Beer Brands Chugging along with AI Psychographics

Beer incumbents are increasingly losing market share and feeling the pressure to compete with craft brewers. Consumer tastes are constantly changing and companies must evolve to stay competitive. The rise of the millennial consumer challenges the market. Their health-conscious, promiscuous behavior makes creating new products and finding loyal drinkers harder than ever. Implementing an AI strategy is the best bet beer companies can make at differentiating themselves from the competition and increasing top-line growth. To give a couple of examples: London-based beer startup IntelligentX leverages AI to analyze customer feedback and develop the next batch of beer. Carlsberg uses AI in a taste sensor platform to quickly distinguish between different flavors developed in their laboratory.

One innovative application of AI is psychographics. With psychographics, we can learn to predict consumer behavior trends and influence purchases by profiling customer personalities. According to one theory, there are 5 main traits that describe a person’s personality: openness, conscientiousness, extraversion, agreeableness, and neuroticism. If you know your target market’s personality, combined with demographic and geographic data, you can create nuanced and personalized messages to resonate more strongly with them. You can measure openness and agreeableness, then correlate to other factors to predict future customers. Psychographic data such as lifestyle data, consumer data, and buying patterns correlate closely to personality data and guide us to sway the consumer. This is a step up from simply analyzing consumer purchasing history and predicting what they will buy next.

Credit

The path to psychographic segmentation is to create a digital consumer footprint, which is produced by algorithms that were trained with millions of data points such as social media profiles and psychometric test scores. These capabilities are now available commercially and go beyond demographics and enable identifying specific behavioral patterns and segmentation according to preferences and personalities.

If this sounds familiar, it’s because some companies have misused this technique. As we wrote about previously, Cambridge Analytica is known for inappropriately utilizing psychographics to influence elections. At KUNGFU.AI, we stress our commitment to doing AI for Good and working ethically.

Using individual psychographics for marketing may sound like a revolutionary idea but, how would it actually apply to the beer business? Let’s take the example of hyper-targeted marketing. Suppose you have a beer company that’s launching a new IPA and you need help deciding where to focus your marketing efforts. You would obviously want to identify beer drinkers that have a high degree of openness and are willing to try new things. However, you can dig a little deeper.

Credit

A good approach would be to identify the personality traits of the people who are on the ledge about drinking a new beer. These people don’t usually try new things, but aren’t completely opposed to the experience. By analyzing psychographic metrics such as lifestyle data and buying patterns, you might tailor a marketing message that will sway these consumers towards your new offering; maybe they are passionate about protecting the environment or have certain political tendencies. Marketing efforts could consider these and place the product in the appropriate channels and with relevant messages.

Psychographics can help beer answer several other questions:

  • What are the target customers main lifestyle patterns?
  • What type of beer would be attractive to a customer segment that you wish to penetrate?
  • What other customer segments would it be beneficial to target?
  • Are there other brands/companies you can partner with to increase engagement and revenue?

 

Credit

There are many other ways to implement AI in the beer industry and other consumer product markets. From supply chain and manufacturing to pricing, AI can help organizations improve capital efficiency, uncover hidden trends, and develop a data-driven culture.