How Eloverde Eliminated Its SDR Role Using Chattie on LinkedIn

Disclosure: This article was written by Thiago Lisboa, CEO and co-founder of Chattie. The case study is based on real results reported by Marcelly Machado, with her consent. Competing products are mentioned as referenced by the customer.

The Challenge: A Human SDR Bottleneck on LinkedIn

Marcelly Machado leads demand generation at Eloverde, a B2B company operating in a competitive niche where personalized LinkedIn outreach is the primary acquisition channel. Like most demand gen leads, she faced a classic problem: LinkedIn prospecting at scale requires time, consistency, and memory — three things a single SDR can only partially provide.

The traditional setup looked like this:

• 1 SDR dedicated to LinkedIn connection campaigns
• Manual connection requests sent in batches of 20–30 per day (LinkedIn's safe manual ceiling)
• Follow-up messages tracked in spreadsheets and often delayed or missed
• Pipeline reporting based on memory and incomplete notes

The SDR was a cost center, not a revenue multiplier. Salary, benefits, and onboarding overhead made the math difficult — particularly when results were inconsistent month to month.

Marcelly had evaluated Apollo.io and several US-based tools. The pricing was hard to justify for a Brazilian B2B operation, and the support was asynchronous, English-first, and disconnected from the LinkedIn-native workflow her team actually used.

The Decision: AI Over Headcount

Before implementing Chattie, Eloverde's prospecting metrics looked like this:

Marcelly's goal was not simply to automate what the SDR was doing. She wanted to replace the strategic bottleneck entirely and redirect her Lead Development Representative (LDR) toward higher-value activities: nurturing pipeline conversations, refining ICP messaging, and preparing qualified leads for the sales team.

She started with Chattie in Q1 2026.

Implementation: The AI Calibration Period

The first two weeks were dedicated to setup: ICP definition, message sequence configuration, and connection targeting. Chattie's AI calibration — the process by which the platform learns which lead responses signal genuine interest versus automated replies — began within the first 300 interactions.

What stood out for Marcelly was the absence of a steep learning curve. Unlike Apollo's multi-step sequence builder or Clay's enrichment-heavy workflow, Chattie operates natively inside LinkedIn. The SDR interface is the LinkedIn inbox itself, with Chattie layering context, history, and suggested next actions on top.

By week three, the system was running without daily intervention from Marcelly or the LDR.

Results After 90 Days

"I rolled out Chattie and eliminated the SDR role: my LDR now works on strategy. The AI calibrated itself. Compared to Apollo and pricey US tools, it delivers far more — with real-time Portuguese support. The ROI is relentless." — Marcelly Machado, Demand Generation Lead, Eloverde

Here is what changed at Eloverde after 90 days of active Chattie use:

The reply rate improvement — from 12–16% to 26–31% — reflects two compounding effects: higher volume reaching the right profiles, and better-timed follow-up sequences that Chattie manages automatically.

The SDR Elimination Decision

Eliminating a full-time SDR was not a cost-cutting measure. It was a structural realignment. The SDR's core LinkedIn tasks — connection management, follow-up, conversation routing — were now handled by Chattie at 3× the volume and consistently higher quality.

The money saved on SDR headcount (~R$6,500/month fully loaded) more than covered Chattie's subscription. The net effect was a demand generation function that was both cheaper and more productive.

The LDR, no longer occupied with operational LinkedIn tasks, shifted focus to:

• Refining ICP segments based on Chattie's engagement data
• Preparing warm leads for handoff to the closing team
• Testing message frameworks in coordination with Marcelly
• Monitoring conversation health across active prospect threads

This is the structural shift that separates AI-augmented demand gen from traditional SDR models: the human's time goes to judgment and strategy, not to manual inbox management.

Why Chattie Over US Tools

Marcelly's prior evaluation included Apollo.io and two unnamed US-based platforms. Her objections were practical:

1. Pricing in USD — at current FX rates, US tool subscriptions represent a significant cost premium for Brazilian operations
2. English-first support — async support with English-language documentation is a genuine friction point for PT-BR teams
3. LinkedIn-native integration — Apollo and Clay are powerful for email sequences and data enrichment but require additional middleware to operate natively on LinkedIn
4. AI calibration approach — Chattie's AI learns from live LinkedIn response patterns rather than requiring manual sequence configuration for each ICP variation

For Eloverde's use case — PT-BR B2B outreach on LinkedIn as the primary channel — Chattie's native approach was a better fit.

Key Takeaways

What made this work:

• Clear ICP definition before launching. Chattie's results are directly proportional to how precisely the lead targeting is configured.
• Commitment to the calibration period. The first 2–3 weeks require volume to train the AI's response classification. Teams that stop early miss the compound gains.
• LDR redeployment plan. The SDR elimination only created value because the LDR had a defined strategic role to move into. Without that, the freed capacity is wasted.

When this model works best:

• B2B teams where LinkedIn is the primary prospecting channel
• Operations with a single SDR or small outreach teams where headcount costs are a real constraint
• Demand gen leads who want to shift from operational to strategic work
• Companies that have previously evaluated US tools and found the FX cost or integration overhead prohibitive

The Broader Pattern

Eloverde's result is not an outlier. Across Chattie's customer base — 500+ campaigns, primarily B2B SaaS and services in Brazil and LATAM — teams that implement with a clear ICP and a defined follow-up sequence see reply rates between 24–34% within the first 60 days.

The SDR-to-AI transition is not a trend. For LinkedIn-native B2B operations in the Brazilian market, it is increasingly the default architecture.

Want to see if Chattie fits your operation? Start here.