Artificial Intelligence

Consumer Insights: Why the Customer Isn’t Always Right

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Every brand needs to have a deep understanding of its target audience. What makes them tick? What are they looking for and where are their needs being, or not being, met? Is there a gap in the market?

Being out of touch or tone-deaf when it comes to your customer base could even alienate or deeply offend them. One example that comes to mind is a recent Dove ad that was meant to celebrate the “beauty of diversity” that didn’t exactly match consumer expectations. The worst part is that they could have learned from a similar advertising misstep in 2011. By analyzing the consumer response to their previous racially charged campaign they could have foreseen that it would elicit anger.

Consumer insights are not just critical for marketers, but for research and development, finance, sales, and boards of directors as well. They inform campaign strategies, future product development, competitive intelligence and so much more. But with so much on the line, why are businesses still turning to outdated methods to gain consumer insights?

In this blog, we’ll look at how far consumer insights have come as well as the developments we can expect to see in the future.  

Social Media: The ‘New’ Focus Group for Consumer Insights

Focus groups have been around for nearly a century. Brands choose a handful of people to sit in a room with two-way mirrors and discuss their product. In theory, it seems like a reasonable way to get accurate consumer insights. The same can be said about surveys, sales analysis, or other traditional types of market research. You’re going directly to the consumer and asking them straightforward questions about your product.

Even though this research may certainly provide value, it’s also flawed. For one, traditional methods of market research rely on a relatively small group of consumers. Not to mention they take time for consumers to complete, and for brands to create, execute, and analyze—often resulting in abandoned research.

Perhaps the most prominent flaw of all in asking consumers is just that—‘asking.’ It’s human nature to first consider who’s asking the question before carefully responding. This well-researched phenomenon, known as the Hawthorne Effect, indicates that a person’s behavior is greatly affected by the awareness of being observed. This means that our responses can often be more aspirational than honest.

For example, when Netflix surveyed subscribers about their entertainment likes and dislikes, they discovered that what people said they liked to watch and what they did watch were often quite different. While consumers might say they are frequent viewers of cerebral documentaries, Netflix knows they’ve never missed an episode of Real Housewives.

Technology has advanced and, through a combination of artificial intelligence and the massive conversation database that is the internet, we are able to gain the most astute consumer insights to date. The internet is an endless buffet of data and trends. The Olive Garden breadstick of data. Because of AI, we are now able to parse billions of tweets, product reviews, and more to narrow it down to specific insights.

How to Discover Real Consumer Trends

Social analytics is an emerging tool that uses artificial intelligence to access and analyze what consumers are talking about online. It involves an algorithm that you can ‘teach’ what you would like to know and gather results based on billions of tweets, forum posts, product reviews, messages, blogs, news articles, and images. From there, you can view the entire buyer’s journey, through their own eyes, at the most granular level and uncover intent behind the purchase.

However, it’s important to differentiate trends from passing fads to avoid make business decisions that you’ll later regret. For example, ‘gluten-free’ is a growing topic of conversation when it comes to food, and there’s data to back that up. But if a term like ‘food coloring’ is decreasing or remaining the same in number of mentions, it’s less likely to deter existing customers or bring in new ones. Pay close attention to the rate of change when analyzing this data.

The best part about social analytics is that it’s multidimensional. It gives brands so much more information than traditional methods. Through AI we can mine the data and messaging even further so that we see more than just what people feel, but why. For example, let’s say you’re researching four diet categories: dairy-free, gluten-free, vegan, and vegetarian. Not only can you compare how often those terms are mentioned, you can also see terms commonly associated with those topics such as allergies, weight loss, high prices, and so on. This compounded data turns consumer research into a true science. 

The Future of AI: Image Analysis and More

Every day, the internet becomes more images and less text. Social media users now share more than three billion images daily. Therefore, the tools that help marketers analyze text alone are losing value, while image analysis technology is taking center stage. Images allow marketers to unpack an even deeper level of meaning than insights gleaned from text.

Let’s stick with food and use ice cream as an example. An ice cream brand can learn a lot from their customers based on the pictures they take. Are they eating at home or at an ice cream shop? If they’re at home are they watching movies or TV? Are they alone or with friends? Are they adding any toppings?

As with all technologies, AI-powered image analysis is evolving incrementally. Did you know that 85% of social media images have no textual reference to the brand in the image? Many solutions allow marketers to identify logos within online images to alert you when your brand or a competitor’s brand is being discussed, and this is just the beginning. As the technology matures, the best AI-powered image analysis tools will also detect faces, actions, settings, and more. As this discipline matures and the software improves, image analytics will make significant contributions to the pursuit of consumer insights.

How are you using AI and other tools to dive deeper into your consumer insights? Tell me about how your process has changed in the comments.