Nancy Roberts

Excited to share that Aperiam has invested in Newton Research’s oversubscribed $9M Series A, alongside Greycroft, Bessemer Venture Partners, S4S Ventures, and LiveRamp Ventures. Newton is redefining what agentic AI can do for marketing analytics, enabling brands and agencies to: - Run customer 360 journey analysis across touchpoints - Segment audiences and build predictive models - Automate attribution, incrementality, and media mix modeling - Generate dynamic, natural language-driven reporting - Save up to 126 hours/month and achieve 10x analytics output Their pre-built “blueprints” let non-technical teams securely run advanced analytics on their own data with just a few clicks. John Hoctor, Matthew Emans, and Steven Bennett have successfully built and exited multiple companies. We love to back repeat founders on their most ambitious ideas, like Newton Research. Link to more in comments.

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AI is completely transforming how we work, but one of the biggest challenges I hear from other CMOs and business leaders is connecting different tools and solutions. I’m super excited about the launch of Gemini Enterprise, which brings all your company's data, tools, and people together in one secure place. Gemini Enterprise is bringing the full power of Google AI to everyone at work. Especially at big companies like ours, AI has incredible power to help us find information across internal documents, unlock new insights from our data, and deploy helpful agents that understand the context of our work and can help us get things done more efficiently. These tools are already saving thousands of hours on our team, and the boost to productivity and collaboration is helping unlock epic new ideas, move at the speed of culture, and drive real results. This is just the beginning, and I’m so excited to see what new campaigns are born with these new tools! 🪄 Congrats to Thomas Kurian, Alison Wagonfeld and the team on the amazing launch. Read more about what we announced → https://lnkd.in/gqiY-USZ

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AI has created an inflection point for nearly every tech company. The question is always the same: How do we actually monetize AI when our systems weren’t built for usage or this scale? At Metronome, we’ve seen the same pattern again and again. Products are evolving quickly, customers are adopting AI and usage-based features daily, but pricing and billing can’t keep up. Launching a new model still takes months. Even small experiments get bogged down by out-dated or homegrown software, and product, GTM, and finance end up stuck in a constant tug-of-war. That’s why we created the Monetization Operating Model: a practical framework on how leading companies are breaking through these constraints. It’s about rethinking pricing and billing as a system, not a one-off or bolt-on project, and showing how to operationalize monetization across the company and teams. If you’re figuring out how to price AI, how to add usage to your existing subscriptions, scale usage-based models, or future-proof your monetization stack, give it a read. I’d love to hear how your team is approaching it. Link in comments (don't worry, it's not gated) 👇 Get the whitepaper: http://bit.ly/3UMUWkB

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We hosted another Executive Marketing Roundtable in Seattle yesterday - Prepping for AI Search: The Rise of GEO - with marketing leaders from $100M+ revenue companies. Tight agenda, great food, and plenty of insights (plus some fun). Few insights from our discussion: ✅  PR, UGC & Topical Authority Drive AI Search Wins – Third-party mentions, high-quality PR, and strong topical authority significantly improve visibility and citations in LLM platforms ✅  Entities & Freshness Are Key Ranking Factors – AI Search increasingly prioritizes entity-based content mapping and fresh updates, especially on platforms like Perplexity ✅  GEO is the Local SEO of AI – Like Local SEO optimizes for maps and local listings, GEO optimizes for AI-generated answers across ChatGPT, Google AI Overviews, Perplexity, etc. ✅  Visual & Multimodal Content Rising – Infographics, videos, and multimodal assets are gaining weight in AI Search rankings, offering a competitive advantage ✅  AI Content Has Limits – AI can scale awareness content but is less effective at driving conversions; human-led, high-intent messaging remains crucial Super thankful to all who attended - Kate Rundell (Amazon), Lucas Welch (Highspot), Jackie Johanson (Capgemini Invent), Jake Milstein (Contrast Security), Michella C. (Congo Brands), Bala Vishwanath (SeekOut), Melody Peng (ex- Avalara), Michael Merwin (MacDonald-Miller Facility Solutions), Rekha Thomas (ex-Seismic), Marina Resto Black, Anirudh Singla There is no looking back when your attendees say this - "This is the best event in terms of value and organisation that I have been to, in recent times" Lot more coming up from Pepper. Stay Tuned :) Pepper Content #AI #GEO #SEO #AEO #AISearch #AIinMarketing

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The recent MIT report that 95% of generative AI pilots are failing to deliver ROI set off alarm bells across the tech industry. At Upwork, we were not surprised to see this data. We hear from our customers every day how they struggle to capture value from AI, and increasingly rely on skilled talent on our platform to solve this. We’ve seen what separates the companies making AI work from those that stall out. The winners? They stop treating AI like a one-time experiment and embrace it as a new way of working, requiring new approaches and new talent models to support it. Two tips I’d offer any company that has a stalled-out AI implementation: 1) Don’t design a new system just to accommodate AI. It has to work for humans too. AI technology is incredible, but too often, it isn’t enough on its own, and doesn’t fill a “worker-sized” shape in an organization. Often it can do both more and much less than your typical colleague. Our clients—from the Fortune 100 to fast-moving startups—are finding the most success when they rethink both processes and talent to incorporate the right combo of humans (who bring vision, problem-solving, curiosity, judgement and taste) working together with AI tools. That’s where the ROI lives. 2) Refresh your talent strategy to meet the AI moment. The talent you need to get an AI experiment or prototype off the ground might not be the same talent you need to scale, maintain or tune the approach over time. We see successful companies rethinking the workforce they need to capture AI value. Deploying contingent workers and teams, including freelancers, gives them faster learnings and makes an immediate impact on workflows. They can train and upskill FTEs as part of implementation, before rotating to the next project or the next company. Approximately half of businesses (49%) are turning to freelancers on platforms like Upwork to address critical skill gaps, because this talent is more highly skilled in emergent technologies like AI. This MIT report is a necessary reminder that AI implementations don’t just happen overnight—after all, this is science, not magic. The companies that invest in adapting their workflows and talent models to meet this moment are already leading the next era of innovation. I’d love to hear your thoughts on the study and what techniques are enabling you to capture AI ROI in the comments. #AI #FutureOfWork #DigitalTransformation

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