What do terms such as big data, machine learning and artificial intelligence really mean in the context of packaging design? And how can data help marketers to develop more effective packaging and expedite and improve the processes? A data mining effort can yield specific insights to these questions and guide future design efforts while creating a path forward to accurately predicting packaging success.
What do terms such as big data, machine learning and artificial intelligence really mean in the context of packaging design? And how can data help us to develop more effective packaging and/or to expedite and improve our processes for doing so?
Throughout the world and across every product category, our studies have consistently confirmed an underlying universal reality: The e-commerce shopping experience is not well suited for packaged goods products.
When the term “luxury shopper” is mentioned, several stereotypical images may come to mind: Perhaps a well-dressed woman looking at Prada handbags or a distinguished gentleman wearing a Rolex watch.
Across nearly all companies, insights teams are struggling with reduced budgets, smaller staff and, most importantly and consistently, the pressures of tighter timelines.
All marketers recognize the importance of winning at the “First Moment of Truth” and influencing purchase decisions at the shelf. And to drive success (across brands, categories and retail channels), it is valuable to begin with a consistent thought process rooted in an understanding of how people actually shop.
Throughout the past decade, behavioral economics has made an enormous impact in the realm of academia, government and public policy. Today, this framework is now entering the world of marketing and consumer research — and its influence will be profound.
Over the past several years, we’ve seen an enormous shift in consumer preferences for food and beverage products. Increasingly, shoppers, most notably younger ones, are walking away from large brands perceived to be processed, artificial or mass-produced in favor of options they feel are more authentic, local and “real.”