How SupportLogic uses AI to scale account intelligence

SupportLogic operates in the competitive support technology space, serving enterprise clients like Salesforce, Snowflake, NTT, and HPE with AI agents that prevent escalations and optimize support operations. As a lean organization focused on efficient scaling, the company needed to maximize account-based marketing effectiveness while reducing operational overhead. Manual account planning consumed significant resources while delivering inconsistent results, limiting the team’s ability to personalize outreach at scale.

How AI solved this

The goal was to automate account intelligence in a way that could inform both outbound campaigns and internal strategy, while reducing manual effort. The team built a solution that transformed scattered data sources into actionable account intelligence. The approach addressed three operational needs:

1. Automated data synthesis: AI workflows aggregate information from SEC filings, earnings calls, job postings, opportunity history, and campaign engagement patterns to create comprehensive account profiles without manual research.
2. Strategic insight generation: Custom-trained GPTs analyze gathered data alongside SupportLogic's personas, positioning, and case studies to identify pain points, competitive messaging, and expansion opportunities specific to each account.
3. Scalable personalization: These structured account plans enable custom, individual-specific outreach rather than broad, persona-based campaigns, enhancing personalization while maintaining operational efficiency.

Key factors that made the implementation successful

SupportLogic leveraged readily available integrations to build a sophisticated yet accessible system:

• Workflow orchestration: Users can launch a workflow directly from Salesforce, using a Zapier integration
• Intelligence engine: GPT-4 (accessed via the OpenAI API) and Perplexity handle data analysis and insight generation
• Knowledge integration: Custom GPTs trained on company-specific personas, positioning, and case studies craft custom, detailed account plans
• Output automation: Insights and campaign suggestions populate directly in Salesforce for easy, immediate access

AI operationalization:

SupportLogic used readily available API integrations with Salesforce to create easy-to-use tools for the team. In addition to providing prompt templates and other tools to encourage SDR and rep experimentation, The team used weekly cross-functional reviews with sales to ensure buy-in and collect feedback. In general, the approach emphasized enablement over enforcement. As adoption has grown, this AI-supported motion has become a foundational component of SupportLogic’s marketing and sales process.

• Time savings: Reduced time per account plan from ~45 minutes to ~90 seconds.
• Cost efficiency: Lowered research costs from ~$12 to ~$0.83 per account.
• Scalability: Enabled research across 3,000+ accounts (versus 50 manually).
• Alignment: Improved consistency in messaging and outreach quality.
• Adoption: Sparked wider AI usage across marketing and sales, helping team members save time on repetitive tasks.
• Personalization: Shifted from persona-level to individual-level customization, enhancing ABM effectiveness.