Whether they meet customers online, offline, or in some combination, retailers share a big problem: How can they offer the right choices, when and how the customer wants, without overwhelming (and often losing) the buyer?

More than anything, this is an information problem. As such, it’s a good candidate for using artificial intelligence (AI) for greater success. Here’s how Richemont tackled the problem.

Richemont owns a portfolio of leading luxury goods brands, recognized for their distinctive heritage, craftsmanship and creativity. It has strengths and specialties in jewelry (Cartier, Van Cleef & Arpels), luxury watches (IWC, Jaeger-LeCoultre, Panerai, Vacheron Constantin), and fashion & accessories (Chloé, Montblanc, dunhill).

People shop for such goods in a number of ways, from online searching to individual meetings in boutiques, and Richemont must be prepared for every context. Understanding which shoppers are likely to buy or repurchase, when to engage directly, and what creation to suggest enables sales associates to spend quality time with clients, engaging at the right time with meaningful advice. Richemont solves these retail challenges with an integrated Client Platform leveraging Google Cloud and its AI/ML capabilities.

Enticing peoples’ desires with Machine Learning

Richemont began by posing two questions:

1. Which prospects or clients need extra attention? Specifically, who is likely to convert or to repurchase?
2. What would be meaningful items to suggest to each client and prospect?

Both questions were addressed with machine learning algorithms. Their challenges included deploying and monitoring algorithms at scale for several brands across the globe, while addressing the specific business needs for each brand. For instance, it may be more relevant to recommend in-season items for fashion brands, while for watchmakers it is more about cross-fertilization across each brand’s iconic creations.

This graph summarizes the prediction process implemented by Richemont:

Engagement data (email opened, clicked, SMS/MMS, website visits…) was found crucial to predict conversion of prospects for whom per definition no transaction history is available. For website interactions Richemont leverages the Google x Salesforce Connector.

To deploy the Machine Learning algorithms and to monitor them, Richemont leveraged Vertex AI, along with BigQuery, Cloud Functions and Google Storage, all orchestrated with Google Cloud Composer.

The role of product recommendation algorithms

Richemont used the deep learning library TensorFlow Recommenders to perform the product recommendation tasks. This library enables companies to build state of the art deep learning algorithms to achieve relevant and robust predictions.

Unlocking client value with integrated technology

Richemont’s innovations show how technology that considers many parts of the customer experience creates more value. In this case, the company used in store applications to invite people with a strong propensity to buy for boutique visits, while others at a different point in the purchasing journey were offered different options more suited to their tastes and inclinations.This solution, now deployed across 11 brands in over 25 countries, shows just one way that AI can improve customer experience, for better customer loyalty.

Key to the process, here and elsewhere, is the way a retailer and its partners put customer understanding at the center of the process. As AI becomes more important not only in retail, but in every industry, this human understanding will become even more important as a fundamental organizing principle. Much is changing, but once again, the winners will be the companies that focus best on their customers.

Last week we announced the private preview of Duet AI for Google Cloud, an always-on AI collaborator that uses generative AI to provide help to developers and cloud users. This article gives you a detailed look at Duet AI for developers, showing how Duet AI can help provide developers with real-time code suggestions, chat assistance, and enterprise-focused customization. You can sign-up here to join our waitlist for Google Cloud’s AI trusted tester program.  

We believe that addressing these use case​​s with large language models (LLMs) will usher in a major leap in productivity in enterprise development. Duet AI uses Codey, a family of code models built on PaLM 2. 

Developers continuously seek ways to improve their productivity and, over the past few decades, these efforts have resulted in massive productivity leaps due to technological changes. From advanced debuggers and online developer communities, to modern IDEs/notebooks and cloud computing, each advance brought massive changes in productivity. Despite these improvements, developers still face numerous challenges, some of which are unique to cloud development:

• Disruptive context switching and friction when integrating a new tool or service
• Excessive time spent on repetitive tasks
• Time required to understand a new code base or project
• Large cognitive workload when working on large code bases or complex APIs

Duet AI for developers focuses on challenges and tasks across the development lifecycle:

Code/Boilerplate Generation — Developers can describe the tasks they have in mind as a comment or function name, such as creating a Cloud Pub/Sub topic. Duet AI will generate a reference implementation that can be reviewed and modified, so developers don’t need to spend time reading through multiple documentation pages.

Inline Code Completion — To reduce the time spent on repetitive tasks and minimize the cognitive workload of tasks such as writing repetitive code or retrieving variable names, Duet AI provides intelligent, context-aware code completion, helping reduce the time spent on coding and enhancing the quality of the written code.

Enterprise Customization — Organizations frequently have massive code bases and specific recommended frameworks and best practices, which generic code assistance solutions may not be best positioned to support. With Vertex AI, developers will be able to tune and customize the underlying models and connect them to the Duet AI experience, allowing for assistance optimized to the needs of the organization.

