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Chameleon Acquires Driveway to Add Interactive Demo Capabilities and Create a Cohesive Digital Adoption and Product Marketing Platform

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Chameleon Acquires Driveway to Add Interactive Demo Capabilities and Create a Cohesive Digital Adoption and Product Marketing Platform

Company to incorporate new technology and launch a “Demos” product, meeting the need of software buyers to explore products prior to sign-up and engaging users post-sign-up

Chameleon, the deepest product adoption platform for modern software companies, announced that it has acquired the cutting-edge interactive demo company Driveway. The move enables Chameleon to expand into the interactive demo category and drive user onboarding via (existing) in-product and (new) ungated walkthroughs. Driveway Co-founder Harrison Johnson will join Chameleon as Product Lead, spearheading Driveway’s integration into the Chameleon platform. Terms of the deal were not disclosed.

Chameleon + Driveway will enable companies to show off new features inside their product as well as on websites, in help docs, across social media, and more, all through one integrated platform. — Chameleon Co-founder and CEO Pulkit Agrawal

“The future of software is more self-service, more product-centric, and more personalized, inside and outside the product,” said Chameleon Co-founder and CEO Pulkit Agrawal. “Chameleon + Driveway will enable companies to show off new features inside their product as well as on websites, in help docs, across social media, and more, all through one integrated platform.”

Read More: SalesTechStar Interview with Puneet Arora, Global President, Yellow.ai

The Future of Product Marketing

The move comes as technology buyers increasingly engage in their own product research before ever speaking to a provider. It is a product-led world where people want to try a product before committing to it. Simultaneously, companies need to be more efficient in their own GTM, so product-led sales have become a strategic priority. Interactive Demos, embedded on a marketing site, or in help docs, can be a great way to showcase key product features without users needing to sign up or log in. Organizations that offer quality, user-friendly interactive demos are able to remove hurdles and expedite sales.

As Gartner® noted in its 2023 Market Guide for Interactive Demonstration Applications, “These trends have created a perfect environment for interactive demonstration applications. As GTM technology serving marketing, sales, and other functional needs, interactive demonstration applications are sometimes referred to as demo automation applications. They provide a near-product experience to prospective buyers, without the need or complexity associated with the actual product behind them — with the exception of live product overlays, which replace the need for intricate or sensitive data and integrations.”

Chameleon recognized the benefits interactive demos could provide, having used them extensively for its own GTM approach, and saw a natural fit with its own platform that enables SaaS teams to build in-app UX patterns like banners, models, walkthroughs, cards, surveys, checklists, and more – all without coding. By adding an interactive demo component, the company can deliver an unparalleled experience that extends from a buyer’s initial engagement with a company’s website or app, through adoption, deployment, and beyond as the company adds new products and features they may want to highlight. This creates a single cohesive experience that users understand and appreciate. It is also an experience that users increasingly request.

“Customers are demanding more interactive and self-serve education; product demos combined with in-app interactive product tours unlock their ability to understand and adopt features, and consequently drive growth for our business,” noted Jeff Chase, Director of Product Marketing at Vitally, a long-time Chameleon user.

“Chameleon is my go-to platform for quickly testing and building intuitive user onboarding experiences. Being able to incorporate interactive demos unlocks a whole new dimension of in-product experiences to drive self-serve product adoption and growth,” added Saad Khan, Growth Product Manager at Fivetran.

Read More: Why AI can’t make good salespeople; implementing AI into GTM processes

Why Driveway

Driveway presented an opportunity to meet better the expanding needs of the customers who already love Chameleon and use it regularly. Driveway enables users to easily capture and record key workflows in their products and then embed annotated versions of these in their marketing and help sites.

“Buyers increasingly want to see and play with the product before they ‘schedule a demo,’ so interactively showcasing product features on the marketing site is becoming the new standard for SaaS go-to-market,” said Johnson. “Driveway’s interactive demos combined with Chameleon’s platform for product adoption creates a must-have bundle for Product Marketing, Product-led Sales, and PLG.”

Driveway, backed by great product operators and investors, including Gradient Ventures, Lenny Rachitsky, Scott Belsky, Harry Stebbings, and Josh Elman, was built using a similar approach to Chameleon, making the acquisition seamless. Additionally, Driveway’s technology uses AI to help identify elements on the page, which will boost Chameleon’s ability to use page content to anchor and trigger in-app experiences.

