlined our processes, improved decision-making, and elevated customer satisfaction
Nathan Yoon
Business Operations, Apollo.io
Enterpret helps us have a holistic view from our social media coverage, to our support tickets, to every single interaction that we're plugging into it. Beyond just keywords, we can actually understand: what are the broader sentiments? What are our users saying?
Emma Auscher
Global VP of Customer Experience, Notion
The advantage of Enterpret is that we’re not relying entirely on human categorization. Enterpret is like a second brain that is looking out for themes and trends that I might not be thinking about.
Misty Smith
Head of Product Operations, Notion
As a PM, I want to prioritize work that benefits as many of our customers as possible. It can be too easy to prioritize based on the loudest customer or the flavor of the moment. Because Enterpret is able to compress information across all of our qualitative feedback sources, I can make decisions that are more likely to result in positive outcomes for the customer and our business.
Duncan Stewart
Product Manager
We use Enterpret for our VoC & Root Cause Elimination Program. It's helping us solve the issues of aggregating disparate sources of feedback (often tens of thousands per month) and distilling it into specific reasons, with trends, so we can see if our product fixes are delivering impact.
Nathan Yoon
Business Operations, Apollo.io