Clear definitions for the terms that come up most in modern B2B sales - intent data, conversation intelligence, MEDDIC, revenue intelligence, and the signals buyers leave behind.
Behavioural and conversational data a prospect produces on surfaces you own - your chatbot, pricing page, docs, product.
First-party intent data is the highest-fidelity intent signal available because it comes directly from the buyer on a surface you control. Examples include AI chatbot conversations, pricing page visits, demo bookings, and product usage events. Unlike third-party intent data, it is explicit, attributable to a known session, and collected under your own privacy policy.
Software that analyses sales conversations - calls, meetings, chatbot sessions - to surface coaching moments, risks, and deal signals.
Conversation intelligence platforms transcribe and classify sales interactions so reps and managers can coach on what was said, spot objections, and track commitments. Traditional tools (Gong, Chorus, Avoma) focus on recorded calls. Newer tools extend the same analysis to AI chatbot conversations on the website, turning pre-call visitor intent into structured signals.
A category of software that consolidates signals from sales activities, CRM data, and buyer interactions to forecast and influence revenue outcomes.
Revenue intelligence platforms (Clari, Aviso, Gong Revenue Intelligence) aggregate pipeline activity, engagement data, and deal health to improve forecasting accuracy and surface at-risk deals. The category is dominated by enterprise RevOps tools; SMB teams typically need lighter, rep-facing alternatives that surface buyer intent signals from inbound conversations rather than overlaying an entire CRM.
Buyer Intent Signals
Observable behaviours or statements that indicate a prospect is researching, evaluating, or ready to purchase a solution.
Buyer intent signals come in three forms: first-party (actions on your own surfaces), second-party (signals from review sites like G2 and Capterra), and third-party (aggregated web activity from cookie panels). The strongest signals tie back to MEDDIC categories - budget, decision criteria, pain points, and champion behaviour - so reps can act on them without interpretation.
A B2B sales qualification framework covering Metrics, Economic Buyer, Decision Criteria, Decision Process, Identify Pain, and Champion.
MEDDIC is the qualification framework most enterprise sales teams use to evaluate pipeline health. Each letter is a deal-critical question: Do we know the economic buyer? Do we understand the decision criteria? Have we identified pain? Who is our champion? Modern tools can detect MEDDIC signals passively from buyer conversations rather than relying on reps to fill in a checklist after the call.
Passive Detection
Inferring sales-qualification signals from natural conversation rather than asking the prospect a checklist of questions.
Passive detection is how Parsley's AI chatbot extracts MEDDIC signals without interrogating the visitor. A prospect who asks "does this integrate with HubSpot?" is signalling Decision Criteria; one who mentions "our VP wants this by Q2" is signalling Economic Buyer and Decision Process. The chatbot answers the visitor's question helpfully, and the signals feed lead scoring in the background. No forms, no qualification survey, no friction.
Lead Quality Score
A single value (Hot / Warm / Cold) that summarises how qualified a lead is based on passively detected MEDDIC signals.
Parsley rolls up detected MEDDIC signals into a Hot, Warm, or Cold score so reps can triage inbound leads at a glance. Hot leads typically show evidence across four or more MEDDIC categories (pain, metrics, champion, decision criteria). Warm leads show partial signal coverage. Cold leads have engaged but haven't revealed qualification depth yet. The score updates in real time as conversations progress and syncs to your CRM.
Hot / Warm / Cold Lead
The three lead temperature bands Parsley assigns based on MEDDIC signal coverage detected from chatbot conversations.
Hot leads have broad MEDDIC coverage — multiple signals across pain, champion, decision process, and economic buyer — and are usually worth a same-day outreach. Warm leads have surfaced some qualification but have gaps; they benefit from a targeted follow-up that fills the missing categories. Cold leads have engaged with the chatbot but haven't shown qualification depth yet; they go to nurture. The bands are thresholds, not absolutes, so always read the underlying signal tags before acting.
Chatbot Knowledge
The documents, FAQs, and content you upload to train Parsley's AI chatbot to answer visitor questions accurately.
