Sales automation that lifted lead-to-project conversion by 40% for a software services firm

Strong lead generation, weak conversion. AI-driven scoring, engagement, and follow-up turned a slow, manual pipeline into one that responds in minutes and prioritises the prospects most likely to buy.

Client
Software services company
Industry
Professional services
Engagement
AI sales automation platform
Abstract composition for Sales automation that lifted lead-to-project conversion by 40% for a software services firm
  • 40% higher

    Lead-to-project conversion

  • 65% faster

    Response to inbound leads

  • 50% lower

    Manual qualification effort

  • 35% shorter

    Sales cycle

  • 30% more

    Qualified opportunities

Context

The client generated leads through digital marketing, referral networks, and outbound sales, and lost too many of them between first contact and signed project. Inquiries waited for a reply. Qualification was manual and inconsistent. Follow-up depended on which channel a lead had used and who happened to own it. Nobody could see which prospects carried real purchase intent, or how the pipeline was actually performing.

Constraints

The system had to work across email and messaging channels the sales team already used, feed the existing pipeline rather than create a parallel one, and leave relationship-building to humans while removing the administrative drag around it.

What we built

An AI sales automation platform: lead scoring and qualification that ranks every inbound prospect; AI agents that engage and nurture leads; conversational chatbots for instant first contact; automated follow-up sequences across email and messaging; predictive analytics that surface the opportunities most likely to convert; automated meeting scheduling and workflow management; and real-time pipeline monitoring with performance reporting.

Architecture

Scoring and predictive models over lead behaviour and pipeline history; conversational agents on web and messaging channels; a workflow engine for follow-up sequences and scheduling; CRM integration as the system of record; a reporting layer over pipeline stages and response times.

conversational agents on web and messaging channels
a workflow engine for follow-up sequences and scheduling
CRM integration as the system of record
a reporting layer over pipeline stages and response times
Architecture overview, drawn from the delivery notes.

Delivery

Discovery traced where leads stalled. Scope defined the qualification rules and which actions the agents could take unaided. Design produced the engagement sequences per channel. Build connected the channels and CRM and trained the scoring model on historical outcomes; weekly demos reviewed real leads moving through the new flow. Verification checked response latency and data integrity before go-live. Run added a monthly model review.

Outcomes

Leads were answered in minutes rather than days, qualification stopped consuming the team's time, and representatives spent their hours on relationships instead of triage. The client acquired more projects from the same lead flow and gained a sales process that scales without adding headcount.

Carried forward

The fastest sales gains rarely come from more leads. They come from responding to the ones you already have before they go cold, and letting a model decide who gets the first call.

Delivered by Qantara's engineering organisation.

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