Moving Forward

The acquisition comes amid a period of immense growth for Chameleon. Since its $13M Series A, Chameleon has increased Growth and Enterprise revenue by 5x. Customers like Salesloft, Domo, S&P Global, DHL, and Cisco have joined an impressive roster that includes Braze, Twilio, Mixpanel, and Drata. Chameleon has also expanded the capabilities of its HelpBar product to include navigation and AI-answers that customers can enable with a few clicks, as well as added more embedded patterns (Cards and Banners). The company now serves over 150 million end-users, and has delivered 400M end-user in-app experiences in the last few years.

Chameleon’s new “Demos” product, incorporating Driveway’s tech, will launch in Q3. In parallel, Chameleon will be launching an “Automations” feature that allows customers to record user onboarding journeys and re-play them on behalf of their end-users, to help overcome the ‘cold start problem.’ Driveway will continue to operate as a product and support its existing base of customers for the foreseeable future.

Write in to psen@itechseries.com to learn more about our exclusive editorial packages and programs.

Online Shoppers Face Information Overload, Lack of Personalization, According to New Report from Zoovu

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Online Shoppers Face Information Overload, Lack of Personalization, According to New Report from Zoovu

Findings come from analysis of over 6,800 descriptions, images, videos, and more on leading ecommerce product pages

Zoovu, the leading AI-powered product discovery platform,  published the Ultimate Guide to Product Detail Pages. The comprehensive report examines how some of the biggest B2C ecommerce brands sell their goods online based on in-depth analysis of more than 2,000 data points across 125 product detail pages.

Driving personalization with generative AI is the biggest opportunity for ecommerce brands to give customers the guidance they’re seeking at the scale they need to drive real, sustainable growth.

In the report, Zoovu analyzed product pages from U.S. and Canadian ecommerce brands in fashion and apparel, consumer electronics, health and beauty, furniture and home appliances, and tools and recreation.

Read More: SalesTechStar Interview with Puneet Arora, Global President, Yellow.ai

Three key findings from the Zoovu report include:

Overstuffed PDPs create friction between buyers and sellers: The average PDP contains more than 59 pieces of information about the product, including specifications, images, related products, product variations, and more. Brands are combating this trend by steering away from overly technical language and toward more benefit-driven or needs-focused content, as well as elements that guide customers in their product evaluation.

Shoppers increasingly rely on what others think of the product and the brand selling it: Over 90% of the product pages analyzed featured customer reviews and more than half (56.8%) included at least two types of social proof such as customer photos, ‘best’ tags, and certification badges. Across the 125 product pages assessed in the report, there were 13 different types of social proof.

Customers want personalization, but brands are finding it difficult to meet expectations: While more than 70% of people not only want, but expect personalized experiences when shopping online, only 16% of the product pages analyzed offered personalized experiences. The report exposes a huge gap in the last mile of the shopping journey that could turn into a massive opportunity for brands that figure out how to personalize PDPs at scale.

Read More: Why AI can’t make good salespeople; implementing AI into GTM processes

“It’s no secret that consumers, with instant access to almost unlimited information, are feeling increasingly overwhelmed, lost, and frustrated when shopping online, which is why optimizing product pages, the last mile of the buying process, is more important than ever,” said Ken Yanhs, CMO at Zoovu. “Driving personalization with generative AI is the biggest opportunity for ecommerce brands to give customers the guidance they’re seeking at the scale they need to drive real, sustainable growth.”

Write in to psen@itechseries.com to learn more about our exclusive editorial packages and programs.

New Book Digital Sales Revolution Transforms B2B Sales, Offers Blueprint for Future Success with Digital Sales Rooms

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New Book Digital Sales Revolution Transforms B2B Sales, Offers Blueprint for Future Success with Digital Sales Rooms

In the first-ever book about Digital Sales Rooms, Allego leaders offer insight into the transformative power of this revolutionary technology in B2B sales 

Yuchun Lee and Mark Magnacca, co-founders of Allego, announced Digital Sales Revolution, a first-of-its-kind comprehensive resource focused entirely on the adoption and impact of Digital Sales Rooms (DSRs) in the business-to-business (B2B) sales process.

