I like to think of myself as a foodie, and I love to explore fabulous new recipes to cook at home. That’s why I was thrilled to discover the innovative predictive personalization application from McCormick called FlavorPrint.
The application provides you with a FlavorPrint based on 12 different flavor personality types, and makes new flavor, product, and recipe recommendations to match. Of course, you can then share these recommendations with your friends via social media or print a shopping list to take along on your next grocery trip. The more consumers engage, the smarter the service becomes.
The trend of predictive personalization, also known as predictive analytics, has brands using data to predict customer needs or wants, then serve communications tailored to these needs.
Amazon and eBay are at the forefront of this technology. By separating the retail signals from the noise across tens of thousands of variables, a company can gain an advanced understanding of what’s happening in its virtual economy and can identify immediate opportunities—effectively, insights in action.
While some consumers might see this technology as ‘Big Brother,’ most are OK with it if they receive a tangible benefit, like saving money, seeing relevant offers, having shopping made easier, or, like with FlavorPrint, discovering new meal options.
Predictive analytics give retailers data they can leverage to differentiate themselves, customize a shopping experience; and make the retail organization operationally efficient, customer-focused, and highly profitable. In the end, it’s a win-win for shoppers and retailers—not only does this technology enhance the overall shopper experience, but, ultimately, the data allows for greater conversion and basket size.
The opportunities to take FlavorPrint to the next level are endless, from partnering with a key retailer group to rollout flavor profiles in the store, to creating printable shopping lists and recipe customization.
Contributed by Erin Kelly, Integer Australia.
Image Source: FlavorPrint
