Flag leads who meet defined engagement or fit criteria, creating a qualified handoff between marketing and sales for efficient follow-up.
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Flag leads who meet defined engagement or fit criteria, creating a qualified handoff between marketing and sales for efficient follow-up.
MQls matter because they create the crucial handoff point between marketing and sales, establishing shared definitions that eliminate the finger-pointing plaguing most revenue organisations. Without MQL criteria, sales complains that marketing sends rubbish leads whilst marketing insists sales doesn't follow up properly both often correct because there's no agreed qualification standard. MQL definitions force the question: what does a good lead actually look like? This forces both teams to examine conversion data honestly rather than operating on hunches. For marketing, MQL targets provide clear success metrics beyond vanity measures like website traffic; marketing can optimise specifically for MQL volume and cost-per-MQL rather than vague engagement. For sales, consistent MQL quality means their pipeline is full of genuinely viable prospects rather than tyre-kickers and early-stage researchers. The staging also improves customer experience: leads receive appropriate nurture based on their readiness, avoiding aggressive sales outreach when they're merely researching or gentle nurture when they're actively comparing vendors. Organisations implementing robust MQL frameworks report 25-40% increases in sales productivity because reps spend time exclusively on qualified opportunities rather than sifting through raw leads. The definition also highlights where processes break: if MQL volume is strong but conversion to opportunity is weak, you've got lead quality problems; if opportunities convert well but MQL volume is low, you need more top-of-funnel activity.
Key concepts and frameworks explained clearly. Quick reference when you need to understand a term, refresh your knowledge, or share with your team.
Start with your ICP spreadsheet: target industries, firm size, tech stack, job titles and regions. Add engagement milestones that show genuine intent pricing page view, webinar attendance, asset download, chatbot question. Publish the matrix so everyone can reference it.
Example (digital agency):
Assign numeric weights. Fit traits might contribute 60 %, engagement 40 %. A finance director from a 150-employee SaaS gets 50 fit points; attending a live demo adds 40 intent points, totalling 90 above the 75-point MQL threshold. Use HubSpot’s native scoring or a Zapier pipe feeding Pipedrive custom fields. Keep the formula public so sales trusts the math.
When a lead crosses the threshold, trigger:
A CTO who scored 60/75 may need a nudge: invite to a technical webinar, send a focused case study, or offer a no-obligation audit. Marketing automation (HubSpot workflows, ActiveCampaign, Customer.io) drips value until the lead self-qualifies.
Pull conversion data: Lead → MQL, MQL → SQL, SQL → Closed-Won. If MQL-to-SQL is under 20 %, fit criteria are too loose; tighten industry filters or raise the score threshold. If conversion is over 60 % but MQL volume starves sales, loosen criteria or create fresh engagement hooks. Continuous calibration keeps quality and quantity in balance.
Architecture firm: Fit property developers with ≥ £5 m build budget; Engagement download BIM integration checklist.
Bookkeeping agency: Fit UK SaaS, ARR £1–10 m, Finance Lead; Engagement uploads trial data + views pricing.
Cyber-security MSP: Fit Healthcare or fintech; Engagement attends “Zero-trust roadmap” webinar + requests breach-cost calculator.
Documenting these rules in the CRM and living by them ensures every MQL handed to sales is truly worth a call raising pipeline accuracy, win rates and team trust across the funnel.
Sales reps need more than a pitch deck. They need email templates that don't sound robotic, case studies that prospects recognise themselves in, calculators that quantify ROI, and videos that explain complex value quickly. Build the collateral that makes selling easier.
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