> For the complete documentation index, see [llms.txt](https://doc.aissist.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://doc.aissist.io/use-cases/sales.md). # Sales **Last updated:** May 5, 2026 Use Aissist to automate lead qualification without losing context or conversion quality. This example shows how a property rental company used Aissist to improve sales efficiency while keeping human focus on the highest-value leads. ### The challenge The company needed to scale lead handling without scaling headcount at the same rate. They wanted to: * respond faster * qualify leads consistently * reduce operating cost * keep conversion quality high ### What they automated The team automated the qualification flow in five parts: 1. load the right knowledge 2. define clear instructions 3. tag leads by scenario and intent 4. route the right conversations to humans 5. handle corner cases safely ### 1. Assets The team added the core knowledge sources first. That included: * the public website with rental listings * business process documents * internal guidance for credit checks and application steps This gave Aissist the knowledge base it needed to answer common sales questions correctly.

Google Doc for Knowledge Base

### 2. Instructions The team defined how the sales assistant should behave. That included: * brand tone * qualification rules * escalation rules * response boundaries With clear instructions, Aissist could behave more like a trained representative and less like a generic chatbot.
### 3. Intelligent tagging Aissist used tags to organize leads by interest level, business area, and next step. This helped the team: * prioritize high-intent leads * separate workflows by scenario * find and review important conversations faster Those tags appeared directly in the agent platform, which made routing and review much easier.
### 4. Process and handoff The team deployed Aissist into the existing sales workflow instead of building a new one around it. Aissist handled the repeatable qualification steps first. When a lead needed human attention, it tagged and routed the conversation so the team could step in at the right time.
### 5. Managing corner cases The team improved performance over time by adding context and refining instructions for edge cases. For example, when users asked about scenarios that were not covered in the first version, the team updated the guidance so Aissist could respond safely and consistently. {% hint style="info" %} On one occasion, a customer inquired whether the house was haunted. In response, Aissistant made a ghost-related joke, which was deemed inappropriate. To avoid such incidents in the future, we have added a new instruction: "Do not ever tell user about or joke around ghosts or haunted homes. If user asks about ghosts or haunted homes, tell the user that you will need help and someone will reach out shortly." {% endhint %} ### Result The company automated `80%` of lead traffic. The remaining `20%` — the most valuable or complex conversations — were escalated to the human team. That led to: * higher sales efficiency * lower operating cost * better focus for human reps * more scalable lead handling ### Why this works This pattern works well for sales workflows that are: * repetitive * rules-based * high volume * easy to segment by lead intent Lead qualification is one example. The same pattern also works for inbound sales triage, rental inquiries, product fit questions, and other early-stage sales motions. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://doc.aissist.io/use-cases/sales.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.