AI-Assisted Lead Qualification

We start by defining what a good lead means for you. We interview your sales team and review closed-won and closed-lost enquiries. Which service lines are profitable, which cities do you serve, what minimum order size makes sense, and what signs predict a serious buyer? We write these as clear criteria, such as must-have, nice-to-have and disqualifying factors. This is the most important step, because AI is only as good as the rules it is given. Next we map the intake: where enquiries arrive, in what format, and what data you already capture. We improve the forms to collect a few structured fields next to the free-text message, since structured answers are more reliable. We then design the AI step. Using a language model through a secure provider, we create a prompt that gives the model your criteria and asks it to return a structured result: a short summary of the request, extracted fields, which criteria are met, a priority level, a confidence note and a suggested next action. We instruct it to say when information is missing and not to guess. We test it on a few hundred past enquiries and compare its priority with what your team knows actually happened, and we refine the criteria and prompt until results are useful. Where volume allows, we measure agreement between the AI and your sales team and report the mismatches honestly. We then connect the workflow to your tools: new enquiry arrives, the AI analyses it, the result is written to your CRM fields, the lead is assigned based on priority and category, and the salesperson is notified with the summary. Low-priority and unclear leads enter a lighter-touch sequence rather than being dropped; see automated lead follow-up. We set safeguards: the AI never sends messages to the customer on its own in this workflow, it does not make price promises, and a human reviews anything flagged as unusual. We log inputs and outputs so you can audit decisions, and we add a feedback button for the team to mark a suggestion right or wrong, which helps us improve the rules. After launch, we review performance monthly, checking time to first contact for high-priority leads, conversion by priority and any bias or drift. We cannot guarantee higher closing rates, because many factors affect sales, and AI output will sometimes be wrong, but a disciplined setup can save reading time and help your best leads get faster attention. For the underlying CRM, see sales pipeline setup.