Who is the client?
KlientBoost is a world-class performance marketing agency led by CEO Jonathan Dane.
They focus on quantifiable business outcomes such as lowering CPA, improving ROAS, and increasing conversion rates. Their ideal clients are SaaS and eCommerce companies with significant digital ad spend.
Their value proposition is built around measurable results, which makes their go to market motion highly dependent on engaging the right accounts with the right timing and context.
Context
At the time, KlientBoost had scaled to roughly $20M in annual recurring revenue.
Which came with:
KlientBoost needed a system that could systematically capture high intent signals across the web, re engage past relationships with precision, and turn intent into sales ready opportunities through a value led experience.
The goal was to build an evergreen engine that converts prospects into inbound style opportunities using automation, signal capture, and integrated RevOps workflows.
This engagement was part of a partnership with Growth Alliance.
What was the problem?
Despite strong traffic and brand presence:
They weren't missing activity. They were missing coordination.
Without a unified system, traffic, database history, social engagement, and signals were operating in silos instead of driving one cohesive demand motion.
The approach we took
We designed and deployed a custom signal based ABM engine built around KlientBoost's Marketing Plan 2.0 offer.
The objective was to convert their existing assets into a structured and scalable demand system. This included:
The full system was architected and implemented within three months. It was organized into five strategic play groups, each aligned with KlientBoost's growth stage and market position.
1. Website Intent Plays
KlientBoost was generating consistent traffic across high value service pages. We built structured plays that:
This ensured that outreach reflected real interest and real timing. Website engagement became an active pipeline driver.
2. Closed Lost and Past Pipeline Reactivation
KlientBoost had years of historical deal and lead data. We structured a reactivation framework that:
This transformed past pipeline into a monitored opportunity layer.
3. Signal Based Prospecting
We implemented outbound plays triggered by observable market activity. Signals included:
Outbound was initiated based on movement in the market, not static lists. This created a higher quality entry point into conversations.
4. LinkedIn Engagement Engine
KlientBoost had an established LinkedIn presence with consistent engagement. We structured this channel into a measurable pipeline contributor by:
LinkedIn activity was integrated directly into the ABM system.
5. Marketing Plan 2.0 Core Engine
At the center of the system was Marketing Plan 2.0. When a prospect engaged:
This created a controlled conversion path from interest to qualified conversation.
Results
Within 3 months, KlientBoost had: