Portfolio

ONE IMPRESSION

Client Overview

One Impression is one of India’s fastest-growing influencer marketing ecosystems — connecting brands with 7M+ creators across niches, regions, and formats. With hundreds of campaigns running simultaneously, the platform needed a way to match the right creators with the right brands at scale.

What We Were Solving?

For One Impression, Infutrix built a predictive matching layer that operationalises creator data, applies dynamic scoring logic, and streamlines campaign execution with consistent, repeatable accuracy.

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The Challenges

The core challenges came from these failures:

Irrelevant Recommendations: Static data analysis failed to accurately predict creator performance and audience quality, leading to a campaign mismatch.
Low Performance: The resulting poor creator selection drove low campaign ROI and conversion rates.
Manual Verification Gridlock: Campaign setup required hours of manual research to analyze engagement, audience quality, and niche alignment.

Our Strategic Approach

Our strategy was to build a data-driven matching engine that operationalized creator data and applied dynamic scoring logic to deliver consistent, repeatable accuracy.

Solution Pillar 1: The Creator–Brand Matching Architecture

We developed a multi-layered system to eliminate human bias, reduce campaign setup time dramatically, and guarantee a high rate of predicted creators. We engineered the data pipeline for near real-time decision-making:

Real-Time Data Processing:The architecture processes and scores creator signals in milliseconds, ensuring that the shortlists generated are based on the absolute freshest performance data, not static, outdated metrics.

Decoupled Architecture:By building the matching layer separate from the core platform (using Microservices/MCP principles), the system can scale its processing power dynamically without slowing down the user experience.

Solution Pillar 2: The Data Flow and Decision Engine

The solution works by processing high-volume, dynamic data through three core intelligent layers:

Brand Input Layer:The system ingests and processes granular inputs like campaign goals, budget, niche, and desired geography.

Creator Data Engine:This layer analyzes creator signals such as audience demographics, engagement authenticity, niche alignment, content style, pricing suitability, and past campaign outcomes.

Fit Score Calculation:The final calculation generates a precise fit score and produces smart shortlists of creators, ready for immediate activation.

Result

The new matching engine transformed operational efficiency and campaign outcomes:

60% faster campaign setup

3.2× increase in match relevance

47% reduction in fake/low-quality creators entering shortlists

Higher campaign ROI due to better creator–brand alignment