Day 4 of 28 · AI Job Hunt
Finding Your Target Role
⏱ 5 min
📊 Beginner
"What job should I go for?" is the question that paralyzes most job seekers. They either aim too low (staying in the exact same role) or too vague (browsing everything and applying to nothing).
Today, AI helps you answer this with data — not guesswork.
From vague ideas to precise targets with AI research.
The role-fit matrix
Most people search for jobs by title. That's a mistake. The same work can be called completely different things at different companies.
The better approach: search by skills and outcomes, not by title. AI can map your skills to roles you've never even considered.
Here's my background: 5 years as a customer success manager at a B2B SaaS company. I manage 40 accounts ($2M ARR), handle renewals, run QBRs, and work closely with the product team on feature requests. I'm looking for a role that pays more and has more strategic responsibility. What roles should I target?
Based on your experience, here are your best target roles — ranked by fit and earning potential:
**Tier 1 — Direct fit (easiest pivot):**
- **Senior Customer Success Manager** — Your natural next step. $95K-$130K. Same work, more accounts and strategic responsibility.
- **Customer Success Team Lead/Manager** — Managing a team of CSMs. $110K-$145K. Your account management + QBR experience positions you well.
**Tier 2 — Strategic pivot (leverage your skills differently):**
- **Account Manager / Account Executive** — Move to the revenue side. $100K-$160K+ with commission. You already manage renewals and relationships.
- **Solutions Consultant / Sales Engineer** — Use your product knowledge to support sales. $110K-$150K.
**Tier 3 — Ambitious but achievable:**
- **Head of Customer Success** — At a smaller company (Series A/B), your experience managing $2M ARR could qualify you. $130K-$170K.
- **Product Manager** — You already translate customer needs to product teams. Would need to emphasize the product side. $120K-$160K.
My recommendation: Apply to Tier 1 and Tier 2 simultaneously. Tier 1 gets you callbacks fast. Tier 2 gets you the pay jump.
↻ Replay conversation
Knowledge Check
Why is searching by job title a limited strategy?
A
Job titles are being eliminated by companies
B
The same work can have completely different titles at different companies — searching by skills and outcomes casts a wider, smarter net
C
Recruiters don't look at job titles
D
Job titles don't appear in search results
A "Customer Success Manager" at one company might be called "Client Partner" or "Account Strategist" at another. If you only search by your current title, you miss roles that are a perfect fit. AI helps you think in terms of skills and outcomes, which opens up opportunities you'd never find otherwise.
The market research step most people skip
Before you start applying, spend 15 minutes having AI research your target market. This one step prevents weeks of wasted effort.
I'm targeting Senior Customer Success Manager and Account Manager roles in B2B SaaS. Before I start applying, tell me: What are companies looking for in these roles right now? What skills are in highest demand? What should I emphasize and what should I avoid?
Here's your market intel:
**What's in high demand (emphasize these):**
- Revenue retention and expansion metrics (NRR, GRR)
- Experience with enterprise accounts ($100K+ ARR)
- Cross-functional collaboration (product, sales, engineering)
- Data-driven customer health scoring
- Experience with tools: Gainsight, Salesforce, ChurnZero
**What's becoming less valued (de-emphasize):**
- "Relationship management" without metrics
- Reactive support (companies want proactive strategy)
- SMB-only experience when targeting enterprise roles
**Red flags hiring managers watch for:**
- No mention of revenue impact or retention numbers
- Generic descriptions like "managed client relationships"
- