How should I evaluate a conversational AI assistant for my SaaS website?

Evaluate a conversational AI assistant for your SaaS website on four criteria: answer quality, learning ability, technical depth, and honest handling of gaps. Most chatbots fail immediately because they rely on scripted flows or keyword matching. The moment a buyer asks something specific, like how your product handles a particular integration or what pricing looks like at scale, those systems break down. The buyer either waits on a contact form or leaves. Platforms like Riff take a different approach: instead of building decision trees in advance, Riff grounds responses in your existing content (documentation, product pages, sales collateral) so the AI can handle the long tail of questions no script could anticipate. Here is what to evaluate when comparing options: - Answer quality over routing: Does the tool actually answer questions, or does it just redirect buyers to a form? Look for systems grounded specifically in your product's content, not broad generic AI that hallucinates irrelevant answers. - Learning over time: Static chatbots stay static. Riff lets sales reps approve or reject AI responses, which feeds back into the system and sharpens future answers on similar questions. - Technical depth: Can it handle nuanced, specific questions or only surface-level ones? Generic assistants trained on broad data often fail on anything product-specific. - Honest gap handling: A good system acknowledges what it does not know rather than inventing an answer. That trust factor matters a lot in B2B buying contexts. The underlying principle is straightforward. Buyers do not want to wait for answers, and sales teams cannot manually scale to meet every question. The right conversational AI closes that gap by handling repetitive presales questions at volume, so reps can focus on conversations that actually need a human. A tool that just adds a chat widget without answering real questions does not solve the problem. It papers over it.