AI-enabled consumer intelligence (AICI) is the next big thing when it comes to data-driven customer experience (CX), marketing, and product development (discussed in my article from last year). And among AICI applications, perhaps the most exciting and least understood use case is using AI and social data to spot unmet consumer needs. Not just to improve product or service experience, but also to identify opportunities for innovation. Anyone in client-facing roles should be paying attention.
AICI is enabling both CX and insights teams to get their online and offline data together, and deliver insights that support CX, customer success, and yes, even sales and marketing efforts more broadly across the enterprise. To make this leap from traditional social listening approaches, we continue to need social signals. But also inputs from customer surveys, and search patterns, and other owned data from websites and marketing tools and beyond.
But the real enabler is AI. And more specifically machine learning.
This is why the most interesting developments in CX are where AI meets consumer insights (see our free Ipsos Views report on the growing role of AI for consumer insights). The cutting edge of this application is using semantic AI and machine learning to process and visualize what consumers are saying and doing. At Synthesio we call this Topic Modeling, and it’s a direction we see most brands heading as they look to master the next generation of social intelligence.
Here’s a view into how this approach works and what CX teams can expect as more vendors embrace this flavor of data science in their insights (and engagement) platforms.
An example in the consumer beauty sector
A great example is in the consumer beauty sector, where customer satisfaction and loyalty is increasingly tied to how the brand is embracing a sustainability imperative, in everything from sourcing and business practices, to packaging.
In this case, a goal was examining consumer experiences with sustainable packaging and refillables, a topic important to both brands as well as their retail partners. An initial Topic Modeling study exposed expected topics like the demand for “zero waste refillable deodorant,” but also found unmet needs related to experiences where packaging broke or wasn’t as durable as expected.
Digging deeper into specific social mentions and online communities, Topic Modeling also helped the team discover new innovation opportunities, such as bamboo as an alternative packaging material due to its uncommon strength and biodegradability.
With these new insights around the CX of current options, the team could then launch a focused follow-on survey to further see what consumers are thinking and identify their purchase intent. Specifically, the survey validated the importance of sustainability in the product consideration process (applicable also to merchants like a retailer or hotel which featured these products). And also showed that a third of consumers would purchase a bamboo refillable product if one was offered.
The best consumer insights create change. In this example, better CX starting by listening to what consumers really wanted. And then being more responsive by letting AI do a lot of the heavy lifting – to spot needs, suggest options, and allow teams to find solutions faster, before one bad experience becomes a trend.
Want to learn more about how Synthesio’s AICI platform can help you boost CX and identify opportunities for innovation? Request a demo with our team of experts!
