In the midst of a self-proclaimed connected world, the connection is missing. Marketing content looks at numbers (stats, analytics, ROI, etc.) and tries guessing target audiences as if they are mathematical equations. By contrast, social media sentiment analysis deep-dives into the psychological profile of users and scans their opinions and emotions.
Before we begin, what does it truly mean to connect with your audience? At any given moment, marketers need to know the best hours to post, the types of content that activate their audience, hot industry trends, and anything big data is bringing out.
However, what charts and figures aren’t telling are what words, pictures, perspectives, believes are making users click. In the end, what brings people together is the number of similarities shared between the brand and its audience.
The more common beliefs brands are using to build a solid social presence, the more members they will activate in their target audience. As social entities, we are drawn to parties with the same core values, be them friends or brands.
Therefore, the practical side of sentiment analysis in social media shows brands how to behave in public. Not only that, but this marketing segment powered by AI is answering so many more questions like this. Who are the best influencers businesses should associate their public image with? What’s the right tone that will defuse a social scandal? Which lifestyle types should the social content address to?
Let’s see how a sentiment reading on social media can fill in the gaps in today’s digital marketing!
What Is Social Sentiment Analysis?
Social sentiment analysis is a marketing process that identifies and registers subjective markers in social media content. At its foundation stands the latest martech solution: artificial intelligence. This explains why so far social media marketing relied on big data collection which barely scratches the surface.
What actually happens during a sentiment processing is starting with a database. It can contain anything from the latest posts from 100 top brands to all comments written to a particular business. Once the data collection is ready, each emotion is labeled as either positive, neutral or negative.
From this point on, the ramifications multiply and intertwine in a synthesis of reports that serve different goals. For instance, one evaluation can be customized to highlight the best influencer to work with out of ten. Find more applications for social sentiment probing in the following chapters.
Once the process extracts the empirical data, social sentiment analysis moves on to deduce user attitudes. This way, marketers learn how their audience feels about their activity on social platforms.
Emotions Under the Radar
There are three tiers that offer depth to sentiment analysis. First, basic attitudes make up a broader spectrum:
- Positive (when customers are extremely satisfied with how your product helped them);
- Neutral (when features are too generic, reviews are lacking in sentiment);
- Negative (when customers are feeling strongly against a product’s performance).
In their turn, these 3 large categories can be branched out in several types of emotions. AI algorithms intercept them through captions, face recognition, geolocation, and object recognition:
Nonetheless, there are not only emotions that marketers are after but also the tones users employ when they’re writing captions, reviews, comments or messages. Usually, the process intercepts them from excerpts in the form of text.
Indeed, there are plenty of different variations that have developed over time. In a world open to interpretation, it is best to choose one model and stick to it from then on. This way, companies can log the history of sentiments and see how it evolves.
Next up, a social sentiment analysis reveals how strong these basic attitudes, major sentiments, and text tones are. On a scale from 0 to 100, each marker is positioned accordingly.
By highlighting sentiment intensity, marketers are in the know of how deeply customers feel about their products. For instance, there can be numerous signals that indicate dissatisfaction. However, as long as none of them goes higher than 30 points in intensity, marketers can focus more on fortifying other weak points.
How Will a Sentiment Scan Help Your Brand?
It’s all about context. Through social sentiment analysis, marketers can read the story behind a sudden change in metrics.
Take social media reach for example. This is a key metric that tells you how many users have actually seen your post. Everybody wants to ace a high reach, but for good reasons.
What if an unexpected spike in your reach was due to negative feedback? If left unattended, all this negativity will rapidly follow a snowball effect. Ultimately, your brand is in danger of falling from grace.
On the other hand, sentiment analysis can decipher the conditions that made a shift in metrics possible. This way, marketers are aware that they need to act before an angry comment gets out of hand.
Benefits of a Sentiment Analysis Implementation
There are certain issues marketers are still having trouble to address despite the massive amount of data available to them. These gaps can be easily filled by accessing subjective information. After all, emotion is a big part if not a decisive one in any shopping experience.
a. A New Formula for Customer Experience Excellence
There’s no better time than today to start improving relationships with your community. An open, timely, and helpful communication can be the very element that differentiates a brand from its competitors.
Sentiment monitoring can detect in time any early speck to a brand’s reputation. While the saying “bad advertising is good advertising” still holds true, it’s the way brands manage negative reviews that makes a difference.
By intercepting and responding to reviews within the first hour of their appearance, companies show the audience that they do care. In the process, the regretful customer can turn into a happy one with the right solution.
b. Protect Your Brand Image
Are photos tagging your brand starting to display customers with neutral expressions on? Do the latest reviews use strong keywords tilting the balance towards dissatisfaction?
Sentiment analysis casts a web throughout social media. At any vibration of a thread, AI sends a report back to marketers. From there on, it’s up to them how they decide to tackle the issue at hand.