The chatbot is only as good as the knowledge you give it. Upload product docs, pricing pages, case studies, objection-handling notes, and FAQs. The richer the knowledge base, the more naturally the chatbot can answer — and the more MEDDIC signal it can capture, because longer, deeper conversations surface more qualification. Knowledge is scoped per user; what you upload trains your chatbot, not the organisation's.
Profile Section
A reorderable block on your Parsley profile — About, Services, Links, Chatbot, and so on.
Profile sections are the building blocks of your public Parsley page. Each section has a type (About, Services, Testimonials, Gallery, Links, Chatbot, etc.) and you can reorder them via drag-and-drop. One section per type is the convention. The chatbot is a separate embedded feature, not a section. Changes save automatically — there's no publish button.
Sensor and Intelligence
Parsley's product frame: the profile and chatbot are the sensor; the MEDDIC signals and lead scoring are the intelligence.
Most tools on the market treat the digital card or the chatbot as the product. Parsley treats them as the sensor — a lightweight surface that captures first-party conversational data — and treats the intelligence layer (signal extraction, MEDDIC mapping, lead scoring, CRM sync) as the actual product. The framing matters because it explains why you should share your profile aggressively: the more visitors, the more intent you capture. The card is not the point; the signal is.
Signal Tag
A tag applied to a lead indicating which MEDDIC category a detected signal falls under.
When the chatbot detects a qualification signal, Parsley tags the lead with the relevant MEDDIC category (Identify Pain, Economic Buyer, Champion, Metrics, Decision Criteria, Decision Process). Tags sync to your CRM so reps can filter pipeline by signal coverage — for example, "show me Hot leads with Economic Buyer detected." Tags are additive: one lead can accumulate multiple signals across multiple sessions.
Metrics (MEDDIC)
Measurable business outcomes the prospect cares about — cost savings, revenue growth, time saved.
The Metrics signal fires when a prospect quantifies the problem they're trying to solve or the outcome they need. Examples: "we need to cut onboarding time by 30%," "our CAC is $800 and we need it under $500." Strong Metrics signal means the deal has a measurable business case, which typically shortens the sales cycle.
Economic Buyer (MEDDIC)
The person with budget authority who can say yes to the purchase.
Economic Buyer signal fires when a prospect references who controls budget — "my CFO will need to approve," "the VP of Sales owns this tool budget," or when the visitor themselves is clearly the buyer. Knowing the Economic Buyer early prevents late-stage surprises where a sponsor loses a deal to someone they hadn't involved.
Decision Criteria (MEDDIC)
The formal or informal requirements the prospect will use to evaluate solutions.
Decision Criteria signal fires when a prospect reveals what they're comparing on — "does it integrate with HubSpot," "we need SOC 2," "must support SSO." These are the bars you have to clear. Catch the criteria early and you can tailor the rest of the sale to each one; miss them and you end up reacting to a procurement checklist you've never seen.
Decision Process (MEDDIC)
The sequence of steps, stakeholders, and timelines the prospect will follow to reach a purchase decision.
Decision Process signal fires when a prospect describes how they buy — "we'll pilot for 30 days then present to the exec team," "legal reviews all contracts over $25k." Understanding the process tells you what happens between "interested" and "signed" so you can plan the path, not stumble through it.
Identify Pain (MEDDIC)
The specific problem or cost of inaction the prospect is trying to solve.
Identify Pain signal fires when a prospect articulates what hurts — "our SDRs spend half their day on manual research," "we lost two deals last quarter because intent data was stale." Pain is the fuel of the deal; without it, even a qualified prospect has no urgency. Parsley surfaces pain mentions prominently so reps can quote them back in follow-up.
Champion (MEDDIC)
An internal advocate at the prospect company who wants your solution to win.
Champion signal fires when the prospect shows they're personally invested in getting the deal done — volunteering to pitch internally, asking what they need to build a business case, requesting collateral to share with their team. A real Champion will sell for you inside their org; the absence of one is a silent deal-killer. Catching Champion early tells you who to equip and when to hand them ammunition.
See Intent Data in Practice
Parsley turns every AI chatbot conversation into first-party intent data mapped to MEDDIC signals and synced to your CRM.
