Tag Archives: personalization

Are Traasdahl, Crisp
Retail Food Safety Forum

Is Programmatic Commerce the Next Wave in Supply Chain Tech?

By Are Traasdahl
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Are Traasdahl, Crisp

While COVID-19 exposed disconnects in the food supply chain, it also served as an overdue catalyst for rapid technology adoption. Food manufacturers, distributors and retailers were forced to grapple with consumer behaviors that—previously expected to occur over five years— changed within about five weeks. Faced with unprecedented demand, channel shifts and rapidly changing consumer purchasing behaviors, forward-looking brands and retailers have started to transform their business models to become highly responsive and agile.

A new approach called “programmatic commerce” may be the key to faster market insights and pivots. Taking cues from past attempts to digitize the supply chain from end-to-end, programmatic commerce uses artificial intelligence (AI) and machine learning (ML) to connect and unify critical business data across food manufacturers, distributors and retailers using common retail portals, BI and CRM tools as well as other data resources and platforms.

With a real-time unified view of channels and activity, programmatic commerce has the potential to create fully automated trade processes to optimize production, inventory management, logistics, promotions and more for both upstream and downstream supply chain activities.

To achieve the potential of programmatic commerce, real-time or near real-time data sources must be easily integrated, unified and displayed. This is in stark contrast to previous attempts to create end-to-end supply chain visibility, which often required custom or manual integrations, had costly and lengthy implementation requirements and necessitated custom reporting.

The programmatic approach is already gaining traction, enabling retailers to leverage AI and ML technology to optimize supply chains. But the real value is in taking it one step further—to tap into rich customer data, understand rapidly changing consumer behaviors and ultimately—to predict and personalize shopping experiences at scale.

Tracking and Adapting to Evolving Consumer Journeys

Consumers increasingly demand greater choice, control, personalization and transparency and companies must continuously create, track and manage a 360º view of customers’ shopping journeys to stay ahead of these trends. Fortunately, real-time data and analytical capabilities are available to supply the critical information they need to implement a programmatic commerce approach.

Among the shifts companies must track as a result of COVID-19 is the explosion in online grocery shopping. In November 2020, U.S. grocery delivery and pickup sales totaled $5.9 billion and a record high 83% of consumers intend to purchase groceries online again, signaling this trend continues as the pandemic lingers on.1 By 2025, online grocery sales are predicted to account for 21.5% of total grocery sales, representing more than a 60% increase over pre-pandemic estimates.2 A permanent shift toward online grocery shopping can be expected as consumers’ shopping and fulfillment experience continues to improve.

For consumers still shopping in stores, the pandemic also drove switches in primary physical store locations. In the United States, an estimated 17% of consumers shifted away from their primary store since the start of the pandemic.3 This was driven by increased work-from-home, which eliminated commuting routes and made different store locations more convenient, including ones closer to home.

Given the multitude of changes impacting consumer journeys during the pandemic, it is imperative that companies track relevant purchase drivers and considerations of each purchase occasion, while also taking into account their recent shopping experience. This creates the need for consistent, seamless and relevant experiences across both digital and physical channels that aligns all touchpoints with the consumer as part of their “total commerce experience.”

Multiple retailers are already pursuing this approach in the hope of retaining their “primary store” status across the totality of their consumers’ shopping experiences. Walmart recently launched a new store format to help achieve “seamless omni-shopping experiences” for its customers through a digitally enabled shopping environment. Customers can use the Walmart app to efficiently find what they’re looking for, discover new products, check pricing, and complete contactless checkout.4 Data tracked on these customers can eventually be used to create personalized recommendations and in-store activations and assistance based on their purchase history and in-store experience.

Conversely, the “digital store” is also being reimagined to align with consumers’ in-store experience to create a seamless shopping experience. For example, personalized meal planning service The Dinner Daily now offers the ability for its members to order recipe ingredients directly from Kroger and other Kroger-owned stores through The Dinner Daily app.5 Integrated data from multiple shopping platforms and consumer touchpoints can provide food manufacturers and retailers with shopper profiles, consumer experiences, and purchase history along with inventory status and other inputs to ultimately build personalized customer experiences and enhance shopper loyalty.

Applying Programmatic Commerce to Deliver Personalization to Consumers

Once armed with real-time data in a uniform format from sources ranging from consumer search analytics to retailer promotional pricing, a programmatic commerce approach can provide companies with predictive understanding of demand and supply to optimize decision making from raw materials through production through retail or direct-to-consumer.

Using online grocery shopping as an example, consumer personalization can be delivered through the accurate prediction and display of items relevant to each shopper based on shopping history, preferences, current cart selections, and other inputs such as real-time availability, marketing promotions and more.

Innovations are already in the market, including Halla, a data science company that developed a grocery-specific personalization algorithm that works with grocery retailer e-commerce platforms to create smart recommendations based on understanding of individual shoppers’ product usage and preferences.6 Another example is the Locai Solutions digital grocery platform, which applies AI to personalize recipe recommendations based on consumer preferences and purchase history and determines ingredients and quantities needed for easy incorporation into their shopping cart.7

The Path Ahead: Accelerating Technology Adoption in the Food Industry

AI and ML are already reducing waste across supply chains and enabling consumer personalization. However, currently only about 12% of retail decision-makers feel they are very effective at providing these experiences to customers and only 10% have access to the real-time data needed to achieve this goal.8

Modern programmatic commerce platforms (see Figure 1) can effectively bridge information gaps, improve inventory and distribution to prevent shortages or overages and help companies be data-ready to meet actual demand. Beyond this, a programmatic approach unlocks the next stage of customer satisfaction and loyalty, personalizing the experience during and after the pandemic.

