THE CHALLENGE

A holding company managing 70+ diverse brands faced an impossible scaling problem: how to produce authentic, brand-specific social content for each subsidiary without a massive team.

Marketing teams were stuck on a content bottleneck, diluting brand individuality and leaving smaller companies with stale, irrelevant feeds.

Marketing teams spent hours collecting brand assets, reviewing old posts, and researching industry trends just to produce a handful of captions. Output lagged, quality varied, and the central team couldn’t keep up.

WHAT WE BUILT

We developed a custom AI content generation agent that automated research, tone modeling, and first-draft creation for each subsidiary.

• Data Ingestion: The agent absorbed each brand’s blog assets, first-draft voice notes, and top-performing social posts.
• Performance Analysis: It identified high-impact themes, formats, and visual trends from historical data.
• Real-Time Awareness: It scanned relevant industry news to surface timely post styles.
• Automated Generation: Using learned KPIs and distinct tone models, the system generated a week’s worth of platform-specific drafts — copy, visuals, and image concepts — in hours instead of days.

The system then mapped generated posts — from scheduling tasks inside Hootsuite and Sprout Social to a copy tools like Jasper — covering most of the process, so that many simpler captions required no human touch. A single marketer could now manage 10+ brands, from ongoing performance analysis through post scheduling and review.

Instead of forcing multiple systems to cooperate, we built a unified agent that understood each brand’s identity end-to-end.

THE CHALLENGES WE FACED

The primary hurdle was inconsistent brand data. Some subsidiaries had full brand kits and years of analytics; others offered little more than a logo.

We built adaptive ingestion logic that weighted available data and used probabilistic inference when information was sparse, ensuring consistent quality across the board.

Another challenge was tone precision. Early drafts blurred voices between brands.

We refined linguistic embeddings and used recursive feedback loops to isolate each company’s unique phrasing and vocabulary, achieving brand-accurate results at scale.

THE OUTCOME

• Faster Production: Weekly posts for 70+ brands generated in under 24 hours.
• Improved Efficiency: One marketer could now review all subsidiaries in the time it previously took to manage five.
• Higher Engagement: Drafts delivered 25–40% more engagement than legacy posts.
• Strategic Bandwidth: Teams shifted focus from production to campaign planning and analytics.

Before: 1 full-time employee spent ~20 hours/week managing content for 5 brands.
After: 1 employee spent ~10 hours/week reviewing and approving content for 20+ brands.

The company now has a sustainable framework that delivers portfolio-wide social storytelling — preserving each brand’s voice while achieving the speed and scale of a unified operation.

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