Mobile Dev Memo Podcast

MobileDevMemo

Mobile Dev Memo is the site of record for mobile advertisers and app developers.

  1. 2 DAYS AGO

    Season 7, Episode 10: Deploying AI personalization at scale

    On this week's episode of the podcast, I am joined by Christina Augustine, the COO of Bloomreach, to discuss the rapidly evolving landscape of AI-enabled personalization in digital marketing and e-commerce. We explore how the shift from predictive models to generative agents is fundamentally changing how brands interact with consumers across multiple touchpoints. Among other things, we discuss: How agentic commerce tools will redefine the traditional customer journey beyond simple search and browse functionsWhether real-time behavioral signals can replace static cohort-based segmentation for truly individualized marketingWhat role Answer Engine Optimization will play in the future of organic discovery as search habits shiftWhy data quality remains the primary bottleneck for brands attempting to deploy sophisticated AI personalization at scaleIf conversational shopping interfaces can significantly reduce product return rates by improving consumer purchase confidenceHow marketers should balance the high cost of personalized SMS with the broader reach of email campaignsWhen the industry will transition from defensive data siloing to a more integrated cross-channel signal environmentThanks to the sponsors of this week’s episode of the Mobile Dev Memo podcast: ⁠⁠INCRMNTAL⁠⁠⁠. True attribution measures incrementality, always on.Xsolla⁠. With the Xsolla Web Shop, you can create a direct storefront, cut fees down to as low as 5%, and keep players engaged with bundles, rewards, and analytics.⁠Branch⁠. Branch is an AI-powered MMP, connecting every paid, owned, and organic touchpoint so growth teams can see exactly where to put their dollars to bring users in the door and keep them coming backInterested in sponsoring the Mobile Dev Memo podcast? Contact Mobile Dev Memo advertising. The Mobile Dev Memo podcast is available on: YouTubeApple PodcastsSpotify

    49 min
  2. 11 MAR

    Season 7, Episode 9: RecSys and internet commerce (with Michael Komasinski)

    On this week's episode of the podcast, I am joined by Michael Komasinski, the CEO of Criteo, to explore the rapidly evolving landscape of agentic commerce and the critical role of recommendation systems in the AI era. We delve into how Criteo is positioning itself as a commerce intelligence layer for AI assistants and the technical distinctions between large language models and purpose-built recommendation engines. Among other things, we discuss: Criteo's recently announced advertising partnership with OpenAIWhether agentic commerce will transition from assisted shopping to fully autonomous purchase decisions without human oversightHow recommendation systems based on purchase data outperform large language models in providing accurate product discoveryIf retailers will eventually trust AI agents to manage complex fulfillment and brand trust in conversational environmentsWhy the integration of semantic language models and high-volume reward algorithms defines the future of digital commerceCriteo GO, Criteo's automated advertising platformHow the partnership between specialized advertising technology and generative AI platforms will reshape the global discovery layerThanks to the sponsors of this week’s episode of the Mobile Dev Memo podcast: ⁠⁠INCRMNTAL⁠⁠⁠. True attribution measures incrementality, always on.Xsolla⁠. With the Xsolla Web Shop, you can create a direct storefront, cut fees down to as low as 5%, and keep players engaged with bundles, rewards, and analytics.⁠Branch⁠. Branch is an AI-powered MMP, connecting every paid, owned, and organic touchpoint so growth teams can see exactly where to put their dollars to bring users in the door and keep them coming backInterested in sponsoring the Mobile Dev Memo podcast? Contact Mobile Dev Memo advertising.

    37 min

About

Mobile Dev Memo is the site of record for mobile advertisers and app developers.

You Might Also Like