Neighborhood Sun Solar

Business Problem

Neighborhood Sun faced multiple challenges in effectively converting inbound sales leads, leading to revenue losses. The primary pain points included: 

  • High Drop-Off Rates: Many potential customers abandoned their queries at different stages of the buying journey due to lack of real-time support. 
  • Manual Sales Process: Inside sales representatives manually reached out to customers, limiting scalability. 
  • Missed Sales Opportunities: The absence of a structured lead nurturing process resulted in lost business potential. 
  • Inefficient Query Resolution: Customers lacked instant access to product information, leading to frustration and disengagement. 
  • Lack of Personalization: Customers expected tailored recommendations based on their location and energy requirements. 
  • LLM Used: The solution utilizes Claude Sonnet 3.5 for generating coherent and contextual chatbot responses and Titan Text Embeddings v2 for vector-based query understanding and retrieval. 

About Sun Solar

Neighborhood Sun is a leading provider of innovative solar energy solutions, dedicated to promoting sustainable energy and assisting homeowners and businesses in reducing their carbon footprint. With a strong commitment to exceptional customer service, the company focuses on making solar energy accessible and affordable for communities. As part of its ongoing initiatives, Neighborhood Sun aims to enhance its sales operations through automation to scale customer engagement and conversion. 

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Solution

Neighborhood Sun implemented a GenAI-powered chatbot to enhance inbound lead conversion by providing real-time support and personalized customer interactions. This AI-driven solution streamlines the sales process, improves engagement, and ensures a seamless customer journey. 

  • Neighborhood Sun implemented a GenAI-powered chatbot to optimize inbound lead conversion. 
  • The chatbot provides real-time support and personalized guidance throughout the customer journey.
  • It extracts the company name from the contact link to process user queries.
  • Titan Text Embeddings v2 generates vector embeddings for user queries. 
  • OpenSearch Serverless retrieves the most relevant information based on stored vector data. 
  • Claude Sonnet 3.5 generates coherent and contextual responses for accurate assistance. 
  • The chatbot leverages state-specific data segmentation for personalized interactions.
  • Data sources include FAQ documents, customer support logs, and video transcripts. 
  • Amazon S3 Buckets store data categorized by company and state. 
  • PostgreSQL on AWS RDS manages user credentials and query tracking. 
  • The AI framework operates on AWS Bedrock for seamless processing. 
  • AWS Lambda handles API requests efficiently. 
  • Elastic Container Registry (ECR) containerizes chatbot services. 
  • AWS CloudWatch provides real-time monitoring and debugging. 
  • The AI-driven automation improved lead conversion and customer engagement.
  • The solution is scalable and future-proof for long-term growth. 
Neighborhood Sun Solar
Outcomes

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Increase in Lead Conversion: Automated customer engagement led to a higher conversion rate. 

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Reduction in Drop-Off Rates: Real-time assistance ensured potential customers completed their purchase journey. 

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Increase in Sales Team Productivity: Reduced manual intervention allowed sales representatives to focus on high-value leads.