Walmart has become the first retailer to scale its drone delivery to five states with its recently announced service expansion in Atlanta, Charlotte, Houston, Orlando and Tampa. The new service will launch at 100 stores throughout Arkansas, Florida, Georgia, North Carolina and Texas, in addition to current operations in Northwest Arkansas and the Dallas-Fort Worth area. Walmart is continuing its partnership with Wing as it expands the delivery service. Wing operates within FAA guidelines and flies its drones within up to a 6-mile aircraft range from any given store. “As we look ahead, drone delivery will remain a key part of our commitment to redefining retail,” said Greg Cathey, SVP, Walmart U.S. transformation and innovation. “We’re pushing the boundaries of convenience to better serve our customers, making shopping faster and easier than ever before. This expansion of our drone delivery service marks a significant milestone in that journey, enhancing our delivery offerings with a focus on speed.”
Nectar Social’s agentic platform for social commerce listens in real-time, surfaces nuanced insights and attributes engagement to revenue across the funnel to deliver >12% campaign conversion rates vs 1-3% for traditional channels
Nectar Social, the agentic social commerce platform for disruptor brands, today announced its emergence from stealth with $10.6 million in combined pre-seed and seed funding co-led by True Ventures and GV (Google Ventures). Nectar steps in as the embedded agent built for today’s commerce—listening in real time, surfacing actionable insights, attributing engagement to revenue, and much more. Nectar is more than a platform—it’s the teammate every brand needs. It listens to customer feedback in real time, surfaces nuanced insights brands didn’t know to ask for, and engages automatically in the moments that matter most in an authentic way. Nectar is built for the way people actually shop now—starting from social platforms. OLIPOP, Jones Road Beauty, and Solawave are among the many businesses leveraging Nectar to unlock the potential of AI and drive greater impact with their teams, with customers achieving >85% AI-assisted responses within 30 days and seeing social DM campaigns deliver >12% conversion rates compared to 1-3% for traditional channels. Early customers have generated six figures of revenue, with some experiencing a 150% lift in engagement rates and 50% increase in content impressions after implementation. How Nectar Transforms Social into a Revenue Channel: Grow and manage communities with social copilot agents; Real-time insights and listening across brand and influencer; Full funnel revenue attribution and selling in DMs.
Xnurta unveils AI reporting agent to accelerate speed-to-insight for Amazon Ads
Xnurta, the agentic AI-powered advertising platform, today announced the launch of its latest AI innovation: the Xnurta AI Reporting Agent. “The Xnurta AI Reporting Agent automates the reporting process using deep research,” said Kashif Zafar, CEO of Xnurta. “Our 20,000-plus client profiles give us a unique view on which insights matter to brands and agencies. With our AI Reporting Agent, you can generate an in-depth, customized report in minutes rather than hours, so brands and agencies can focus on higher-value work like analyzing results and building strategy.” Key Features and Capabilities: Time Efficiency, Comprehensive Data Analysis, Multi-Format Reporting, Transparency & Accuracy. Xnurta’s AI Reporting Agent flips the script, serving up actionable insights without the fluff. It’s the kind of tool that lets you focus on strategy, not spreadsheets. Use Cases: Automated Performance Reports: Produce branded, presentation-ready reports in minutes with key metrics like ROAS, ACOS, CTR, CVR, CPC, etc., tailored by prompt. Instant Audits for New or Prospective Clients: Agencies can quickly generate full account diagnostics with just account access to produce stand-out recommendations. Campaign Wrap-Up Summaries: Turn post-event performance into clear, visual reports benchmarked against past campaigns with just a few clicks.
