Twitter DM automation changed everything for our outbound strategy. In just 30 days, we booked 15 qualified sales calls with decision-makers at B2B SaaS companies. Here's exactly how we did it.
The Challenge: Cold Email Was Dying
Our cold email campaigns were getting worse every month with 23% open rates down from 45%, 1.2% reply rates mostly "not interested", deliverability issues plaguing every campaign, and prospects telling us they get 100+ cold emails per day. We needed a new channel. Enter Twitter DMs.
Why Twitter DMs Work in 2025
Twitter DMs have several advantages over email:
1. Less Competition
Most prospects receive 50-200 cold emails daily, but only 0-5 cold DMs. Your message actually gets seen.
2. Social Proof Built-In
Recipients can see your profile, recent activity, and mutual connections before responding. This builds trust immediately.
3. Higher Engagement
Our Twitter DM campaigns achieved 89% delivery rate vs 72% for email, 8.7% reply rate vs 1.2% for email, and 5.3% positive reply rate vs 0.6% for email.
Step 1: Account Setup & Warm-Up
Don't skip this step. Going from 0 to 450 DMs overnight will get you banned.
Our Warm-Up Schedule:
- Week 1: 10-20 DMs per day
- Week 2: 50-100 DMs per day
- Week 3: 150-250 DMs per day
- Week 4+: 300-450 DMs per day (max limit)
Critical Setup Steps:
- Use aged accounts (3+ months old minimum)
- Get verified (blue checkmark increases deliverability by 40%)
- Complete your profile (bio, website, profile image)
- Post regularly (3-5 tweets per week minimum)
- Engage organically (like, retweet, comment)
Step 2: Target the Right People
We didn't message everyone. We filtered aggressively for job title (Founder, CEO, Head of Sales, VP Marketing), company size (10-200 employees), industry (B2B SaaS, agencies, consulting), activity level (tweeted in last 30 days), and engagement signals (posted about lead generation, sales, or growth).
How to Find Them:
- Search Twitter for keywords: "need more leads," "sales pipeline," "outbound strategy"
- Check who's engaging with competitor content
- Look at followers of industry influencers
- Use AI filtering to identify buying signals
Step 3: Craft Messages That Convert
Forget generic templates. Here's what worked.
The Winning Message Structure:
Line 1: Specific observation about their content/business
Line 2: One sentence of value (insight or compliment)
Line 3: Soft question or conversation starter
Why This Works:
- Personalized (references their specific content)
- Provides value (shares a data point)
- Low pressure (asks a question, not pitching)
- Conversational (sounds human, not like a sales robot)
Step 4: The Follow-Up Sequence
Most people don't respond to the first message. Our sequence was:
Message 1 (Day 1): Initial Value
Your opening message with observation and question.
Message 2 (Day 3): Case Study
Following up with case study mentioning similar companies helped and offering to share details if interested.
Message 3 (Day 6): Breakup Message
Acknowledging their busy schedule, removing pressure with "breakup" language, and leaving door open for future.
The "breakup" message gets the highest response rate (40% of our replies came from this message).
Step 5: Multi-Threading
Don't just message one person at a company. We messaged Founder/CEO (vision and strategy angle), Head of Sales (pipeline and quota angle), and Marketing Lead (channel diversification angle).
This increased our chances of getting a response by 3-4x and often created internal conversation about our solution.
Step 6: Qualification & Booking
When someone responds positively, we qualify them with 2-3 questions about their current lead generation process, what's working and what's not, and what would their ideal system look like.
If they're qualified (budget, authority, need, timeline), we send a calendar link with a personalized message.
The Results: 15 Calls in 30 Days
Here's the complete breakdown: 2,847 messages sent, 89% delivery rate (2,534 delivered), 8.7% reply rate (220 replies), 5.3% positive replies (134 interested), 15 calls booked, 0.53% booking rate, and $31 cost per call vs $127 for cold email.
Quality of Calls:
- 12/15 were qualified (80% qualification rate)
- 4 became customers within 60 days
- 5 still in pipeline
- 3 not ready now but staying in touch
What We Learned
What Worked:
- ✅ Hyper-personalization (referencing specific tweets/content)
- ✅ Value-first approach (giving before asking)
- ✅ Multi-threading (messaging multiple stakeholders)
- ✅ Breakup messages (removing pressure increased responses)
- ✅ Targeting active users (tweeted in last 30 days)
What Didn't Work:
- ❌ Generic templates (flagged as spam immediately)
- ❌ Pitching in first message (scared people away)
- ❌ Messaging inactive accounts (wasted messages)
- ❌ Ignoring account warm-up (got temp-banned twice)
- ❌ Sending identical messages (Twitter caught on)
Summary
The playbook above is exactly what we used to book 15 calls in 30 days. Doing this manually is time-consuming and error-prone. That's why we built Scrapely—to automate the execution while maintaining the personalization that drives results.