In e-commerce private-domain channels such as instant messaging and e-mail, merchants engage customers directly as part of their Customer Relationship Management (CRM) programmes to drive retention and conversion. While a few top performers excel at crafting outbound messages, most merchants struggle to write persuasive copy because they lack both expertise and scalable tools. We introduce CRMAgent, a multi-agent system built on large language models (LLMs) that generates high-quality message templates and actionable writing guidance through three complementary modes. First, group-based learning enables the agent to learn from a merchant's own top-performing messages within the same audience segment and rewrite low-performing ones. Second, retrieval-and-adaptation fetches templates that share the same audience segment and exhibit high similarity in voucher type and product category, learns their successful patterns, and adapts them to the current campaign. Third, a rule-based fallback provides a lightweight zero-shot rewrite when no suitable references are available. Extensive experiments show that CRMAgent consistently outperforms merchants' original templates, delivering significant gains in both audience-match and marketing-effectiveness metrics.

AI is rapidly changing the way Hollywood functions. It revolutionizes how stories are told, how movies are made, how audiences engage with content, and more. AI has the potential to disrupt the entire movie industry, from the way producers develop scripts to the way audiences consume content. AI is already being used to help filmmakers create more engaging stories. AI-powered screenwriting tools are being used to help writers generate ideas and structure their stories.

CTV is one of digital advertising's hottest channels. Conversation on CTV tends to focus on the ability to pair TV's emotional storytelling power with granular targeting. Kalyan Lanka, VP of product management at Ampersand, argues that the same pairing of creative and targeting potential is hitting local TV. Here's how marketers can take advantage of the opportunity. Local TV inventory in general provides a great opportunity for marketers who are trying to engage with the right consumer at the right moment and within a highly engaged context.

When I first encountered A/B testing, I immediately wanted to become the type of marketer who tested everything. The idea sounded fun to me. Like being a mad scientist running experiments to prove when my work was actually "working." Turns out though, there's always a long list of other things to do first… blog posts to write, campaigns to launch, and don't get me started on the meetings! A lot of marketers are just too darned busy to follow up and optimize the stuff they've already shipped.

Factual, the location data company, today announced a significant update to its Audience product, adding Predictive and Loyalty audiences built using machine-learned predictive insights to its roster of targeting solutions for marketers. Beginning today, marketers will have access to new Predictive Audiences and Loyalty Audiences, both built on sophisticated visitation pattern analysis, which will further enable marketers to construct highly scalable and accurate audience segments based on real-world consumer behavior and designed for ROI. The company has also added more than 100 ready-to-use audience segments in every vertical, including auto, retail and QSR. Factual builds its Predictive Audiences by developing an understanding of visitors to a place category and mapping their visitation patterns beforehand. Using Factual's Observation Graph, consumers most likely to visit a category based on these patterns can be segmented into audiences, giving marketers the ability to connect with consumers before they set foot in a brand's retail location.

Sitecore Symposium 2019, Orlando, Fla. – Nov. 5, 2019 -- Sitecore, the global leader in digital experience management software, today announced Sitecore AI, a new machine learning framework that empowers marketers with predictive insights to automate the delivery of personalized digital experiences. Automated Personalization -- an add-on for the Sitecore Experience PlatformTM (XP) 9.0 and above -- is the first of the next-generation services within Sitecore AI, providing one of the industry's first solutions powered by Microsoft Azure to automatically identify visitor trends, create customer segments, and modify page elements to deliver personalized experiences. Sitecore AI amplifies the power of Sitecore XP to deliver individualized, contextual experiences that guide visitors along their journey with content that is useful and actionable. It can analyze a customer's behavior to understand their interests and intent, enabling marketers to learn about where each person is in their journey -- without the guesswork -- and determines the best content for each customer while continuously optimizing their experience, nurturing them toward conversion. "Sitecore AI helps us solve the content crisis for marketers by giving them the intelligent insights they need to optimize content creation and personalized experience delivery at massive scale," said Desta Price, executive vice president of product, Sitecore.

Hello Product Hunters, Thank you for taking the time to check out RefineAI's Audience Insights product. During my long stint in the Media industry one thing that we were not measuring well was how do our customer feel about our content. We spent millions on Market Research. But the results were rarely actionable as the content was already created. The idea for audience insights gathering using computer vision and machine learning was born from the notion that we should be able to build and test video content rapidly.

Artificial intelligence (AI) is making advertising more effective, but it's also making it more opaque. With each new layer of automation, human beings are moved one step further from the most crucial marketing decisions of any digital campaign. After all, if AI makes its own decisions about which audiences to target, how can marketing professionals be confident that they're reaching the right people? AI systems were once primarily focused on efficient bidding, but new innovations have expanded their capacity to include audience segmentation, creative optimization and ad unit design. Until brands and agencies have ways of validating AI decision-making, it will be difficult for stakeholders to trust new technologies.

With technology moving as fast as it is, we're all scrambling to stay relevant. And marketers are no exception. Every day, we're met with stories about robots taking over our jobs and AI-less businesses soon being left in the dust. And in this dramatically shapeshifting panorama, it's easy to get all shifty-eyed and assume your competitors are nailing the whole AI thing, poised to bury you. Naturally, you look for solutions to put your marketing capabilities on steroids, vowing to tap the power of AI.

Artificial Intelligence marketing is the new trend taking the marketing world by storm, but many marketers are still in the dark around how AI strategies can be leveraged in everyday marketing campaigns. With AI, marketers can sift through large amounts of data to determine patterns and trends, and thanks to AI solutions doing the'searching', there is little to no manual data analysis. Once patterns are identified, marketers can preemptively promote solutions, products, or programs to the respective audience segments. A good example of preemptive marketing comes from Netflix and their'you may also like' prompt. Netflix amalgamates viewing data and runs it through their AI programs to pinpoint similar shows or movies a viewer may enjoy.