The EPIC Framework for Agent Evaluation, Explained
A shopper is using a brand’s AI agent to find wide-fit running shoes to train for a marathon. The agent…
A shopper is using a brand’s AI agent to find wide-fit running shoes to train for a marathon. The agent…
Around 2010, one of the first major broadcasters to launch a streaming product had a problem nobody could name. The…
Twenty million people don’t open a live sports app gradually. They open it ten minutes before kickoff, all at once.…
An AI shopping agent can complete a purchase and still fail the customer. Why? Because outcome and experience are not the same metric. In this episode of Beyond The Cart, Keith Zubchevich, CEO of Conviva, discusses what e-commerce brands need to consider when deploying AI agents. Watch the full episode on YouTube and read theRead more »
Fresh off a World Cup where Conviva monitored tens of millions of concurrent streams across 20+ platforms, Conviva CEO Keith Zubchevich joined the Profluence Sports Podcast to talk about the future of live-streamed events. His main point: the Quality of Experience (QoE) discipline that built streaming can’t stop at the stream. It has to extendRead more »
SDK Integration MCP is Conviva's solution for allowing developers to guide, review and approve agents-driven Sensor SDK integrations.
Nexa, Conviva's analytics agent, is built to close the gap that's always existed in live sports streaming: speed of response to viewer issues.
AI-referred buyers convert at 3.5x the site average, and 45.5% when they ask an on-site agent about price. Conviva's A2A Commerce Report reveals the behavioral signals driving the channel.
Download the Conviva report to discover how your business can leverage the A2A acquisition channel to boost conversions and retention.
Conviva research finds that consumer-facing agents spend an average of two minutes and 32 seconds establishing basic context before they can address a customer's actual request.
Download our report today to dig into the research and discover critical insights into how consumer-facing AI agents can make or break your relationship with customers.
New data shows that two-thirds of your most valuable customers take journeys your analytics were never built to see. The implications for AI agent design — and the analytics infrastructure behind them — are significant.