See consumer reactions to different product designs and packaging materials
While door-to-door delivery and pickup has offered consumers new convenience and efficiency, retailers are facing increased costs and shrinking margins to pick, package and deliver these orders to consumers’ homes or trunks. . These costs are passed on to brands who are already facing increased expenses for higher shipping and material costs.
Brands are now faced with the delicate balance between creating lighter packaging to help reduce shipping costs and using sustainable materials, while creating packaging that will appeal to their target audience.
How AI can help brands hit cost, implement sustainability and balance visual appeal
Consumer expectations experiences around brands and online retailers have never been higher, in part because e-commerce activity has increased dramatically and many more brands are selling online. Algorithms and machine learning have accustomed consumers to personalized experiences when streaming content, scrolling through their social media feeds and visiting online marketplaces such as Amazon.
To get an indication of how consumers will react to new or redesigned packaging and products, brands have traditionally had to invest in expensive research projects that often take months, have limited options for respondents to review, and are subject to to prejudices.
AI-powered predictive image analytics enables brands to quickly understand consumer expectations at the speed and accuracy of e-commerce. It gives brands, marketers and analytics professionals the ability to test and optimize packaging designs in real time, allowing them to assess the effectiveness of potential packaging designs and concepts. visuals for a consumer audience in seconds.
Using machine learning based on millions of real interactions with online visual content, new predictive image analytics can assess an image’s performance across all channels, giving brands the ability to select designs most likely to motivate their target audience to action. . This technological advantage also gives brands the ability to understand the necessary cost and material trade-offs before they even start manufacturing.
Visual packaging trends in consumer goods categories
When it comes to packaging, brands need to implement innovative ways to grab consumers’ attention in saturated and competitive markets. To understand the types of insights brands can expect from AI-based predictive image analytics, it is possible to look at current trends across different product categories.
Online snack shoppers, for example, prefer product packaging with highly saturated and vibrant colors and patterns over product packaging with desaturated background colors. Brands such as Fruit Roll-Ups, Gushers, Funables and Betty Crocker all use bright colors in their fruit snack packaging.
When it comes to the spirits and liquor industry, brands whose labels feature detailed black-and-white illustrated graphics attract more online consumer attention and have a higher likelihood of converting digital shoppers. Brands such as The Kraken, Espolon, and Captain Morgan are currently using these product packaging design techniques.
While it’s especially important for branded food and beverage packaging to appeal to consumers, all industries face competition. Take the pharmaceutical industry for example – it’s critical that product and packaging designs outperform competing offerings. Over-the-counter (OTC) online shoppers prefer blue packaging elements and high-contrast or highly stylized product bottle caps. Products with high-contrast or highly styled caps include Robitussin Naturals, Vicks Nyquil, Mucinex All-In-One, and Kroger brand Severe Cold and Flu Daytime Cough Syrup, while products with blue packaging elements such as Mucinex Day & Night Children’s Cold Liquid and Vick’s VapoShower, are also said to be very effective.
Bring new agility, precision and collaboration to consumer goods and supply chain design teams
With consumer goods organizations tasked with bringing products to market faster and more cost-effectively than ever before, a deep understanding of customer preferences and how those preferences translate into costs and profit margins is required. AI-powered predictive image analysis makes conversations between design and supply chain teams more productive and packaging selections more informed. By using data to support their decisions, the two teams now have a common understanding of how consumers will react to packaging materials, shape, textures and composition. With this shared understanding, supply chain and purchasing teams can more accurately estimate packaging costs while having the ability to quickly retest concepts in seconds.