Original research · Kachilu beta results
LinkedIn outreach results report: what happened across 35,292 approaches
Across 35,292 LinkedIn approaches, Kachilu reached a relevant CTA in 29% of cases. Kachilu Scout, which connected with a message before engaging with a prospect's posts, reached roughly 10%—making the observed Kachilu rate 2.9 times higher.
35,292
Kachilu approaches
Prospects that entered the Kachilu LinkedIn outreach workflow during the beta period.
29%
Kachilu CTA reach rate
Share of Kachilu approaches that reached the campaign's relevant next step.
~10%
Scout CTA reach rate
Approximate share of predecessor Kachilu Scout approaches that reached the CTA.
Same denominator: approaches initiated
CTA reach increased from about 10% to 29%
The measured difference is 19 percentage points, or 2.9 times the Scout baseline. The central workflow change was whether personalized engagement happened before the connection request.
2.9×
higher CTA reach rate
Kachilu Scout
about 10%
Kachilu
29%
Direct-first workflow
Kachilu Scout
- 1Identify a prospect
- 2Send a connection request with a message
- 3Send the job description as the CTA
Engagement-first workflow
Kachilu
- 1Research the prospect and relevant posts
- 2Add a personalized like or reply
- 3Send a personalized connection request
- 4Introduce the relevant CTA in context
Key takeaways
- Kachilu's CTA reach rate was 29%, compared with roughly 10% for predecessor Kachilu Scout: a 19-point increase and 2.9 times the historical rate.
- Scout sent a message with the connection request and then the job description; Kachilu first creates a personalized touchpoint through a relevant like or reply.
- We believe the engagement-first workflow contributed to the improvement, but this historical comparison does not isolate causation.
Written by
Kachilu Research
Product research and editorial team
Reviewed by
Kachilu Product Team
Editorial and product review
The team responsible for reviewing metric definitions, product behavior, and the limitations stated in this report.
The result: CTA reach rose from about 10% to 29%
Kachilu reached a relevant CTA in 29% of 35,292 initiated approaches. At the same funnel stage, predecessor Kachilu Scout historically reached roughly 10% of initiated approaches.
That is a 19-percentage-point increase and a relative rate 2.9 times higher. At 29% of 35,292 approaches, approximately 10,235 prospects reached the CTA stage in the Kachilu aggregate.
| Product | CTA reach rate | Workflow before connection |
|---|---|---|
| Kachilu Scout | About 10% | No required post engagement; connection request with a message. |
| Kachilu | 29% | Personalized like or reply, then a personalized connection request. |
What changed between Scout and Kachilu
Kachilu Scout used a direct-first sequence. It sent a connection request with a message without first liking or replying to the prospect's posts, then delivered the job description as the CTA.
Kachilu requires a personalized engagement step first. It researches the prospect, likes or replies to a relevant post, and only then sends a personalized connection request. The CTA is introduced after that context has been established.
Why personalized engagement may have improved CTA reach
A relevant like or reply gives the prospect a recognizable interaction before the connection request arrives. The subsequent message can refer to the prospect's actual role or post rather than beginning as an unexplained pitch.
We believe this individualized context was a major contributor to the higher CTA reach rate. The data is consistent with that interpretation, but it does not prove that the engagement step alone caused the full difference.
How to apply the finding to your own LinkedIn outreach
- 1.Define one measurable CTA and keep initiated approaches as the denominator.
- 2.Create a relevant touchpoint through the prospect's own content before sending a connection request.
- 3.Personalize the connection message from the prospect's role, company, or post instead of inserting a generic pitch.
- 4.Compare engagement-first and direct-first cohorts before increasing volume.
Comparison method and limitations
Kachilu's 29% rate uses aggregated beta event records available by August 19, 2026, with 35,292 initiated approaches as the denominator. Scout's approximately 10% is a historical product rate using the same funnel denominator.
This is a product-period comparison, not a randomized test. The CTA can be a job description, meeting, demo, product page, or another campaign-defined next step. No names, profile URLs, messages, or other personally identifying prospect data are published.
- Absolute difference: approximately 19 percentage points.
- Relative difference: 29% divided by 10%, or approximately 2.9 times.
- Kachilu CTA count: approximately 10,235, rounded from 29% of 35,292 approaches.
- The comparison does not isolate audience, offer, account history, timing, or message quality.
FAQ
Frequently asked questions
How much did CTA reach improve from Scout to Kachilu?
The observed rate increased from about 10% of initiated approaches in Kachilu Scout to 29% in Kachilu. That is an increase of about 19 percentage points and a relative rate 2.9 times higher.
What counts as an approach?
An approach begins when a qualified prospect enters the controlled LinkedIn outreach workflow. It does not necessarily mean that a sales pitch was sent immediately.
What does CTA reach mean?
It means the outreach progressed to the campaign's relevant next step, such as a job description, meeting, demo, or product destination. The denominator is initiated approaches for both products.
Does the comparison prove that likes and replies caused the improvement?
No. Personalized engagement is the central workflow change and we believe it contributed, but the comparison spans different product periods and does not isolate targeting, audience, account condition, offer, timing, or message quality.
Does this report contain personal LinkedIn data?
No. The public report uses aggregated counts and definitions and does not publish names, profile URLs, message bodies, or other personally identifying prospect data.