“Digital Sales Revolution enlightens us with the essential insights B2B sellers need to succeed with current and future buyers,” said Mary Shea, PhD, Innovation Evangelist and former Forrester analyst. “This book is not merely an analytical study but a compelling roadmap to help sales leaders, sellers, and marketers navigate the shifting terrains of the digital selling universe.”

Read More: Highspot Brings AI-Driven, Personalized Coaching at Scale to Sales Enablement

Digital Sales Revolution reveals the power of key selling technologies, such as Digital Sales Rooms (DSRs), and illuminates the digital revolution that successful sales leaders, sales enablement professionals, and individual sellers need to understand and then act on. In the book, Lee and Magnacca, along with Allego Chief Product Officer Andre Black and Product Leader Ruby Kennedy, provide actionable strategies for integrating DSRs into the B2B sales process, as well as enhancing buyer engagement and improving sales outcomes.

“Just as Amazon and Netflix tailor experiences based on individual preferences, the introduction of Digital Sales Room technology heralds a new era of customer engagement for B2B sales,” said Lee, co-author and Allego CEO. “Our vision goes beyond mere automation; it’s where an efficient self-serve buyer experience meets the personal touch of a skilled seller. By seamlessly integrating content sharing and back-and-forth collaboration throughout an entire customer/client engagement, DSRs empower customer-facing teams to expedite deal cycles while fostering differentiating and authentic relationships.”

Read More: SalesTechStar Interview with Puneet Arora, Global President, Yellow.ai

Packed with insights from industry experts who have firsthand experience transforming their sales process through the successful implementation of DSRs, Digital Sales Revolution offers forward-thinking insights into the world of digital sales and the evolving B2B buying experience. The book provides a blueprint for success, explaining precisely how sales teams can use DSRs to succeed in increasingly competitive marketplaces, including:

  • Why the DSR is taking the B2B world by storm
  • How top-performing B2B sellers use DSRs to create better buying experiences
  • The key role DSRs play now in Modern Revenue Enablement and will play in the future

“In today’s B2B landscape, 65 percent of buyers initiate purchases independently, highlighting the growing importance of Digital Sales Rooms,” said Magnacca, co-author and Allego President. “This new category of technology empowers sales teams by providing the tools they need to create the tailored, self-guided buying experience today’s customers expect, collaborate with and advise buyers, and develop stronger customer relationships. By utilizing DSRs, sales and other customer-facing teams will revolutionize the way they engage with customers and buyers and close deals.”

Write in to psen@itechseries.com to learn more about our exclusive editorial packages and programs.

CallTower Unveils the Future of Operator Connect for Microsoft Teams, GTx

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CallTower Unveils the Future of Operator Connect for Microsoft Teams, GTx

GTx, powered by CallTower, revolutionizes the transactional landscape for Managed Service Providers (MSPs), System Integrators, Resellers, Distributors, and VARs by empowering them with Operator Connect for Teams, enhancing connectivity and efficiency

CallTower, a global leader in delivering unified communications, contact center, and collaboration solutions, including Microsoft Teams, Webex by Cisco, and Zoom, introduces GTx, a game-changing rebiller program designed to revolutionize the transactional landscape for Managed Service Providers (MSPs), System Integrators, Resellers, Distributors, and VARs, empowering them with Operator Connect for Microsoft Teams.

GTx stands out as a seamless, effective, and innovative tool crafted to empower partners to elevate their services, simplify operations, and unlock unparalleled growth opportunities within the unified communications sector.

Read More: CData Software Acquires Data Virtuality to Modernize Data Virtualization for the Enterprise

As a part of CallTower’s innovative rebiller program, GTx provides an all-in-one transaction tool for enhanced operational efficiency. Through GTx, partners can elevate service offerings and unlock new growth opportunities. It paves the way for deeper transformative development within the Microsoft stack.  The telecom tax, compliance regulations, and additional responsibilities are managed by CallTower.

Jessica Flannery, Director of Strategic Alliances at CallTower, exclaimed, “I am thrilled that CallTower’s partner program is meeting partners at their current stage of development. GTx is a valuable tool that enables partners to conduct transactions aligning with their requirements. We understand that partners possess diverse skill sets, with many eager to handle implementation, billing, and day 2 services. GTx is our response to fulfill this demand effectively!”

