Marketers know that consumers gravitate toward content with a strong emotional hook. Look at the most successful Super Bowl ads: While some aim for shock value and absurdity to lodge in viewers’ minds, the safest bet is often to create a commercial that either makes viewers laugh or brings them to tears.
A single tweet or email blast doesn’t carry nearly the clout that a Super Bowl ad can offer, but the value of emotional messaging is still clear. Social media content performs best when it strikes the right emotional chord for its audience. But in the course of production, the right sentimental move isn’t always obvious. Content that goes viral faces a similar challenge. While a few viral hits seemed destined for success from the get-go, most content that reaches this peak digital velocity is the product of data-driven analysis combined with expert intuition.
Emotional content is no different. For every tear-jerking ad about a lost puppy, there are many other attempts that fall flat in their efforts. Even worse, they miscalculate the audience’s reaction and are faced with a mass of offended consumers. It’s an unenviable position, and one that brands can help themselves avoid by taking advantage of new analytics opportunities designed to predict the emotional disposition of an audience regarding a brand, product, or service. This algorithmic approach, known as sentiment analysis, is harnessing big data to mine critical new insights into consumers’ behavior and their relationships with brands through the services they offer, the experience they provide, and the content they publish to social media and beyond.
Image attribution: Scott Webb
Sentiment analysis is an extension of predictive analytics and behavioral data, which many brands already use to become more efficient and effective in how they target their audience. It combines these data points and, based on how a consumer is currently reacting to a brand, product, or service online, makes educated guesses about the sentiments consumers are most likely to receive positively.
The process of evaluating an audience on an emotional level might seem futuristic, but it’s simpler than it sounds. With consumers expressing their viewpoints, opinions, and experiences through digital channels—primarily social media—it’s possible for an analytics solution to collect, organize, and evaluate the sum of these reactions to gauge the general consensus. According to the Balance, the most common approach to emotional analysis is studying consumer attitudes regarding “top box ratings.” These ratings are the variables that most often influence a consumer’s purchase decision, making them the most important factors in acquiring or retaining a customer. The primary top box ratings are effectiveness/accuracy, timeliness, and cost.
By tracking these data points through sentiment analytics solutions, a brand can use social listening tools to better understand where a company is succeeding and failing at keeping its target audience happy. Unlike more arduous types of feedback, sentiment tracking uses social media to collect information shared organically by consumers. Not only does this information reflect the attitudes of existing customers, but it also reflects the larger public discourse that shapes the reputation of that company. Through emotional analysis, brands can be more proactive in addressing gaps in customer satisfaction, responding effectively to the emotional needs of an audience, and taking better control of their brand’s reputation.
In the end, sentiment analysis can extend beyond the benefits of marketing to affect a range of brand activities including sales and product development. By continually studying the sentimental relationship between consumers and your brand, you can understand how to better satisfy their desires and needs.
Image attribution: Vance Osterhout
An algorithmic approach is currently the best way to spearhead sentiment analysis for any organization. With social listening tools to gather data and provide insights, brands can adjust strategy accordingly and tweak the emotional tone of content to get more engagement from an audience—and, just as importantly, to make them happier consumers.
It’s a worthwhile strategy for any company creating social media content or any other digital content to reach a target audience and deepen the brand’s relationship with consumers. But even this emerging approach may soon evolve through the incorporation of artificial intelligence. According to Marketing Dive, AI solutions represent an even more accurate method of understanding the emotional disposition of consumers and pinpointing the best ways to create emotional appeal. This includes not only establishing the base emotion, but also generating recommendations on subject matter, style, and tone, among other variables.
Personalized content is already a critical area of focus for brands, and fine-tuning the emotional appeal of content is simply another way to take these efforts further. While AI represents a potentially more expensive approach to emotional analysis, it’s also an opportunity to increase the value and ROI of your branded content by making it more effective in achieving its goals.
As companies face more pressure to connect with consumers on a deeper level, the emotional tone of content is becoming an important variable in a successful content strategy. Sentiment analysis offers the ability to strengthen content published via social and other digital channels, building a better audience relationship simply by taking the time to hear and understand their needs.
Featured image attribution: Aral Tasher