Magnite integrates Anoki ContextIQ Platform and AI Copilot to bring scene level targeting to CTV, analyzing scene content, sentiment, and brand safety
Magnite announced the integration of Anoki ContextIQ, the industry-leading multimodal AI platform for contextual video intelligence at scale. As the first SSP to adopt ContextIQ, Magnite is helping bring the benefits of the platform and its AI copilot to CTV advertising. The collaboration unlocks exclusive access to ContextIQ through Magnite SpringServe, giving buyers access to scene-level contextual targeting and planning tools. Anoki ContextIQ is a purpose-built AI engine that analyzes scene content, sentiment, and brand safety in CTV environments. Integrating the technology within Magnite SpringServe helps unlock greater transparency for buyers and resonance with the scene and emotions ahead of the ad break. This allows campaigns to be aligned with content and helps unlock the full potential of scene-level buying. Publishers can gain deeper insight into the contextual value of their content, helping them to surface high-value inventory that aligns with brand objectives, improves yield and unlocks new monetization opportunities. Kristen Williams, SVP, Partnerships at Magnite said “By embedding AI-powered scene analysis into our CTV stack, we’re equipping advertisers with smarter, more scalable tools to reach their audiences in the most relevant moments, all while maintaining transparency and control. ContextIQ leverages multimodal AI to capture the full emotional, visual, and auditory context of every scene. That allows publishers and advertisers to unlock more precision, brand safety, and emotional resonance in CTV.
Starbucks is leveraging location-based marketing technology from Radar to send promotions of specific drink discounts or other deals via push-based text notifications to customers when they are near one of its stores
Starbucks Coffee Company is personalizing mobile promotions to customers as they approach stores. The coffee giant is leveraging location-based marketing technology from Radar to send promotions of specific drink discounts or other deals via push-based text notifications to customers when they are near one of its stores. Typically, the discount is personalized to match the customer’s favorite drink based on their purchase history. Location-based marketing is core to the Starbucks mobile marketing strategy, and has helped the company maintain one of the most engaged customer bases in the quick-service restaurant vertical and second place in the 2025 Brand Finance annual report of the world’s 25 most valuable restaurant brands. The Starbucks app is the industry leader in active usage, with 48% of US restaurant app users surveyed by The Manifest saying the Starbucks’ app is the one they most regularly use. In addition, 34.3 million of the retailer’s U.S. reward members made up nearly 60% of their U.S. sales as of the first quarter of 2024. Other app features include the ability to place orders for DoorDash delivery from local Starbucks stores within the Starbucks app in the U.S. and most of Canada.
Startup Rime’s text-to-speech model can quickly generate “infinite” new voices of varying genders, ages, demographics and languages just based on a simple text description of intended characteristics; while incorporating social context, individual speech habits and non-verbal conversational cues
Startup Rime is tackling this challenge with Arcana text-to-speech (TTS), a new spoken language model that can quickly generate “infinite” new voices of varying genders, ages, demographics and languages just based on a simple text description of intended characteristics. The model has helped boost customer sales — for the likes of Domino’s and Wingstop — by 15%. Rime’s multimodal and autoregressive TTS model was trained on natural conversations with real people (as opposed to voice actors). Users simply type in a text prompt description of a voice with desired demographic characteristics and language. Rime’s Mist v2 TTS model was built for high-volume, business-critical applications, allowing enterprises to craft unique voices for their business needs. “The customer hears a voice that allows for a natural, dynamic conversation without needing a human agent,” said Lily Clifford, Rime CEO and co-founder. Rime’s model generates audio tokens that are decoded into speech using a codec-based approach, which Rime says provides for “faster-than-real-time synthesis.” Rime’s data incorporates sociolinguistic conversation techniques (factoring in social context like class, gender, location), idiolect (individual speech habits) and paralinguistic nuances (non-verbal aspects of communication that go along with speech). Rime intends to give customers the ability to find voices that will work best for their application. They built a “personalization harness” tool to allow users to do A/B testing with various voices. After a given interaction, the API reports back to Rime, which provides an analytics dashboard identifying the best-performing voices based on success metrics. Another KPI customers are maximizing for is the caller’s willingness to talk to the AI. They’ve found that, when switching to Rime, callers are 4X more likely to talk to the bot.
