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As digital channels became the primary way customers discovered new vehicles, an automotive company struggled to produce advertising content at the scale and speed their campaigns demanded. Manual coordination between creative and marketing teams created bottlenecks, limiting their ability to keep pace with growing campaign volumes and tight timelines.
The company’s diverse vehicle portfolio required distinct visual presentation and messaging for each model. Marketing teams found themselves creating multiple ad variations for different platforms and audiences, often under tight deadlines. What worked for a family crossover wouldn’t resonate with performance vehicle buyers.
The manual process was straightforward but time-consuming: select images, draft copy, coordinate with designers for backgrounds, and assemble polished advertisements. For a handful of campaigns, this approach worked fine. But as digital advertising expanded and the company pushed to reach more customers across more channels, the workload became overwhelming. Creative teams spent their days producing assets rather than analyzing campaign performance or refining strategy. The repetitive nature of the work also made it difficult to respond quickly when market conditions shifted or new opportunities emerged.
Data Science Dojo designed an application that automated the mechanical aspects of ad creation while keeping humans in control of creative decisions. The system analyzed uploaded vehicle images using Microsoft’s Florence computer vision research to identify key visual elements and color schemes, then used these insights to generate advertisement copy that naturally aligned with what viewers would see.
Marketers could guide content through prompts, maintaining control over tone and direction while eliminating repetitive drafting work. Instead of writing every headline and description from scratch, they could set the creative direction and review multiple generated options. This preserved the judgment that makes advertising effective while removing the tedious aspects of production.
The system also generated complementary backgrounds that enhanced vehicle images without requiring design team intervention for every single ad. Rather than producing a single output, it created multiple content variations, making it easier for teams to review, refine, and select the most suitable versions. This approach maintained quality standards while significantly reducing the time investment required from creative professionals.
The results were immediate and substantial. Campaign preparation time dropped by over 85%, with tasks that previously required hours completed in minutes. Marketing teams could now keep up with campaign schedules and explore a wider range of creative options without adding headcount or extending timelines.
This efficiency translated into meaningful cost savings while improving ad consistency and visual alignment across campaigns. Teams could now test more creative approaches, iterate faster based on results, and maintain consistency across their entire portfolio. The system became an integrated part of daily workflows, supporting everything from routine campaigns to major vehicle launches without requiring constant technical intervention. What started as a solution to a production problem evolved into a strategic advantage, allowing the company to scale their advertising operations sustainably as digital demands continued to grow.
Ready to automate your organization’s processes? Let our experts at Data Science Dojo tailor an AI solution for your business. Book a call or explore more case studies.