Built Data Aggregation Pipeline for Social Media Influencers

Process Flow: The Visual Story

Technology Stack

Problem Statement

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Identification: With the increasing number of social media influencers, it can be challenging to identify the right influencers who align with the business's brand image and target audience.

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Authenticity: Businesses may struggle to determine the authenticity and credibility of an influencer, and whether they will be a suitable brand representative.

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Relevance: It can be challenging to assess whether an influencer's followers and content are relevant to the business's target audience.

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Measuring Impact: Businesses may find it difficult to measure the impact of an influencer marketing campaign, and whether it is effectively reaching and engaging their target audience.

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Cost: Hiring an influencer can be costly, and businesses may need to allocate significant resources to evaluate multiple influencers and run a successful marketing campaign.

Solution Overview

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OptiSol created an automated pipeline that continuously aggregates, scores, and ranks the tweets of social media influencers, aimed at helping businesses discover outstanding brand ambassadors for their products.

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As initial step, the tweets are pre-processed, re-tweets are contextualized ready to be ranked.

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A data aggregation pipeline is then built to extract the tweets from social media influencers who have agreed to be scored by the Social IQ platform.

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Using Universal Sentence Encoder (USE), a semantic indexing model is developed to categorize the tweets into 13 dimensions of social intelligence.

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The pre-processed tweets are then ranked based on their scores and displayed on a robust dashboard.

Business Impact

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Efficient and Scalable: Can process and rank large volumes of data in real-time, reducing the time and effort required to manually evaluate and rank influencers.

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Objective Evaluation: Removes subjective biases and human error, providing a more objective and accurate evaluation of an influencer's social intelligence.

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Increased Relevance: Can assess an influencer's relevance to a business's target audience and brand image, increasing the chances of a successful influencer marketing campaign.

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Better Performance Metrics: Can provide detailed and reliable performance metrics, allowing businesses to evaluate the impact and effectiveness of their influencer marketing campaigns.

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Increased Cost-Effectiveness: Can reduce the cost of evaluating and selecting influencers, allowing businesses to allocate more resources towards other aspects of their marketing strategy.

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