Read More: SalesTechStar Interview with Puneet Arora, Global President, Yellow.ai

CallTower’s Chief Revenue Officer, William Rubio added, “GTx is more than just a tool; it’s a powerful approach to equipping our partners with the tools, resources, and assistance necessary to thrive in today’s rapidly evolving technological sphere and enhance their clients’ Microsoft Teams Operator Connect journey.”

GTx represents CallTower’s commitment to empowering partners with the resources and support needed to thrive in a competitive landscape. By providing a platform that fosters innovation and efficiency, CallTower is dedicated to driving success for its partners and ushering in a new era of client-centric service deliver.

Write in to psen@itechseries.com to learn more about our exclusive editorial packages and programs.

Fujitsu leverages data and AI to enable Panasonic EW’s resilient supply chain management

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Fujitsu leverages data and AI to enable Panasonic EW’s resilient supply chain management

Fujitsu announced that it has developed a new system based on Fujitsu Data Intelligence PaaS, an operation platform for Fujitsu Uvance that leverages data and AI to achieve resilient supply chain management for Electric Works Company, Panasonic Corporation (Panasonic EW), and has started a full-scale operation of the new system at Panasonic EW in April 2024.

Read More: Aircall Broadens AI Capabilities, Empowering More SMBs to Nurture Relationships, Drive Performance, and Fuel Growth

The new system will integrate large amounts of data residing in more than 3000 sites, including domestic and overseas suppliers and factories across the entire organization to support decision making for business continuity. Panasonic EW, which handles electrical construction materials, manages tens of thousands of products, parts, and other information for each department, division, and location separately, using different formats of data. The introduction of the new system manages the data integration of 20 existing systems, including production, sales, inventory, and parts procurement, as well as the identification and visualization of parts with more than 200,000 parts in stock. This has resulted in increased optimization of the PSI plan and parts procurement plans at company-wide level. In addition, it also leverages the use of AI to implement accurate demand forecasting models based on data.

Panasonic EW enables dynamic and resilient supply chain management by using data to quickly respond to disasters or changes in the business environment by using AI to predict the uncertain outcomes in order to make corrective decisions.

Read More: SalesTechStar Interview with Eran Hollander, Chief Product Officer at HungerRush

Towards 2030, when the labor shortage is expected to become apparent due to the rapid decline in the working-age population in Japan, Fujitsu will support Panasonic EW in building a sustainable and resilient supply chain system and promote operational reforms to achieve high productivity that will allow them to complete similar tasks with 50% of their current man-hours. Under Fujitsu Uvance, Fujitsu will contribute to the realization of a sustainable world by providing a comprehensive view of the entire supply chain through Digital Shifts initiatives that utilize data and technology to help companies strengthen their resilience and respond to environmental and societal issues.

Write in to psen@itechseries.com to learn more about our exclusive editorial packages and programs.

SalesTechStar Interview with Juan Jaysingh, CEO at Zingtree

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SalesTechStar Interview with Juan Jaysingh, CEO at Zingtree

AI powered salestech enables B2B sellers to scale efforts and processes, but only if they are implemented with the right fundamentals; Juan Jaysingh, CEO at Zingtree shares a few tips that can help:

_____________

Hi Juan, tell us about yourself and your journey so far. Take us through Zingtree’s story and how it evolved over the years?

I’ve always been fascinated by the potential for technology to streamline complex processes and improve people’s lives. That passion has guided me throughout my career, which started in tech consulting before founding my first startup, ZeeMee, a social platform to help high school students transition to college. I then joined Universal Tennis to lead the rollout of their community platform to clubs and academies worldwide.

In 2020, I became CEO of Zingtree and focused on scaling the company as a profitable, B2B SaaS leader. Zingtree started with a simple idea — to help businesses streamline complex support issues with interactive decision trees that guide customers and agents to resolutions. Today, our AI-powered platform enables over 700 enterprises worldwide to automate support processes across all customer touchpoints.

By making it easy to build smart workflows, Zingtree empowers agents to resolve issues faster and more effectively. The platform also drives better self-service, allowing customers to troubleshoot on their own. The results are transformational — major reductions in contact volume, improvements in key metrics like average handle time and first contact resolution, and, most importantly, happier customers. We’re excited to continue innovating to make support as seamless as possible in the years ahead.

