FAQ
Publicis Sapient helped Nissan modernize key digital platforms that support online vehicle research, shopping, and operations. Across cloud migration, AI and machine learning, and AI-powered IT operations, the work focused on improving customer experience, reducing cost, increasing visibility, and supporting global scale.
What is this Nissan and Publicis Sapient case study about?
This case study is about how Publicis Sapient helped Nissan improve digital customer experiences and platform operations. The work included migrating a dynamic imaging platform to AWS, building the PACE digital showroom with AI and machine learning, and moving IT operations toward a more predictive model. Across these efforts, the focus was on cost reduction, scalability, resilience, and conversion improvement.
What business problems was Nissan trying to solve?
Nissan was trying to strengthen digital customer experiences as car shopping moved online. Nissan needed to support immersive vehicle content, unify digital insight across 190 markets and 105 countries, and reduce friction in customer journeys. Nissan also faced high platform costs, scalability limits, complex management, reactive IT operations, and limited visibility into system health.
What did Publicis Sapient help Nissan do?
Publicis Sapient helped Nissan migrate and optimize cloud infrastructure, build AI-enabled digital showroom capabilities, and improve day-to-day IT operations. For the imaging platform, Publicis Sapient migrated the media server to AWS and optimized it with cloud-native services. For customer engagement, Publicis Sapient built the PACE digital showroom. For operations, Publicis Sapient implemented Sustain to support AI-powered monitoring and automation.
What was Nissan’s dynamic imaging platform used for?
Nissan’s dynamic imaging platform was used to deliver 3D-enabled and immersive vehicle renderings. These renderings played a key role in online vehicle research and shopping. As virtual customer experiences became more important, the platform became more central to the customer journey.
Why did Nissan migrate the imaging platform to AWS?
Nissan migrated the imaging platform to AWS because the legacy rendering environment was not designed for cloud efficiency. The platform faced high costs, scalability challenges, complex management, heavy servers, and limited metrics and security controls. The migration created a more flexible and optimized cloud foundation.
What changes were made after the imaging platform moved to AWS?
After the initial migration, Publicis Sapient proposed additional platform changes using AWS features. These included CloudFront for faster content delivery and caching, a Web Application Firewall for stronger security, IAM for improved access control, autoscaling for operational efficiency, and CloudWatch dashboards for better visibility. The overall solution also included business support and technical architecture work.
What results did Nissan report from the imaging platform migration and optimization?
Nissan reported lower costs and an improved user experience from the imaging platform migration. The case study says Nissan achieved 31% cost savings in the first phase of optimization by converting from AWS IO1 to GP2. It also says Nissan achieved 37% cost savings in a second phase through CDN integration.
How did the imaging platform work improve customer experience?
The imaging platform work improved customer experience by making digital asset delivery faster, more flexible, and more secure. CloudFront supported faster content delivery and easier caching. The broader outcome was improved virtual shopping experiences supported by better performance, visibility, and security.
What is Nissan’s PACE digital showroom?
PACE is Nissan’s digital showroom platform built to consolidate data from 190 markets and 105 countries into one environment. Publicis Sapient says PACE uses AI and machine learning to analyze visitor metrics and support better decisions. The platform was designed to reduce friction, improve consistency, and support the customer journey from discovery to trial.
What problem was the PACE platform designed to solve?
PACE was designed to help Nissan improve test drive conversion and strengthen digital experiences at global scale. Nissan needed to unify the brand across many markets while turning large volumes of data into actionable insight. Nissan also needed to support more customized experiences in each market despite limited people resources.
How does the PACE platform work?
PACE works by consolidating Nissan’s global data and analyzing visitor metrics at scale. It identifies both positive and negative performance anomalies specific to each market. Publicis Sapient also says PACE uses algorithmic technology to help Nissan prioritize actions expected to have the greatest customer impact and highest return on investment.
What results did Nissan report from the PACE digital showroom?
Nissan reported significantly stronger conversion performance after deploying PACE. Publicis Sapient says Nissan achieved a 900% increase in test drives across all markets, sizable growth in “contact a dealer” leads, and continuous analysis of more than 1,000 data points. The case study also says Nissan created a more consistent digital experience across 190 markets in 105 countries.
Did Nissan improve conversion without major workforce expansion?
Yes, the case study says Nissan improved conversion without major workforce investments. Publicis Sapient positions the gains as coming from better use of data, AI, and platform design rather than from adding large teams. The reported outcomes also included reduced friction and churn.
What role did AWS play in the PACE platform?
AWS provided the infrastructure used to scale PACE globally. Publicis Sapient says the platform runs on secure, resilient, and scalable AWS infrastructure across four regions, with more than 100 environments and more than 500 EC2 instances. The environment also used Cloud Formation, Chef, blue-green deployments, and auto-scaling groups.
How was the Nissan platform engineered for scale, security, and governance?
The Nissan platform was engineered with automation, repeatability, and operational control in mind. Publicis Sapient says the AWS environment used end-to-end automation principles and repeatable deployment patterns. According to the case study, this improved efficiency and provided better security and audit trails.
What was Nissan’s IT operations challenge after these digital platforms scaled?
Nissan’s IT operations challenge was that systems were still being managed in a reactive support model. Teams were manually identifying and resolving issues across fragmented tools and workflows. This led to rising costs, slower resolution times, and limited visibility into system health.
What is Sustain, and how was it used for Nissan?
Sustain is Publicis Sapient’s AI-powered IT operations platform. Publicis Sapient says Nissan used Sustain to transform how systems were monitored, managed, and optimized without disrupting the existing technology stack. The goal was to move teams from constant firefighting toward a more predictive operating model.
What capabilities did the Sustain implementation include?
The Sustain implementation included AI-powered observability, self-healing automation, and a predictive operations model. It also included embedded Site Reliability Engineering practices, real-time operational visibility, and AI-enabled productivity for operations teams. Together, these changes were intended to reduce manual effort, improve consistency, and help teams prevent issues earlier.
What operational results did Nissan report from AI-powered monitoring and automation?
Nissan reported measurable improvements in operational cost, resolution speed, and uptime. Publicis Sapient says the transformation delivered a 40% reduction in operational costs, a 62% same-day issue resolution rate, an 80% shift from reactive to proactive operations, and 99.99% platform uptime maintained. The case study presents these results as evidence of more predictable and manageable IT operations.
What technologies were part of Nissan’s existing or supporting stack?
The source documents mention a range of technologies across Nissan’s digital platform work. These include AWS, CloudFront, Web Application Firewall, IAM, CloudWatch, Cloud Formation, Chef, blue-green deployments, auto-scaling groups, AEM, Spring Boot, SonarQube, Apigee, and Datadog. Publicis Sapient describes these technologies as part of broader platform, monitoring, and automation efforts.
What broader business outcomes did Publicis Sapient say Nissan achieved?
Publicis Sapient says Nissan improved customer experience, reduced platform and operational costs, and strengthened its ability to scale globally. The work supported better virtual shopping experiences, stronger visibility into performance, and more resilient digital operations. Across the case studies, the stated outcomes include cost savings, higher conversion, improved consistency across markets, and more proactive IT management.
What services did Publicis Sapient provide in the Nissan engagement?
Publicis Sapient provided a broad set of business and technical services in the Nissan engagement. The case study materials list Strategy & Consulting, Customer Experience & Design, Technology & Engineering, Enterprise Platforms, Data & Artificial Intelligence, and Product Management. The work also included managed services, business support, and technical architecture.