Personalization at Scale

By Elizabeth Gooding / Published:

Customization and personalization is now happening throughout the supply chain. Data on customer buying preferences – what, where and how they buy – is driving change in inventory management, distribution, product design and marketing.

Thomas Sineau of CB Insights* recently published a post titled “From Mass Production to Mass Personalization” that discusses how companies in highly standardized industries such as food, fashion and retail are driving hyper personalized customer service using big data and artificial intelligence.

  • McDonalds acquired Dynamic Yield, an AI-powered “Personalization Anywhere” platform that delivers individualized experiences across web, apps, email, kiosks, IoT, and call centers. The platform’s data management capabilities promise a unified view of the customer, allowing the creation of highly targeted digital interactions.
  • Nike recently purchased Celect, a cloud-based, predictive analytics platform that allows retailers to optimize their inventory portfolios in stores and across the supply chain. The technology allows retailers and brands to predict future buying patterns and behavior (both online and in-store) so they can make profitable merchandising, allocation and fulfillment decisions.
  • Walmart acquired Aspectiva which uses AI technology to analyze consumer review and opinion data from across the web and generate insights to influence online shoppers’ purchasing decisions.

The article cites McDonald’s plans to offer adaptive menus for drive-thru customers. The company may suggest items based on season, time of day, current traffic and weather to make ordering faster and more efficient. While the information cited relates to drive through and electronic menus, one can see how data could be similarly applied to printed menus in restaurant chains and related retail signage. Many chain restaurants carry affiliate advertising on their packaging which could also be tailored.

Fashion brands like Nike are using predictive analytics to manage inventory levels – but also to determine when, where and how consumers may buy the products. This may have an impact on how packaging is sourced designed and printed. Will more customers buy at particular retail locations or will more inventory be shipped direct to the customer?

Inkjet allows production output in every application segment and industry sector to be personalized at scale. I mean everything – from direct mail to menus and from postcards to packaging. The possibilities for changing the way that printed products are produced and managed are tremendous in many industries and that is where innovative companies can truly get ahead with more profitable output.

But in order to customize or personalize effectively, you must have data and related design variations to be driven. As CB Insights cautions, “AI algorithms are only as good as the data they are trained on.” Without good data, all our excellent software and hardware can’t fulfill its potential. Inkjet innovators should pursue data, processing and design partnerships in order to drive personalization at scale.

About the Author

Elizabeth Gooding


Elizabeth is the Editor and Co-founder of Inkjet Insight. She has a rare ability to see print related issues from many perspectives. She has managed creative teams on complex design projects, selected outsourcers for major brands and helped print organizations to retool operations, focus their market positioning and educate sales teams to accelerate growth. She works with a team of top analysts to translate experiences into tools, data and content to help print organizations evaluate the potential of inkjet, optimize their operations and grow pages profitably. She is a founding member of the Inkjet Summit advisory board, the co-author of an award-winning book on designing for inkjet and a curious consultant constantly seeking innovative ways to drive new pages onto inkjet presses.

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