It can be a complaint to which there’s already an easy fix or constructive feedback for which the tech department needs to build the fix. Either way, staying on top of the situation is part of any business success story that knows how to protect its reputation on social media.
c. Out of a List of Compatible Influencers, Select the Surefire Partner
In the absence of a social media sentiment analysis tool, marketing teams select influencers based on their public stats. However, there are further underlying criteria that can be true game-changers.
By intercepting the emotion a creator’s work sparks across their community, brands can better understand influencers’ depth of authority.
Ultimately, what companies are looking for in a partnership with influencers is their power of suggestion over a certain kind of audience. As long as the public reaction remains cold to the bulk of creative content, a product recommendation might not yield any fruitful results.
d. Explore Empathic Engagement
Social media marketing entails a 2-way street. Marketers shoot out promotional material but they also have to keep the lines of communication hot. Otherwise, an aloof business account has few chances to build trust with customers.
This is where social media sentiment analysis comes in. A good grasp of the tone and sentiment of an audience makes it easy to replicate the same mindset and respond to comments and replies in the same manner.
This is what psychologists call mirroring. It is a social behavior that gives away signs of empathy when a person starts replicating the other’s gestures or verbal tics. At the same time, people whose behavior is mirrored feel like it comes naturally to relate to their companions. On social media, this phenomenon helps brands engage more easily with their community.
e. Get Access to the Latest Competitive Insights
Sentiment analysis can also be seen as a new pair of goggles to spy on your competitors. By redirecting the algorithms towards similar eCommerce sites, companies can notice how differently consumers feel about them.
By scanning competitors’ social audience, you get access to a new perspective. In a short time, your brand can acquire a better understanding of complementary features and what’s so attractive about them. Armed with a fresh vision, it’s easy to adjust tactical strategies and plan upcoming product improvements.
A Short ProductLead Use Case in the Beverage Industry
ProductLead’s Insights Analytics managed to compare 6 influencers and choose the best fit for a client activating in the beverage sector. Overall, the process integrated social media sentiment analysis into its big data report.
In the end, all 6 names underwent an appraisal consisting of several chapters. The ProductLead team studied authentic engagement, quality audience, reach, engagement rate, demographics, interests, sentiment activity, and motivations.
What influenced the final decision was the client’s brief describing the perfect persona. ProductLead’s influencer selection paid close attention to three main features:
- a highly influential creator (thus the numbers had to be topnotch);
- with an outgoing personality (therefore the target motivations were Vitality, Power, and Recognition);
- who nurtures an amazing connection with the audience (the perfect fit had to score big on the sentiment segmentation map under the Positive spectrum).
Sentiment Segmentation Map
By collecting both objective and subjective data, ProductLead managed to rationalize why a creator is better than the other businesswise. Their social stats might have been hypnotizing, but it was the way their community perceives them that made it as the biggest decisioning factor.
The Sentiment Segmentation Map gives a visual representation of the extent each creator influences their community in a positive, negative or neutral way. Behind each percentage stand strings of data where emotions and tones are expressed on a scale of 0 to 100.
According to the Sentiment map, Influencer 4 creates the biggest positive impact on social media. Not only that, but ProductLead data shows that the same account’s negative and neutral footprint is minimal.
As previously mentioned, the client’s brief did not limit ProductLead’s research to the subliminal messages algorithms identify in UGC, captions, hashtags, colors, and so on. On the contrary, the project went further than that to the point of analyzing the underlying motivations that drive influencers’ creative work.
Simply said, the brief asked for a gregarious and sophisticated influencer. On top of that, the ideal partner needed to be susceptible to stimuli born in a modern urban landscape such as metropolitan travel destinations or the latest trends in tech and entertainment.
On a motivational scale, this target persona fits three models:
- Vitality (This is a person who never settles, but is always looking for new experiences, full of energy, accepts challenges easily);
- Power (Cares about social status with a desire to guide others, takes initiative);
- Recognition (Individuals in this group feel at their best when they are in the center of attention and find it natural to stand out in the crowd thanks to their extravagant personality).
Within the data environment ProductLead algorithms populated with intel from sentiment analysis, tone analysis, and color psychology, the following chart ensued. Insights Analytics succeeded in measuring the range each of the six influencers crossed within Vitality, Power, and Recognition.
Once again, Influencer 4 trumps all others on the Motivational Map. Armed with this kind of data, it is up to the client to compare subjective and objective analytics and make the decision that suits their company best.
AI Is Well Within Your Reach
All in all, AI technology has advanced further enough to become an everyday tool marketers employ to finetune their strategies. Social media sentiment analysis is now capable of extracting core intel that big data cannot distinguish.
The common perception stagnated to a period where artificial intelligence was a vivid character in SF novels only. However, technology has made groundbreaking progress since then. Now marketers have an entirely new slew of data to build their personalized strategies with.
Social media sentiment analysis enjoys all the good reasons to step inside any eCommerce concept. It improves engagement, goes deeper into the relationship with customers, spots the perfect influencers, and builds a better social presence for your brand. Try this technology yourself and watch how your social media marketing unlocks new possibilities!