AI Chatbot for Customer Support: Complete Buyer’s Guide for 2025
Thinking about an AI chatbot for customer support? This guide walks through the evaluation criteria, common traps, and how to pick the right platform for your team.
If you are considering an AI chatbot for customer support, the landscape can feel crowded and confusing. Intercom, Drift, Chatbase, SiteGPT, Gleap, and dozens of others all promise “AI support.” The real question is: which platform actually fits your team, your customers, and your budget?
This guide focuses on support leaders: heads of support, CX leads, and founders who want to automate the repetitive work without losing the human touch.
If you are also comparing vendors right now, start here:
1. Start with Your Support Jobs-to-be-Done
Before comparing feature checklists, clarify why you want an AI chatbot in the first place.
Common goals include:
- Deflecting repetitive FAQs so agents can focus on complex issues
- Providing 24/7 coverage without hiring a night shift
- Giving customers instant answers on key pages like pricing and docs
- Capturing qualified leads while customers ask support questions
Write down your top three jobs-to-be-done for the chatbot. You will use this list to evaluate every platform, including Guzli.
2. Decide: Support-First vs. Sales-First vs. General Chat
Not all chatbots are built for the same purpose:
- Support-first tools (like Guzli) focus on ticket deflection, handoff, and customer satisfaction.
- Sales-first tools (like Drift) prioritize pipeline, demos, and account-based marketing.
- General Q&A tools (like simple website bots) prioritize basic question answering.
You can mix and match, but trying to make a sales-first platform do support, or a basic Q&A bot do workflows, often leads to frustration.
3. Evaluate Training Sources and Control
Ask each vendor:
- Which data sources can we train on? (website, help center, files, internal docs)
- Can we exclude sensitive or outdated content easily?
- Can we override or guide the AI with specific rules and prompts?
- How do we update the knowledge base when our product or policies change?
A good support-first platform should make it easy to:
- Crawl your website and help center
- Upload key docs and FAQs
- Re-sync content in minutes, not days
Guzli, for example, is designed to treat your support content as the source of truth and gives you clear controls over what the AI can and cannot say.
4. Look at Handoff, Not Just Answers
Great support is not only about answering questions; it is about routing the conversation correctly.
Evaluate:
- When the bot is unsure, does it ask a follow-up question, search again, or just say “I don’t know”?
- How does it escalate to agents (Slack, Zendesk, email, internal queue)?
- Does it pass a clear summary or force your team to read the whole transcript?
- Can customers request a human easily, without fighting the bot?
Platforms like Guzli are built to handle uncertainty gracefully: ask clarifying questions, surface relevant content, and hand off with full context when needed.
5. Pricing: Seats, Messages, or Value?
Pricing models matter more than vendors like to admit.
Common models:
- Per seat: pay per agent using the tool (common for Intercom and Zendesk).
- Per conversation/message: pay based on usage, regardless of team size.
- Flat tiers: pay for a bundle of features and limits.
Questions to ask:
- How will this scale if our support volume doubles?
- Are AI features bundled or separate add-ons?
- Are there overage charges or hidden fees?
Guzli’s pricing is intentionally simple and transparent, with plans on the pricing page designed for teams that want to start small and grow as deflection improves.
6. Integrations: Meet Your Team Where They Work
An AI chatbot that lives in isolation will always be less effective.
Check:
- Does it integrate with your helpdesk (Zendesk, Intercom, etc.)?
- Can it update your CRM (HubSpot, Salesforce) when it captures a lead?
- Can it send alerts to Slack or Teams for important conversations?
- Is there an API or webhooks for edge cases?
Guzli integrates with popular CRMs, messaging tools, and helpdesks so the chatbot is not another silo. It becomes part of your existing workflows.
7. Analytics: Can You Prove It Works?
Before rollout, agree on your definition of “success.”
Look for analytics that show:
- Ticket deflection: how many conversations the bot resolves without escalation
- Resolution time: how much faster customers get help
- CSAT: how customers feel about bot-assisted support
- Lead capture: how many qualified conversations turn into pipeline
Tools like Guzli expose these metrics directly so you can report ROI to stakeholders. For deeper numbers, you can also reference our AI chatbot ROI analysis.
8. Implementation Timeline: Weeks vs. Hours
One of the biggest differences between platforms like Intercom or Drift and support-first tools like Guzli is time to value.
Ask every vendor:
- How long does it usually take customers like us to go live?
- Do we need professional services or consultants?
- Can we run a pilot on just one page or channel first?
Guzli was built so small teams can go live in under an hour, and larger teams can run a contained pilot before rolling out more widely.
9. Reference Checks: Who Switched From What?
Many modern AI chatbot deployments are second or third attempts: teams who tried something like Chatbase, SiteGPT, Gleap, Drift, or Intercom and now want something more focused.
Ask vendors for:
- Case studies of customers switching from your current tool
- Examples of migrations (what carried over, what changed)
- Honest tradeoffs, including what the new platform does not do
We openly publish comparison guides such as Intercom vs Guzli and other competitor pages so you can see where Guzli fits and where other tools still make sense.
10. Run a Real Pilot, Not a Demo
Finally, test with your own content and customers:
- Use real pages (pricing, docs, onboarding)
- Involve real customers, not just internal testers
- Measure deflection, CSAT, and agent workload before and after
The goal is not to prove that AI is “cool,” but to verify that it actually helps your support team and customers.
