Here’s Why Taco Bell Added Artificial Intelligence Technology To Its Mobile App

  • “Artificial intelligence was identified by a number of restaurant tech providers as a top trend for 2020 and, so far, those predictions seem pretty spot on. 
  • Taco Bell is making its case for AI, announcing a broader partnership with Certona
  • Through the technology, machine learning derives the most relevant menu items for app users and also pushes promotions and content based on an individual customer’s behavior.
  • Last week, Starbucks President and CEO Kevin Johnson told the National Retail Federation Show crowd about the company’s Deep Brew (AI) technology, calling it a “key part” of Starbucks’ future.”

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AI and Dark Stores among key e-commerce trends to watch out for in 2020

“Deeper AI Integrations: From automated chatbots to image recognition and personalization, Artificial Intelligence is expected to play a larger role in mcommerce.

AI and ML will see a greater play in Ecommerce

Here are top expected applications of AI in Ecommerce:

• Personalized User Journeys

• Predictive Product Recommendations

• In-store Insights & Customer Engagement

• Dynamic Pricing

• Predictive Behavior Modeling

• Visual Search”

A Bank That Doesn’t Embrace AI Will Not Be Relevant to Younger Generations, Says Exec

  • “Traditional banking is being challenged by companies like Google, Amazon, and Facebook, who now offer financial services as well, Basson said.
  • If the first generation of AI in banking was mostly about efficiency, now it is also about leveraging data into insights that could be used to improve customer experience”

The Future Of E-Commerce

“Future of E-commerce Experience

1. The E-commerce Experience will Transcend The Screen.

2. The E-commerce Experience will be More Personalized.

3. The E-commerce Experience will Include a Lot More Relevant Content.

4. The E-commerce Experience will Shift Toward Better Service and Elevate the Shopping Experience.”

The AI stack that’s changing retail personalization

“With the sheer amount of products being sold online, shoppers primarily discover products through category or search-based navigation. However, inconsistencies in product metadata created by vendors or merchandisers lead to poor recall of products and broken search experiences. This is where image recognition and machine learning can deeply analyze enormous data sets and a vast assortment of visual features that exist in a product to automatically extract labels from the product images and improve the accuracy of search results.”