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Case study

Colado

Outbound systems and GTM strategy that generated qualified pipeline.

Reply rate

0x

vs. previous baseline

Qualified meetings / mo

0

net-new pipeline

Days to first booked call

0

domain + copy + list

01

The problem

Colado had an incredible product but lacked a systematic way to generate predictable pipeline. Relying entirely on organic word-of-mouth creates feast-or-famine cycles that prevent true scale. They needed a repeatable motion that worked instantly.

02

The insight

Decision-makers were ignoring standard feature-based pitches. They didn't care about the product's UI; they cared about how it solved their specific bottleneck. We needed to transition from "selling software" to "selling an outcome."

03

The strategy

We rebuilt their positioning around specific pain points. Instead of a single broad campaign, we architected multiple highly segmented outbound sequences targeting distinct buyer personas with hyper-relevant offers.

04

The execution

Over 4 weeks, we stood up dedicated outbound infrastructure, warmed up domains to ensure maximum deliverability, and deployed our sequences. We split-tested hooks weekly to find resonance quickly and doubled down on what worked.

Experiment log

  1. Week 1 - ICP & positioning teardown5 days

    Collapsed 3 generic personas into 2 sharp ICPs. Rewrote positioning around a bottleneck each ICP already feels weekly.

  2. Week 2 - Outbound infra7 days

    Provisioned sending domains, warmed inboxes, configured deliverability, mapped CRM handoff.

  3. Week 3 - Sequence v1 launch5 days

    Two segmented sequences live. Hook A/B testing weekly, tight feedback loop with founder.

  4. Week 4 - Double-down5 days

    Killed 3 underperforming variants, scaled winning hook 3x, opened a second ICP in parallel.

Outcome

What we delivered

  • Significant traction via net-new outbound pipeline
  • Absolute clarity on ideal customer profile (ICP) positioning
  • Automated, scalable outbound engine built for the long term
T
Insights by Tanmay

You don't have a pipeline problem; you have a relevance problem. The moment we killed the generic feature pitch and built micro-targeted outbound sequences, Colado's response rates 4x'd. Predictable pipeline isn't magic, it's math and precision.