Can you discuss some of the biggest lags in modern digital CX journeys and how new-age sales tech and AI-powered platforms are enabling better experiences?

One of the biggest pain points in digital customer support today is the sheer volume of data and systems agents must navigate. Support information is often scattered across a dozen or more tools, making it incredibly difficult and time-consuming for agents to piece together the full context needed to efficiently resolve issues. This not only leads to lengthy handle times and frustrating back-and-forth, but also takes a mental toll on agents who are under immense pressure to find answers quickly.

AI-enabled platforms like Zingtree tackle this by acting as a unified front end that connects all the backend systems. By guiding agents through the optimal troubleshooting steps based on customer context, AI helps them resolve issues faster. By enabling more self-service, AI relieves the burden on agents so they can focus on higher-value work. The result is faster issue resolution, lower costs, and happier agents and customers.

Read More: SalesTechStar Interview with Kristy Schafer, Vice President of US Sales at Optable

For marketers or sales teams setting up these types of tools for the first time to drive better automated responses, what are some of the fundamentals to keep in mind?

The biggest mistake I see companies make is trying to automate support with AI before getting their underlying processes and knowledge in order. Throwing a chatbot or virtual agent at a broken process will only lead to frustrating experiences for customers and agents. Instead, the first step should always be to map out and optimize your support workflows, establish clear resolution paths for common issues, and build out a robust, accessible knowledge base.

Once you have that strong foundation, you can start to layer on AI to automate tasks within those established parameters. This way, you can be confident that the AI will follow your approved processes and not go off the rails with nonsensical or even damaging responses. It’s also essential to have a clear data integration strategy from the start, as the AI needs access to the comprehensive customer context to provide relevant, personalized support. Taking the time upfront to build out these underlying systems will pay huge dividends in the long run in terms of reliability, efficiency, and customer satisfaction.

How do you feel AI will change the overall customer experience game down the line?

When implemented thoughtfully, AI can transform customer experience. In the coming years, we’ll see wider adoption of AI tools like intelligent virtual assistants that can understand context and intent and resolve a high percentage of routine customer issues.

This will enable a larger volume of customer interactions to be handled through automated self-service, with seamless escalation paths to human agents when needed. Agents, in turn, will be empowered by AI to resolve complex cases faster. We’ll see many frustrating lags in customer journeys eliminated as AI enables quicker, more personalized resolutions across channels.

However, AI will never replace the need for human connection and critical thinking. The most successful companies will find the right balance between AI automation and agent enablement. When implemented thoughtfully, AI can augment agents’ capabilities by providing real-time insights and recommendations. But ultimately, it’s the human touch that will remain the heart of great customer service.

If you had to highlight a few top B2B SaaS brands whose end-to-end CX journey piqued your interest; which ones would you highlight here?

While Zingtree focuses on solutions for B2C companies, there are many commonalities in terms of what it takes to provide great customer service in B2B. I admire what companies like Salesforce, AWS and Atlassian do from a customer support and success perspective…

Read More: Digital Experience Tactics That Can Drive Brand Revenue

About Zingtree

Our story | Zingtree

 Zingtree’s mission to transform complex processes into clear actions for businesses around the globe.

About Juan

Juan Jaysingh is President and CEO at Zingtree, since becoming CEO in January 2020, Juan has focused on scaling and expanding Zingtree as a profitable, B2B SaaS organization working with over 700 customers worldwide.

Juan’s years of experience in tech entrepreneurship include his time at Universal Tennis, the sports tech startup behind UTR Powered by Oracle. Juan led the GTM strategy and rollout of UTR’s community platform to elite clubs and tennis academies worldwide. Juan also founded ZeeMee, a social media community platform for high school students transitioning to college. Under his leadership, ZeeMee was named to the inaugural CNBC Upstart 25 in 2017. Before ZeeMee, Juan held various technology consulting roles.

An accomplished tennis player, Juan immigrated to the United States alone at the age of 14. A chance encounter landed him full tennis scholarships to study and compete at Georgetown Prep and then at American University. Juan says passion and integrity drive his work ethic. As he likes to say, “if it’s too easy, it’s probably not worth it.” Juan and his family reside in Palo Alto, California.

