Automotive Brand Content Marketing

Project Background

The client is a leading domestic joint-venture automotive brand with a portfolio of 6 models on sale, spanning both ICE and new energy vehicles. In Q3 2024, the brand entered a period of intensive product refreshes, with new launches or mid-cycle updates for 3 consecutive months. However, due to long content production cycles and fragmented platform operations, the brand's voice growth across four major content platforms—Douyin, Bilibili, Xiaohongshu, and WeChat Channels—lagged noticeably behind competitors. Particularly among younger audiences for new energy models, brand awareness ranking fell out of the top five, creating an urgent need for a solution that could rapidly scale content output and unify cross-platform distribution cadence.

Core Challenges

Severe mismatch between content capacity and launch cadence. The traditional video production process—from scriptwriting and shooting to post-production editing—averaged 12 working days per product video. Yet in the Q4 2024 plan, the brand needed to complete content reserves within 90 days: 24 model explainer videos, 18 short videos on technical highlights, and 12 user testimonial stories.

Difficulty unifying content tone across platforms. Douyin favors 15-30 second high-impact clips, Bilibili users prefer 3-5 minute deep-dive analyses, Xiaohongshu requires scenario-based recommendation copy, and WeChat Channels emphasizes brand tone. Previously, the four platforms were operated by different agencies, resulting in inconsistent core selling points for the same model across platforms—even conflicting specifications.

Broken data feedback loop. Each platform's backend data was tracked independently, making it impossible to aggregate and analyze which content formats actually drove lead conversion. The marketing team had to manually export 4 reports weekly and merge them by hand, causing decision-making delays of at least one week.

Solution

SUPER TRANGO deployed an "AI Video Script Engine + Omnichannel Distribution Hub" combined solution for the brand:

• AI Script Generation: Input model specifications, target audience profiles, and platform content guidelines; the system automatically generates video script frameworks tailored to each platform's context, which then enter the shooting phase after human review. Script production time per video was compressed from 2 days to 3 hours.
• Unified Asset Library: All shot footage is uploaded to a cloud asset library, where AI automatically tags content (e.g., "chassis structure," "smart cockpit," "range testing"), allowing platform operators to retrieve assets on demand and ensuring consistent messaging of core selling points.
• Cross-Platform Scheduling Dashboard: Integrates publishing calendars across all four platforms, supports one-click schedule synchronization, and automatically detects excessive content overlap across platforms on the same day.
• Voice Attribution Model: Connects to public APIs and search indices across platforms, converting brand mentions, engagement, and search growth into a unified "Brand Voice Index" updated daily.

Execution Highlights

New Energy Model Launch Week Campaign: During the launch week of an all-new pure electric SUV, the AI engine rapidly generated 8 short video scripts from different angles—from "three-electric system teardown" to "female owner commuting scenarios"—adapted for Bilibili, Douyin, and Xiaohongshu respectively. One Xiaohongshu video on "car interior space makeover" received 23,000 saves, driving a 210% week-over-week increase in search index for that model.

Tech Brand Day Livestream Integration: For the launch of the brand's self-developed intelligent driving system, the AI script engine pre-generated 12 teaser short video scripts and distributed them simultaneously across all four platforms on livestream day. Within 48 hours after the livestream, 6 additional secondary distribution videos were automatically generated from highlight clips, extending the content lifecycle of a single event from 3 days to 2 weeks.

Dealer Content Collaboration: AI script templates were made available to 200 core dealers nationwide. Dealers only needed to replace local test-drive footage and promotional offers to produce regional content aligned with brand tone. This initiative raised brand consistency of dealer-generated content from 62% to 91%.

Results

Beyond the core voice metric, the project delivered two other notable changes: the brand's awareness ranking among target audiences for new energy models rose from 9th to 4th; and after unifying content tone across all four platforms, negative feedback in user comments regarding "inconsistent specifications" dropped 78% quarter-over-quarter.

Key Takeaways

The value ceiling of AI scripts depends on input quality. In the early stages, scripts generated directly from product manuals were highly homogenized. It was only after incorporating script structures, hook patterns, and pacing models from the past 3 years of top-performing videos across platforms into the training asset library that output quality achieved a qualitative leap. Brands need to budget at least 2 weeks for content asset organization.

Cross-platform unification is not one-size-fits-all. What gets unified is core selling points and data specifications—not the mode of expression. For the same model's battery safety technology, Douyin emphasizes the visual impact of crash test footage, while Bilibili breaks down the cell structure principles. Both scripts are generated separately by AI, but key specifications reference the same data source.

Voice growth must be tied to the business funnel. A 450% voice increase that cannot convert into test-drive bookings or showroom visits is merely a vanity metric for the brand. We recommend planning lead capture pathways at project kickoff and integrating voice data with the CRM system to validate the true ROI of content marketing.