Walmart bets on AI assistant Sparky to ignite sales
Walmart is expanding its AI offerings by introducing a new shopping assistant. Customers can now access the Gen AI-powered “Sparky” on the Walmart app. “Sparky helps customers search to find items, synthesize reviews, and offers insights to prepare for any occasion — from looking up current sporting events and finding the right jersey to planning celebrations and picking out the perfect toy,” Walmart said. In addition to making recommendations, Sparky also provides instant and comprehensive answers to product-related questions, helping customers quickly understand specific features, compare items and make informed choices. Soon, Sparky will do even more — giving customers the power to customize their experience, from automatically reordering household essentials to booking services that simplify even the most complex shopping tasks. Walmart said the assistant will be multi-modal (able to understand text, images, audio and video), “seamlessly weaving into customers’ lives to unlock instant access to the products and services they need, whenever and however they shop.”
HubSpot’s ChatGPT connector can help marketers find the highest-converting cohorts from their recent contacts and create a tailored nurture sequence to boost engagement while ensuring role-based data access
HubSpot is the first CRM to launch a deep research connector with ChatGPT. HubSpot customers who have admin controls can enable the connector for their organization by going to ChatGPT and turning on the HubSpot deep research connector function, selecting HubSpot as a data source, and authenticating their account. From there, any user in the organization can toggle it on, sign in, and start asking questions. In addition to being easy to use, the HubSpot deep research connector is also easy to trust. We built it to ensure users only see the CRM data they’re allowed to access in HubSpot. For example, individual sales reps will only see pipeline data for deals they own or manage. With the HubSpot deep research connector, customer data is not used for AI training in ChatGPT. Within ChatGPT, for example: Marketers can ask “find my highest-converting cohorts from recent contacts and create a tailored nurture sequence to boost engagement,” then use the insights to launch an automated workflow in HubSpot. Sales teams can find new opportunities by asking, “segment my target companies by annual revenue, industry, and technology stack. Based on that, identify the top opportunities for enterprise expansion,” then bring them back to HubSpot for prospecting. Customer success teams can say, “identify inactive companies with growth potential and generate targeted plays to re-engage and revive pipeline,” then take those actions in HubSpot to drive retention. Support teams can say, “analyze seasonal patterns in ticket volume by category to forecast support team staffing needs for the upcoming quarter,” and activate Breeze Customer Agent in HubSpot to handle spikes in support tickets.
Walmart’s Sparky helps customers search to find items, synthesize reviews, offers insights, instant and comprehensive answers to product-related questions
Walmart is expanding its AI offerings by introducing a new shopping assistant. Customers can now access the Gen AI-powered “Sparky” on the Walmart app. “Sparky helps customers search to find items, synthesize reviews, and offers insights to prepare for any occasion — from looking up current sporting events and finding the right jersey to planning celebrations and picking out the perfect toy,” Walmart said. In addition to making recommendations, Sparky also provides instant and comprehensive answers to product-related questions, helping customers quickly understand specific features, compare items and make informed choices. Soon, Sparky will do even more — giving customers the power to customize their experience, from automatically reordering household essentials to booking services that simplify even the most complex shopping tasks. Walmart said the assistant will be multi-modal (able to understand text, images, audio and video), “seamlessly weaving into customers’ lives to unlock instant access to the products and services they need, whenever and however they shop.”
Walmart optimizes social customer engagement with HGS AI and automation technology for filtering and tagging social media mentions, analytics and to reply to and engage with more customers online
Walmart Inc. is effectively managing millions of mentions per year across disparate social media networks. Part of the volume is generated by local Walmart store pages on Facebook, where the retailer wants the customer experience to match that of their neighborhood store. Walmart turned to AI-based business process improvement platform provider HGS to help improve its end-to-end social customer care, brand-building, and customer engagement. HGS provided Walmart with AI and automation technology for filtering and tagging social media mentions, analytics, a crisis management solution coordinated with a public relations firm, and a customizable social media management platform to reply to and engage with more customers online. In addition, Walmart was able to leverage a team of HGS social brand ambassadors, and a social media playbook. As a result, Walmart saved more than $12 million by filtering non-actionable mentions via enhanced automation and AI. The retailer also obtained more than 1.2 million customer insights, removed more than 220,000 spam mentions (such as hate speech and bullying), engaged 180,000 customers with personalized responses across four social media platforms, and generated 200,000 e-commerce site visits from reactive comments.