Observed Signal · Sep 27, 2022 · Analysis · Source: CMSWire · Impact: 2/5 · Sentiment: Positive
Edge Computing Is the Road to Customer Experience Nirvana
Edge computing processes data closer to its source, enabling brands to react to customer engagement in real time. The article explains how edge, combined with IoT, AI, and 5G, supports hyper-personalized and omnichannel customer experiences, from real-time marketing notifications to smart checkout systems in retail. Expert quotes from IntelePeer and Silk highlight benefits such as reduced latency, resilience to outages, and new interactive experiences. Examples include Kroger's KroGo smart shopping cart and Standard AI's 'just walk out' technology. The piece also covers challenges like security and the risk of invasive notifications. Market forecasts from Gartner, Juniper Research, and Insider Intelligence are cited to project growth in edge data processing, smart checkout transactions, and IoT device adoption.
Edge computing is an enabling technology for real-time marketing and hyper-personalized customer experiences; the article aggregates expert insights and market forecasts but contains no breaking news or major industry shifts.
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Key Takeaways & Evidence Grounding
- Gartner estimated that 75% of data will be processed at the edge by 2025.
- Kroger debuted its KroGo smart shopping cart with built-in scanner and camera in 2021.
- Juniper Research predicted smart checkout transactions will reach $387 billion in 2025.
- Insider Intelligence forecast 3.74 billion IoT mobile connections by 2025 and 64 billion IoT devices by 2026.
- A Kollective report found 52% of IT leaders cited security as a key edge deployment concern.
Connected Companies & Entities
4 Entities mapped“A Gartner report estimated that by 2025, 75% of data will be processed at the edge, outside of traditional, centralized data centers and the...”
“In 2021 Kroger debuted a new self-checkout system that is self-contained on its shopping cart, called the KroGo cart....”
“Standard AI uses edge computing along with artificial intelligence to create such a 'just walk out' shopping experience....”
Ontology Mapping & Concepts
Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
Verndale Launches AI Visibility & Content Supply Chain Services
Verndale, a digital consultancy, has introduced new services to help marketers measure and improve their brand's visibility in AI-generated answers. As AI assistants like ChatGPT and Google's AI Overviews increasingly influence research and buying decisions, brands need to know whether they are mentioned, recommended, and correctly described in these responses. Verndale's services include an AI Visibility assessment that tests real audience questions across major AI platforms, identifying gaps in brand mentions and citations. They also offer an AI-Ready Content Supply Chain Assessment to optimize content operations for AI-era discoverability. The company cites research from SparkToro showing 68% of Google searches end without a click, and Gartner reporting 45% of B2B buyers use generative AI for purchase research. A case study with Quinnipiac University demonstrated significant improvements in content optimization and AI readiness through governed agent workflows.
OK Future's AI 'Pressure Cooker' Campaign for Goodwipes
Former MullenLowe U.S. CEO Frank Cartagena launched creative shop OK Future to test generative AI's potential for a small agency. Their first project, a spoof of OpenAI's Astra ad for personal hygiene brand Goodwipes, was produced in four days using AI tools like ArtCraft, Seedance, and OpenAI's Astra model, cutting projected production costs from $700,000. The campaign, 'Meet Asstra,' gained over 1.5 million views on Reddit. However, Cartagena described the pace as 'unsustainable' and a 'pressure cooker,' with team members working around the clock and even threatening to quit. Goodwipes' SVP of Marketing, Meredith Diehn, emphasized trust in Cartagena and the value of experimenting with AI. The article highlights the growing use of AI in creative production, with 73% of marketers using GenAI for visual content and Gartner forecasting AI software spending to reach $981 billion by 2029.
AI Startups Face Pricing Power Squeeze from Model Suppliers
An analysis by Trending Topics highlights a structural challenge for AI startups: they often act as token resellers with thin margins, akin to middlemen, rather than classic software businesses. Using a fictional sports app example, the piece illustrates how costs for app store fees, token consumption, and free-tier AI features can erode profits. Citing a market study, it notes inference costs average 23% of revenue for scaling AI firms, with gross margins around 52% versus 78-80% for traditional SaaS. The article discusses how providers like OpenAI and Anthropic hold pricing power, and some startups, like Cursor, invest heavily in own infrastructure to reduce dependence, though this is often not feasible for most. Neoclouds are seen as not solving the fundamental dependency issue. However, a counterview suggests that rapidly falling inference costs could improve margins, and AI-native startups have already captured significant market share in some segments. The piece concludes with strategic advice for startups to focus on proprietary data, workflow integration, and cost optimization.
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