Code Explanation — Developers spend significant time and effort reading and understanding code written by their peers or external contributors. To help assist in this process, Duet AI for code assistance provides an “Explain this code” option available whenever a developer selects their code, allowing them to more quickly understand, map, and navigate unfamiliar code bases.

Code security guardrails — Code generated by Duet AI can also be scanned for vulnerable dependencies via Source Protect, helping surface known public vulnerabilities impacting code, along with suggested fixes when available, bringing additional security.

By harnessing the power of AI-driven developer assistance such as the one provided by Duet AI for developers, businesses can unlock unprecedented levels of productivity and efficiency in software development, paving the way for a new era of innovation and growth.

These early features of Duet AI for Google Cloud will be available for limited users and we will be expanding access very soon. Sign up here to join Google Cloud’s AI Trusted Tester Program.

We’re excited to share that Gartner has recognized Google as a Leader in the 2023 Gartner® Magic Quadrant™ for Enterprise Conversational AI Platforms, authored by Bern Elliot and Gabriele Rigon.

We believe this recognition is a testament to Google Cloud’s robust investments and commitment to innovation in AI, coupled with a deep understanding of enterprise customer needs. Enterprises are increasingly investing in AI-driven solutions that balance addressing customer expectations with operational efficiency. At a time when the demand for quality, performant, and trustworthy conversational AI has never been higher, we’re thrilled to continue to deliver best-in-class technologies, purpose-built to solve our customers’ most critical use cases.  

In 2022, Google Cloud delivered cutting-edge conversational AI technologies with many launches to our Conversational AI API portfolio. Together, these enabled developers to leverage Google’s technologies to power their applications with our end-to-end Contact Center AI (CCAI) suite, designed to solve the needs of Customer Experience (CX) and contact center leaders. 

Google Cloud’s Conversational AI APIs include pre-trained models for Speech to Text, Text to Speech and Natural Language Understanding. This conversational AI core leverages Google Research’s technology for speech, understanding and interaction, enabling and orchestrating high-quality conversational experiences at scale.

With Contact Center AI, organizations see improved customer satisfaction, higher agent productivity and reduced costs through increased agent efficiency. By focusing on user needs, Google Cloud provides comprehensive and integrated solutions that are ready for the enterprise. CCAI encompasses a comprehensive set of offerings to address the needs of the contact center.

In 2022, we launched Contact Center AI Platform, our AI-first, mobile-first, user-first contact center as a service (CCaaS), providing AI-powered experiences, CRM-centered design and deployment flexibility in a single platform without the need for multiple providers. Contact Center AI Platform auto-scales on the backend, with capacity for up to 100k concurrent users on a single tenant. It also offers multi-provider voice resiliency with global low-latency routing for best possible call quality and is optimized for enhanced customer/business data security, reduced downtime, and increased agent productivity. Segra, one of the largest independent fiber infrastructure bandwidth companies in the Eastern U.S., is leveraging CCAI Platform to reimagine their customer experience through predictive flows for common experiences and greatly expanding their channels for customer interaction.

CCAI also includes Dialogflow for building virtual agents, enabling businesses to meet their customers across multiple channels. It offers robust, flexible self-service voice and chat interactions that are just as natural as a live agent. Dialogflow enables both a great customer experience and a cost-effective way to scale services. 

Our Agent Assist service gives businesses the ability to transition a call from a virtual agent to a human agent while maintaining context. It efficiently guides the agent to an accurate response, while providing real-time suggestions, more accurate responses and informed recommendations.

To improve contact center operations, CCAI Insights analyzes all customer conversations to provide leaders with real-time, actionable data points on customer queries, agent performance, and sentiment trends. Its topic modeling capabilities enable deeper understanding of key investment areas and greater classification accuracy.

To ensure our enterprise customers deploying CCAI realize value faster, Google Cloud offers CCAI through three defined transformation stages with out-of-the-box packages. The first stage starts with efficiency basics in the first week that include transcription and summarization. The second stage covers automation basics within six months using Agent Assist and Insights. The final stage is full automation within a year with industry use cases and pre-built components. All of this leads to higher agent efficiency, improved customer satisfaction and increased containment.

As we look forward to the rest of 2023 and beyond, elevating the customer experience through user-first design, AI-first capabilities and accelerating time-to-value will be our north star. We plan to announce exciting new capabilities over the next few months to enable that vision to become a reality for many more organizations. 

We are honored to be a Leader in the 2023 Gartner® Magic Quadrant™ for Enterprise Conversational AI Platforms, and look forward to continuing to innovate and partner with customers on their digital transformation journeys. 

Download the complimentary copy of the report: 2023 Gartner® Magic Quadrant™ for Enterprise Conversational AI Platforms.

Learn more about how organizations are transforming their business with Google Cloud solutions with Contact Center AI.

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