Vendor Demo Checklist: 15 Questions That Count

When evaluating a sales AI tool, a demo is your primary opportunity to move beyond marketing claims and see the product in action. Without a structured approach, these demos can become generic presentations that don’t address your specific needs. The key is to ask targeted questions that uncover the tool’s true capabilities, limitations, and fit for your organization.

This checklist provides 15 essential questions to ask during a sales AI tool demo. These questions are designed to help you assess technical feasibility, data handling, integration, user experience, and long-term viability.

Before the Demo: Your Preparation Checklist

Before any vendor demo, do your homework. This ensures you maximize the time and get answers relevant to your team.

• Define your problem: What specific pain points is your team experiencing that AI could solve? Be precise.
• Outline desired outcomes: What does success look like? Is it increased pipeline, faster response times, or better data hygiene?
• Identify key stakeholders: Who needs to be in the demo? Sales leaders, RevOps, IT, legal?
• Prepare your data context: Be ready to discuss your current CRM setup, data quality, and any specific data privacy concerns.
• Review the vendor’s website: Understand their core offering before the demo starts. This helps you ask more advanced questions.

Sharing your specific use cases and desired outcomes with the vendor before the demo allows them to tailor the presentation. A generic demo is rarely useful.

A generic demo is rarely useful.

1. Core Functionality & Use Cases

This section focuses on what the tool actually does and how it aligns with your team’s daily operations.

How does this tool directly solve [Specific Problem X] for our sales team?

Don’t let the vendor give a generic overview. Insist they show how the product addresses your identified pain points. For example, if your problem is “SDRs spend too much time researching prospects,” ask them to demonstrate how their AI tool automates or streamlines that specific research process.

Can you show us a real-world example of [Specific Use Case Y] within the product?

Marketing materials often highlight ideal scenarios. Ask to see the feature in action, ideally with data that resembles your own. If they claim to summarize calls, ask to see a summary generated from a call transcript similar to what your team records. This reveals practical usability.

What are the primary inputs and outputs of the AI?

Understand what data the AI consumes (e.g., CRM notes, call recordings, emails) and what it produces (e.g., email drafts, call summaries, lead scores). This clarifies the data flow and potential impact on your existing workflows.

2. Data & Security

Data is the fuel for AI. How a vendor handles your data is critical for compliance and trust. This is often where vendors are weakest.

How is our data secured, both in transit and at rest?

Ask about encryption standards (e.g., AES-256), data residency (where is the data physically stored?), and access controls. Understand who at the vendor has access to your data and under what circumstances.

What are your data retention and deletion policies?

Clarify how long your data is stored on their systems and the process for requesting data deletion if you terminate the contract. Ensure their policies align with your internal compliance requirements.

Do you use our data for model training or to improve your product for other customers?

This is a critical question. Many vendors use customer data to enhance their AI models. Understand if this is optional, anonymized, or if you retain full control. If they do use your data, ask about the opt-out process.

What compliance certifications do you hold (e.g., SOC 2 Type II, GDPR, CCPA)?

These certifications indicate a commitment to information security and privacy. Request copies of audit reports if available. This is non-negotiable for most enterprise deployments.

3. Integration & Implementation

A powerful AI tool is useless if it doesn’t integrate with your existing tech stack or is too complex to implement.

How does your solution integrate with our existing CRM and other sales tools?

Ask for specifics. Is it a native integration, API-based, or does it require custom development? What data flows in and out, and how frequently? Understand the level of effort required from your IT or RevOps team.

What is the typical implementation timeline and what resources do we need to allocate?

Get a realistic timeline for initial setup, data migration, and user onboarding. Ask about the internal resources (people, time) you’ll need to dedicate to the project. This helps you budget for more than just the software cost.

What happens if our CRM or other integrated systems change or update?

Understand the vendor’s process for maintaining integrations. Will their tool automatically adapt, or will it require manual updates or new development from your side? This impacts long-term maintenance.

4. Customization & Flexibility

Sales teams have unique processes. An AI tool should adapt, not force you to change your entire workflow.

To what extent can we customize the AI’s outputs or behavior?

Can you fine-tune the AI’s tone, messaging, or specific recommendations to match your brand voice or sales playbooks? For example, if it drafts emails, can you provide templates or rules it should follow?

How does the AI handle edge cases or scenarios outside its typical training data?

No AI is perfect. Ask how the system behaves when it encounters unusual data or situations. Does it flag it for human review, make a best guess, or simply fail? This reveals its robustness.

5. Support & Roadmap

Beyond the initial sale, you need to know the vendor will support you and continue to innovate.

What kind of ongoing support and training do you provide?

Inquire about support channels (email, chat, phone), response times, and available training resources (documentation, webinars, dedicated account manager).

What is your product roadmap for the next 12-18 months?

Understand the vendor’s vision for the product. Are they actively developing new features? Do they align with your long-term strategic goals? This helps assess the tool’s future viability and potential for growth.

How do you handle feedback and feature requests from customers?

A vendor that listens to its customers is more likely to evolve in a direction that benefits you. Ask about their process for collecting and prioritizing customer input.

6. Pricing & ROI

While not always covered in detail during a first demo, it’s important to understand the pricing model and how to approach ROI. For a deeper dive into calculating ROI, refer to our guide on how to calculate the real ROI of a sales AI tool.

What is your pricing model, and what factors influence the cost?

Understand if pricing is per user, per usage, per feature, or a tiered model. Ask about any hidden costs, setup fees, or additional charges for premium features or support.

How do you measure the success of your customers using this tool?

While vendors will present their own metrics, ask them to explain how they track success. This helps you understand what metrics you should focus on internally to validate the tool’s impact.

After the Demo: Your Follow-Up

The demo is just one step in the AI vendor evaluation process. After the demo, consolidate your notes and discuss with your team.

For complex tools, a trial period or proof of concept is essential to validate claims with your own data and team.

Our guide on AI vendor contract exit clauses can help with contract review. By using this structured checklist, you can move beyond superficial presentations and make an informed decision about which sales AI tool is the right fit for your organization.