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.
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.
Afterpay claims its customers are being asked to close BNPL accounts by banks to qualify for a mortgage and later offered a credit card upon qualification in a bid to protect decline in interest-yielding credit card debt
Some customers of Australia’s Afterpay have been asked to close buy-now-pay-later accounts to qualify for a mortgage and offered a credit card upon qualification, the BNPL provider said, underscoring fierce competition in the consumer finance sub-sectors. Afterpay claimed banks were capitalising on a perception of BNPL users as riskier than traditional borrowers to protect a declining lending category. Australian interest-accruing credit card debt is down 30% in half a decade as borrowers seek cheaper options. The company added that its survey found BNPL users had credit scores and on-time repayment records broadly in line with credit card users. The BNPL model has avoided regulation under Australian consumer credit laws so far as it doesn’t involve interest. However, “if it looks and acts like credit, then it should be regulated as such,” the Australian government had said last year. New legislation requiring BNPL firms to run credit checks on borrowers kicks in on Tuesday, which, Afterpay’s Head of Public Policy Michael Saadat hopes, would improve transparency around user creditworthiness. The main reason Afterpay customers close their accounts is because their lender or broker told them to, and “this should not be something that is driven by misperception of the regulatory requirements,” Saadat told.
Ratio is the only platform that combines embedded BNPL with a fully integrated Quote-to-Cash system for B2B subscription businesses
Ratio announced the launch of its Custom Payment Terms feature, which enables sellers to tailor financing options to match each buyer’s cash flow needs—without sacrificing upfront revenue. This release comes as Ratio reports over 800% growth in the past 12 months and adds Taxwell (also known as Drake Software) as a marquee customer. Ratio is the only platform that combines embedded Buy Now, Pay Later (BNPL) with a fully integrated Quote-to-Cash system for B2B subscription businesses. Ratio enables Taxwell to configure fully customized payment terms that align with the needs of its customer base—primarily SMBs—while maintaining full control over billing, renewals, and revenue collection. By integrating Ratio into its sales and finance workflows, Taxwell can manage deals end-to-end with greater speed and accuracy, reduce operational friction, and improve both buyer experience and cash flow. Ratio’s new Custom Payment Terms solution includes: Fully configurable schedules – Offer monthly, quarterly, deferred, or custom terms; Upfront cash flow – Sellers receive full contract value immediately; Modular Quote-to-Cash process – Unified quote-to-checkout-to-subscription experience inside CRM and billing workflows, configurable as a complete end-to-end flow or as a modular layer within your existing stack.
Starbucks is rolling out OpenAI-powered gen AI assistant to help baristas with quick and accurate answers to questions such as making an iced shaken espresso or troubleshooting equipment errors
Starbucks is set to roll out a generative artificial intelligence assistant, “Green Dot Assist,” to 35 locations in the US and Canada as part of its strategy to simplify baristas’ jobs and speed up service in its cafes. The technology, developed with Microsoft Azure’s OpenAI platform, will be used by baristas to answer questions such as making an iced shaken espresso or troubleshooting equipment errors. The company’s CEO, Brian Niccol, has emphasized the importance of quick, accurate answers to barista questions to help revive its sluggish US sales. Starbucks is expanding its relationship with Microsoft after the tech giant’s CEO, Satya Nadella, stepped down from the board of directors. The company’s partnership with Microsoft includes a grounding engine to ensure the accuracy of the information provided. Other restaurant companies have also been exploring AI to simplify their workers’ jobs and improve operations, such as Yum Brands partnering with Nvidia for AI order-taking and restaurant performance assessments.