AI Backed Call Analytics Systems – How they are changing Sales and After-sales

STS Staff Writer
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AI Backed Call Analytics Systems – How they are changing Sales and After-sales

AI-backed call analytics systems revolutionize communication strategies. These systems tap into artificial intelligence to extract valuable insights from phone call data. Key features like speech recognition and sentiment analysis come into play. They convert spoken words into text, decoding conversational nuances.

Call analytics systems identify patterns and trends in your customer interactions. They highlight potential areas of improvement, from agent performance to customer experience. They also predict customer behaviour, helping you proactively meet their needs. With AI at the helm, your call data becomes a powerful resource. It’s no longer just about answering calls; it’s about understanding what lies beneath them.

AI-backed call analytics systems are the future of intelligent customer service. They offer accurate, deep, and actionable insights. They take your call operations from data-rich to insight-driven. With them, your business has the tools to provide superior customer service, drive growth, and stay competitive.

How AI Backed Call Analytics Systems are Changing Sales/After Sales and Customer Support?

AI-backed call analytics systems are reshaping sales, after-sales, and customer support landscapes with actionable insights and predictive analytics. These systems decode customer interactions, deriving value from every conversation. Here’s how they are changing the game:

1. Boosting Sales Conversions:

AI systems analyze call data, identifying successful sales patterns. They offer strategic recommendations to increase conversion rates, thereby boosting sales.

2. Improving Customer Segmentation:

Through data analysis, these systems can accurately categorize customers based on their interactions. They allow for personalized engagement, enhancing customer satisfaction.

3. Predictive Analytics:

Predictive models in these systems can forecast customer behavior. This allows sales teams to make proactive decisions and close deals more efficiently.

4. Automating Routine Queries:

AI can handle basic customer queries, reducing wait times. This improves the customer experience while freeing up agents for complex issues.

5. Enhancing Agent Training:

By assessing call data, AI can provide detailed feedback for agents. It highlights areas of improvement, enhancing service quality and agent performance.

6. Sentiment Analysis:

These systems can analyze customer sentiment from calls. This helps in identifying any dissatisfaction and addressing it promptly, improving customer retention.

7. Efficient After-Sales Service:

AI-backed call analytics systems streamline after-sales services. They schedule follow-ups, handle complaints, and ensure a seamless customer journey, leading to increased loyalty.

8. Data-Driven Decisions:

These systems provide valuable insights from large volumes of call data. They enable informed, data-driven decisions, leading to more effective sales strategies and improved customer support.

Read More: SalesTechStar Interview with Kristy Schafer, Vice President of US Sales at Optable

Examples of Brands Using Call Analytics Systems

AI-backed call analytics systems are revolutionizing sales, after-sales, and customer support, offering transformative solutions for businesses. Here are five real-life brand examples showcasing this change:

1. Amazon Connect:

Amazon’s cloud-based contact center, Amazon Connect, uses AI to streamline customer service. It integrates with AWS machine learning capabilities, offering sentiment analysis, automated interactions, and detailed analytics. With these insights, Amazon boosts agent productivity, enhances customer experience, and drives informed decision-making.

2. Cisco Webex Contact Center:

Cisco utilizes AI for comprehensive call analytics in its Webex Contact Center. It offers advanced features like predictive analytics and voice recognition. Cisco uses these tools to guide agent-customer interactions and develop data-driven strategies. The result is improved service quality, increased sales conversions, and superior customer support.

3. IBM Watson:

IBM’s Watson Assistant leverages AI to handle customer interactions efficiently. It automates routine queries, reducing customer wait times. Meanwhile, its call analytics capabilities highlight areas of improvement for agents, driving superior training and performance. Watson’s ability to turn data into actionable insights enhances both sales and customer satisfaction.

4. Microsoft Dynamics 365 Customer Service Insights:

Microsoft’s Dynamics 365 integrates AI for valuable customer service insights. It analyzes call data to determine trends and pain points. Microsoft uses this information to improve customer experience, streamline after-sales service, and refine sales strategies. With AI-backed analytics, Microsoft ensures a customer-centric approach, boosting customer loyalty and retention.