Programmatic Commerce Platform visualization
Figure 1. Programmatic Commerce Platform visualization. (Courtesy of Crisp)

References

  1. Bishop, D. (2020). Tracking Online Grocery’s Growth. Brick Meets Click.
  2. Mercatus. (2020). The Evolution of the Grocery Customer.
  3.  Briedis, H., et al. (2020). Adapting to the next normal in retail: The customer experience imperative. McKinsey & Company.
  4. Whiteside, J. (2020). Reimagining Store Design to Help Customers Better Navigate the Omni-Shopping Experience. Walmart.
  5.  Corke, R. (2020). Our Online Ordering Connection for Kroger is Here. The Dinner Daily.
  6.  Halla. (2016). Halla Grocery Solutions.
  7. Locai. (2018). Locai Meal Planning.
  8. Bluecore. (2019). Align Technology, Data, And Your Organization to Deliver Customer Value.

 

Sasan Amini, Clear Labs

2020 Expectations: More Artificial Intelligence and Machine Learning, Technology Advances in Food Safety Testing

By Maria Fontanazza
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Sasan Amini, Clear Labs

2018 and 2019 were the years of the “blockchain buzz”. As we enter the new decade, we can expect a stronger focus on how technology and data advances will generate more actionable use for the food industry. Food Safety Tech has highlighted many perspectives from subject matter experts in the industry, and 2020 will be no different. Our first Q&A of the year features Sasan Amini, CEO of Clear Labs, as he shares his thoughts on tech improvements and the continued rise consumer expectations for transparency.

Food Safety Tech: As we look to the year ahead, where do you see artificial intelligence, machine learning and blockchain advancing in the food industry?

Sasan Amini: AI, ML, and blockchain are making headway in the food industry through advances in supply chain management, food sorting and anomaly detection, and tracing the origin of foodborne outbreaks. On the regulatory side, FDA’s focus on its New Era of Smarter Food Safety will most likely catalyze the adoption of the above mentioned technologies. On the private side, a few of the companies leading the charge on these advancements are IBM and Google, working in partnership with food manufacturers and retailers across the world.

Along those same lines, another area that we expect to grow is the use of AI and ML in tandem with robotics—and the value of new troves of data that they collect, analyze and distribute. For example, robotics for the use of environmental monitoring of potential contaminants, sorting techniques and sterilization are valuable because they ensure that end products have been through thorough testing—and they give us even more information about the lifecycle of that food than ever before.

At the end of the day, data is only valuable when you can transform it into actionable insights in real-time with real-world applications, and we expect to see more and more of this type of data usage in the year ahead.

FST: Where do you think food safety testing technologies will stand out? What advancements can the industry expect?

Amini: In 2020, technology is going to begin to connect itself along the entire supply chain, bringing together disparate pieces and equipping supply chain professionals with action-oriented data. From testing advances that improve speed, accuracy and depth of information to modular software solutions to promote transparency, the food safety industry is finally finding its footing in a data-driven sea of technological and regulatory advances.

Right now, legacy testing solutions are limited in their ability to lead food safety and quality professionals to the source of problems, providing insights on tracking recurring issues, hence having a faster response time, and being able to anticipate problems before they occur based on a more data heavy and objective risk assessment tools. This leaves the industry in a reactive position for managing and controlling their pathogen problems.

Availability of higher resolution food safety technologies that provide deeper and more accurate information and puts them in context for food safety and quality professionals provides the food industry a unique opportunity to resolve the incidents in a timely fashion with higher rigour and confidence. This is very in-line with the “Smarter Tools and Approaches” that FDA described in their new approach to food safety.

FST: How are evolving consumer preferences changing how food companies must do business from a strategic as well as transparency perspective?

Amini: Consumers are continuing to get savvier about what’s in their food and where it comes from. Research suggests that about one in five U.S. adults believe they are food allergic, while only 1 in 20 are estimated to have physician-diagnosed food allergies. This discrepancy is important for food companies to consider when making decisions about transparency into their products. Although the research on food allergies continues to evolve, what’s important to note today is that consumers want to know the details. Radical transparency can be a differentiator in a competitive market, especially for consumers looking for answers to improve their health and nutrition.

Consumers are also increasingly interested in personalization, due in part to the rise in new digital health and testing companies looking to deliver on the promise of personalized nutrition and wellness. Again, more transparency will be key.

FST: Additional comments are welcome.

Amini: Looking ahead, we expect that smaller, multi-use, and hyper-efficient tools with reduced physical footprints will gain market share. NGS is a great example of this, as it allows any lab to gather millions of data points about a single sample without needing to run it multiple times. It moves beyond the binary yes-no response of traditional testing, and lets you get much more done, with far less. Such wealth of information not only increases the confidence about the result, but can also be mined to generate more actionable insights for interventions and root cause analysis.

This “multi-tool” will be driven by a combination of advanced software, robotics, and testing capabilities, creating a food safety system that is entirely connected, driven by data, and powerfully accurate.