PUBLISHED DATE: 2026-09-21 22:28:13

Automotive Case Study – Fueling Customer Centricity with One Platform | Publicis Sapient

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Global Automaker Increases Conversion by 25%

How one platform connected all touchpoints across the customer journey for improved experience and sales.

Summary

Better, connected data helped the automaker spend less to turn digital interest into vehicle sales.

25 % increase the digital lead conversion
15 % decrease in cost per digital lead
15 % decrease in digital cost per sale

hero-customer-story-automotive-customer-journey-platform

Client Auto Company

Industry T&M

Topic Data

In this customer story

Intro
The Problem
The Solution
The Impact

Intro

For a global automaker, generating leads was only part of the job. The bigger challenge was knowing which marketing decisions actually led to vehicle sales, then using that insight across markets. To do this, it needed a clearer link between customer behavior, media spend and demand. Publicis Sapient built a global platform that worked backward from the sale, helping teams predict demand, make faster marketing decisions and focus spend where it had the greatest impact.

The Problem

The automotive industry is facing disruption on multiple fronts. Customer expectations of brands has changed as have their expectations for vehicle ownership. Amidst this environment, this leading global auto maker aims for one in every 12 utility vehicles sold globally to be one of their brands by 2020. To meet this goal, we designed and prototyped the blueprint for a global platform at scale to drive a data-driven customer experience across all touchpoints to generate demand and increase sales.

The Solution

The global platform facilitates the breakdown of siloes, leverages data and technology, drives accountability and enables teams along the entire sales funnel to react more quickly to buyer demands by arming them with real-time metrics and dashboards. We applied a reverse funnel approach, meaning we worked backwards, starting with the bottom of the funnel (a purchased vehicle), to predict the required media spend for an outcome-oriented model that resulted in significant efficiency gains. The platform was launched in two representative markets as a pilot, but once scaled globally, will allow global teams to roll out similar models within their local regions. More specifically, to better understand and improve how marketing and sales contributed to overall sales, the auto maker decided to take a closer look at the sales funnel and marketing campaigns.

Demand model: A predictive sales funnel

The auto maker needed to predict the effectiveness of their sales funnel at each stage of the buyer journey, the current and future state of the business and the effect of direct and indirect factors on sales. We built advanced machine learning models to:

Forecast sales funnel performance with high accuracy
Simulate various marketing plans and expected outcomes
Make informed decisions on the optional marketing mix
Implement an optimized algorithm to recommend spend for a given target or budget

Dynamic creative: Personalized marketing campaigns

The auto maker needed to get into market faster and optimize creative along the way. We streamlined processes and collaboration, resulting in a reduction of the campaign workflow from campaign brief to go-live by 50% despite the richness of campaign variants and the added complexity of personalization. In addition the insights-based campaigns and created targeted personas have driven efficiencies in:

Cost per visit
Cost per lead
Actual cars sold

The Impact

The platform is not just a technology solution -- it presents a holistic approach to marketing and sales across people, process and technology. The auto maker is now able to optimize media and incentive spend together across the entire sales funnel, beyond just lead generation, to get an accurate prediction of business outcomes and recommendations on how to improve them.

Demand forecasting model results:

Delivered usable, reliable forecasts after just three months
Advanced machine learning models are highly cost-efficient compared to traditional statistical forecasting models
Models are scalable—they are built on a modular basis so that additional inputs (like competitor incentives and sales) can be easily integrated to increase predication accuracy

Dynamic creative results:

25% increase the digital lead conversion
15% decrease in cost per digital lead
15% decrease in digital cost per sale
Workflow from campaign brief to go-live has been shortened by 50%

The changed perspective of the reverse funnel has surfaced additional opportunities to remove gaps in the customer journey and to further improve performance. Gaps in the customer journey have been identified in the process, providing opportunities to further improve performance.

" Success lies in one-to-one customer engagement at scale enabled by technology and agile teams that are connected globally, but operate locally. A global platform provides the speed to find and execute efficiencies, build new products and services and ultimately continue to rise as a market leader. "

— Arthur Sadoun

CEO, Publicis Groupe

Meet our author

Alyssa Altman

Transportation & Mobility Lead, Americas