Machine Learning Africa’s AI in Retail online conference brought together a variety of speakers that each touched on AI from a different perspective.

Pieter van Eyssen, from Genesys, demonstrated the use of AI bots to sell more to the digital customer.

In my talk, which starts around 35.5 minutes in to the video below, I focused more on the foundations for the use of AI for analytics purposes.

I discussed the HALO effect of brick-and-mortar retail on online sales – the reality that omnichannel retail strategies that combine physical and online presences are more profitable than purely online stores. Location intelligence solutions that enrich existing data sets with up-to-date consumer demographics and movements are critical to reducing the historical bias that may sway survival strategies.

The CX Group’s Yugesh Frylinck covered the impact of AI on the customer experience.

Have listen and let me know what you think.

• The video is about the AI in Retail Conference 2020 hosted by Machine Learning Africa, focusing on the use of AI in the retail industry.
• The conference aims to provide insights to retail organizations about using AI, virtual reality, and other technologies to enhance customer experiences and operational efficiencies.
• The program director for the conference is Claire Mothers, owner of gadgetgirl.com and a tech journalist with experience in hosting tech shows.
• The conference agenda includes topics like using AI to predict outcomes and engage with customers in real-time, the importance of data integrity in AI preparations, and the impact of AI and virtual reality on customer experiences.
• The COVID-19 pandemic has accelerated the shift towards online shopping, with retail profit margins under pressure and increased shopping cart abandonment rates.
• The key to success in retail lies in offering personalized, contextually relevant experiences to customers across all channels.
• Genesis, the presenter, offers a solution called “Genesis Predictive Engagement” powered by AI to analyze visitor intent, predict buying interests, engage customers at the right moment, and provide options for engaging with virtual or human agents.
• A case study on Ethiopian Airlines shows significant improvements in conversion rates and customer service after implementing AI-driven engagement solutions.
• The presentation emphasizes that AI can help increase sales, enhance customer experiences, and respond effectively to the challenges posed by the pandemic in the retail sector.
• 25:07 The speaker discusses a scenario where someone with food allergies is concerned about ordering food online due to allergen concerns.
• 26:03 The individual receives a marketing email from a company called Cloud to Table related to online food ordering.
• 27:05 The Cloud to Table platform is introduced, running AI on Amazon Web Services for scalability and AI benefits.
• 29:08 The user logs in and starts adding items to their cart, and the AI detects this, providing information about the user.
• 30:10 The user contemplates whether the food contains nuts, leading to cart abandonment, and a chat offer is presented.
• 31:07 The user engages in a chat with an agent and receives assistance.
• 33:17 The AI can assist the agent by providing relevant knowledge base articles based on the customer’s query.
• 34:12 The user successfully completes the checkout, achieving the desired business outcome.
• 35:44 Gary Allemann discusses the importance of data integrity in AI and analytics for retail.
• 39:01 The differentiator in AI is the proprietary training data used, not the algorithms, and data integrity is crucial.
• 42:59 Data integrity involves bringing together internal and external data to ensure accuracy, consistency, and context in data.
• 45:16 The speaker emphasizes the importance of data literacy, auditability, and trust in data, especially with AI.
• 48:57 The final speaker, Yugesha Freylink, is introduced as a CX expert, and she will discuss AI’s impact on customer and organizational experience in CX.
• 49:49 The purpose of business is to create value that matters to customers, improving their lives and leading them to pay for it.
• AI refers to the simulation of human intelligence in machines, enabling them to think like humans and mimic their actions.
• AI is not meant to take over the world or replace human jobs; it is an enabler to help humans become smarter in delivering experiences to customers.
• Every company is becoming a technology company, driven by customer expectations for technology-focused, intuitive experiences.
• Customers expect service-related technology but still value interactions with real people.
• The AI hype cycle follows a pattern from high expectations to more realistic applications.
• Responsible AI use requires a deep understanding of customer needs and a focus on enhancing customer experiences.
• Successful AI implementation involves cross-functional teams, executive involvement, clear purposes, and measurement.
• Cybersecurity is crucial as AI depends on data; securing AI systems is essential to prevent misuse or corrupt data inputs.
• AI can play a significant role in enhancing cybersecurity by detecting suspicious behaviors and threats.
• AI can be used for both enhancing operational efficiency and improving cybersecurity, including the detection of hackers.
• The mindset of considering potential disruptions and security threats should be present from the early stages of AI and ML development.
• Cybersecurity education is crucial, both at home and in corporate settings, to protect against data breaches and cyberattacks.
• As AI becomes more prevalent, skills like critical thinking, empathy, problem-solving, and data literacy are in high demand.
• There is a need to address biases in AI systems and develop safeguards to manage and mitigate them.
• Privacy concerns related to AI and data collection are evolving, but consumer education and trust-building by companies can alleviate some of these concerns.
• The cloud offers career opportunities, especially for individuals without degrees, in various data-related roles.
• Executives should focus on data literacy to ask the right questions and interpret data effectively for decision-making.
• Practical and targeted applications of AI are currently more effective than general AI, and businesses should leverage AI for specific tasks and outcomes.
• AI is a tool, not a magic solution, and it should be used wisely and ethically.