What do your customers want, and what leads them to make the choices they do? In the age of social media, there’s no use operating your business on guesswork, hunches, or intuition when it comes to understanding your audience. Consumers leave clues to their behavior all over the internet, and savvy brands are sniffing it out and putting those consumer insights to work.
Consumer behavioral analysis is how they’re doing it, and social media listening does the heavy lifting. We’ll explore what that looks like in further detail, with a focus on:
- What is consumer behavioral analytics?
- How does consumer behavioral analytics work?
- How consumer behavioral analytics can help improve your brand
Not only is getting to the root of consumer behavior important – you need to get there fast. Sentiment, perceptions, and behavior change quickly in the digital age, so you’ve got to collect insights and act upon them promptly for the best results. Consumer behavior has already changed a lot since the pandemic started, as these stats suggest:
- 69% of people surveyed by Nielsen said they turned to ecommerce to buy household goods for the first time during the pandemic. Additionally, Millennials outspent Gen Z and Boomers when it came to stockpiling during quarantines.
- 50% of customers will do an about-face and shop with a competitor after a bad customer experience.
- 80% of consumers feel that the customer experiences a brand provides are equally as important as the products it produces and the services it renders.
Brands want insights into what makes their customers tick – and they know time is of the essence. To that end, let’s take a deeper look at consumer behavior analytics, including what it is and how it works.
What is Consumer Behavioral Analytics?
Since consumers are the heartbeat of any brand, it pays to do some legwork to better understand how they operate. Consumer behavioral analytics seeks to climb behind sales figures and general social media commentary to see what’s at work with your customers behind the scenes.
Nowadays, social listening has evolved in a way that can crosscut brand conversations for customer insights into why consumers behave the way they do. This is possible because social media users talk about their interests, influences, behaviors, and inclinations across the vast reaches of the web.
While the data they leave is primarily unstructured, it’s an invaluable data source nonetheless. Analysts harvest this data and use it to learn how their customers are operating within their circumstances and in light of emerging trends.
This type of consumer intelligence goes far beyond vanity metrics to explore the complexities of your audience. Often, customer behavior is not entirely intuitive from a surface-level understanding. Therefore, aggregating social media data for further exploration shows brands precisely what their customers are doing, talking about, and what they love, as well as what puts them off – and it’s all backed up by data.
In essence, consumer behavioral analytics assumes that surface-level insights alone cannot support effective strategy over time. Social media offers a vast and uncoerced source of consumer behavioral insights that can be explored to a granular level. And this depth of consumer understanding illuminates the factors at work that form your consumers’ overall perspectives.
The goal is to attain a comprehensive view of your customers’ behavior from the ground up. Let’s talk about how it works.
How Does Consumer Behavioral Analytics Work?
Consumer behavioral analytics is yet another capability of modern social listening tools. Using advanced artificial intelligence and natural language processing (NLP), we can capture and categorize every brand mention as it occurs on social media and across the web.
Text categorization segments your brand conversation by sorting for grammatical usage, including slang and misspellings, and assigning a sentiment value that accounts for positivity and negativity. In this way, your brand discussion becomes infinitely searchable and measurable.
Top terms, hashtags, attributes, behaviors, and emotions are brought to the forefront by aggregating their mention count. And since these are assigned a sentiment value, analysts can explore consumer behavior in-depth while tracking metrics over time as they wax and wane.
By uncovering the consumer behaviors present in your brand conversation, you’re then free to explore the ones most pressing to your brand’s market situation.
How Consumer Behavioral Analytics Can Improve Your Brand
A keen understanding of your consumers’ behavior provides value to many aspects of your brand. It’s possible to uncover how customers react to your marketing, how they behave within your purchase funnel, their response to your customer experience, and how they interact with your products, to name a few.
Humans are fascinating creatures, and their reactions to your products aren’t always what you’d expect. Understanding what they do with your products allows you to craft messaging that speaks to their peculiarities or roll out features that complement the innovative ways they like to use your product.
For example, here’s a word cloud showing the top behavioral terms in the social media discussion around iRobot’s popular Roomba vacuum cleaner over the past three months:
These terms act as thematic avenues brands can travel down to understand consumer behavior. Words such as want, buy, and need stand out, and here, they simply indicate they need or want to buy a Roomba.
That’s worth pointing out because, in your consumer behavioral analysis, you may find that they ‘want’ to buy a part, attachment, or ‘need’ someone to escalate their support ticket. That’s why digging down into these behavioral terms is so important.
However, where the Roomba conversation gets interesting is that their consumers exhibit some peculiar behavior with the product. And these conversations are found in words such as ‘watch’ and ‘interact.’ People absolutely love watching them work. Not only that, but many also consider them robotic family members – or even pets. This is definitely an area to attach messaging to.
Sometimes I just sit and watch my roomba like it’s my pet
— Traitor Joe (@LystenToMe) September 22, 2021
Since text analytics segments language in extreme detail, we can crosscut our brand conversation for insights into themes we’re most interested in. You can dial into consumer behavior insights according to demographics, geolocations, industry themes, emotional targeting, life moments, purchase funnel, etc.
Below, we’ve created a dashboard for Dyson’s brand commentary and attached themes filtering for specific conversational data. The ones we’ve chosen include behavioral terms surrounding consumer trust, customer care, purchase, and personal narrative (posts including ‘I’ and ‘my’).
This immediately gives us a high-level perspective of how these behavioral conversations are playing out with volume, timeline, and overall sentiment metrics.
We see that discussions around customer care and trust are smaller than the others but could use some work in the sentiment department. We can dive into the top terms, sentiment drivers, and behaviors attributed to each of our themes for a deeper understanding.
Going into detail in this manner provides the context for which these behavioral terms are used. Each of them is explorable, so we can see the posts and what people are talking about in each theme. For instance, how people use the words ‘buy’ and ‘use’ in a customer care context doesn’t correlate with their purchase funnel uses.
Consumer behavioral analytics takes you deep into the voice of the consumer. You’ll quickly find that pain points tend to aggregate into various themes, which you can then isolate and explore. Consumer behavior insights can be used in audience targeting, marketing strategy, R&D, customer service, and even a competitive intelligence capacity.
Reach out for a demo, and we’ll show you how a tailored approach to customer behavioral analytics can uncover actionable insights specific to your brand.