Project
Pombeau Cosmetics
Premise is a data and analytics platform that empowers decision-makers with real-time, actionable intelligence. By combining the power of a global network of on-the-ground contributors with industry-leading data science and machine learning Premise is ‘The Source of Ground Truth.’ A $66M Series C venture capital organization, backed by Valor Equity Partners, Social Capital, Google Ventures, and Andreessen Horowitz, among others.
Premise, as a data and analytics platform, relies on a global network of contributors to provide real-time, actionable intelligence. The platform faces challenges in maintaining high data quality and ensuring accurate information from its contributors. Inconsistent data, potential inaccuracies, and delays in task completion are hindering the platform’s ability to deliver reliable insights to decision-makers. To maintain its reputation as ‘The Source of Ground Truth,’ Premise needs to address these data quality issues.
To tackle the data quality problem, Premise needs to adopt a multi-faceted approach that focuses on Social Media Management, Customer Support, and Project Management. The aim is to optimize each service to ensure high-quality data collection, efficient support, and effective project execution.
- Social Media Management:
- Enhance Engagement Strategies: The Social Media Management team will conduct an in-depth analysis of user preferences, content performance, and trending topics. Based on the findings, they will implement tailored engagement strategies to increase likes, comments, shares, and saves. This will not only improve data collection but also increase the platform’s visibility among potential contributors and users.
- Expand the Contributor Community: Building on the success of the existing Premise Contributor Community on Facebook, the team will establish and grow communities on other relevant social media platforms. This expansion will enable greater outreach and recruitment of contributors, diversifying the data collection network and improving data coverage.
- Customer Support:
- Advanced Support Tools: Implement a comprehensive customer support platform that includes AI-driven chatbots capable of resolving common inquiries and issues quickly. This will free up human support agents to focus on more complex user queries, ensuring a faster and more efficient support process.
- Continuous Training for Support Agents: Invest in ongoing training for the support team to stay up-to-date with platform updates, data collection methodologies, and emerging challenges. This will equip them to provide better guidance, troubleshooting, and instruction to Premise Contributors, leading to improved data quality.
- Project Management:
- Streamlined Project Onboarding: Enhance the process of recruiting contributors for specific projects by creating a standardized onboarding procedure. This will ensure that contributors are well-versed in the project’s objectives and data collection protocols, reducing errors and inconsistencies in data submissions.
- Quality Assurance and Validation: Implement a robust quality assurance system that validates the accuracy and reliability of the data collected. This can include random spot-checks, cross-referencing with other sources, and statistical analysis to identify and address potential discrepancies.