5. Five9:

Five9’s cloud contact center uses AI to drive efficient customer interactions. It identifies customer sentiment and intent, helping agents personalize their approach. Moreover, Five9 uses AI for intelligent routing, ensuring customers reach the right agent faster. These features lead to reduced handling time, increased first-call resolution, and overall improved customer satisfaction.

Conclusion

AI-backed call analytics systems are catalyzing a revolution in sales, after-sales, and customer support. By harnessing the power of AI, businesses can delve into rich call data, extract invaluable insights, and drive strategic decisions. Brands like Amazon, Cisco, IBM, Microsoft, and Five9 exemplify this transformation.

They enhance customer experiences, optimize agent performance, and refine sales strategies. As technology advances, AI’s role in call analytics is set to become increasingly critical, ushering in an era of informed, effective, and customer-centric business operations.

Read More: Digital Experience Tactics That Can Drive Brand Revenue

One year into their gen AI era: retailers must scale early investments as shoppers adopt AI into their daily lives – Bain & Company

STS News Desk
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One year into their gen AI era: retailers must scale early investments as shoppers adopt AI into their daily lives – Bain & Company

  • Generative AI–powered productivity enhancements and cost savings could boost retailers’ already thin margins

  • Personalized shopping initiatives, such as AI-powered conversational shopping assistants, could increase a retailer’s revenue by 5-10%

  • AI tools for content generation, software development, and employee support can increase productivity by up to 25-40%

Retailers have had access to generative AI (gen AI) tools for more than a year now time enough for almost all to see the new technology’s undeniable power. New research from Bain & Company shows how generative AI at scale will rapidly improve productivity, easing the industry-wide pressure on margins through an array of cost savings.

“From conversational search to personalized apps, gen AI is reshaping the retail landscape in a way that is going to be even faster and more transformative than the smart phone or the internet,” said Mikey Vu, partner in Bain & Company’s Retail practice. “A year into their journey, retailers have enjoyed some early successes. It will be critical for them to scale these use cases, with a focus on ROI, to keep pace with the evolving expectations of shoppers who are rapidly incorporating generative AI into their daily lives.”

Read More: Aircall Broadens AI Capabilities, Empowering More SMBs to Nurture Relationships, Drive Performance, and Fuel Growth

Personalized shopping experiences
One highly promising use case centers on personalizing the customer experience through tools such as AI-powered conversational shopping assistants, enhanced search, and localized shopper recommendations. Bain found these use cases at scale have the potential to increase a retailer’s revenue by 5-10% overall. Underscoring this point is research from Bain showing consumers trust AI for personalized shopping recommendations more than any other use case they were asked about.

Automated marketing content generation
Retailers are likely to have experimented already with using generative AI to enhance and streamline their marketing efforts—with promising results. Bigger rewards now lie in store for executive teams that wrap these initiatives into a broader push to automate generation of marketing collateral in areas such as translation and repurposing of content, social media, and the creation of dynamic and personalized landing pages. We estimate that this broader family of use cases can deliver marketing productivity gains of 30% to 40%.

Supercharged employees
Bain estimates generative AI enhancements that reshape the way retail employees work on the front line, in warehouses, and at HQ could boost productivity up to 25%. This includes automated inventory checks and restocking alerts, and search assistants for real-time problem resolution.

The first year of the generative AI era has also caused retailers to think hard about its long-term impact. One worry is that big tech companies will muscle in on the early stages of the shopping journey, such as inspiration and curation. Another fear is of being shouldered aside by digital insurgents that are simply faster at implementing generative AI in a compelling way.

Read More: SalesTechStar Interview with Eran Hollander, Chief Product Officer at HungerRush

To fully capitalize on the promise of AI, retailers must ensure that their rollout passes tests in these three areas:

  1. Change management. Amid all this change, retailers need to note that jobs may need to be entirely redesigned, both on the front line and at the corporate level, and improvements made now should facilitate future evolution as well.
  2. Democratization. To successfully move from experimentation to scaled delivery, retailers need to put gen AI tools in the hands of all their employees, not just those in the tech department. At the same time, however, they need to centralize gen AI–related capabilities to avoid duplication of work and other inefficiencies.
  3. Talent. As best practices in gen AI implementation will often date quickly, retailers must help workers continually update their new skills in tech-related roles and across the organization by focusing on upskilling existing employees.

Write in to psen@itechseries.com to learn more about our exclusive editorial packages and programs.

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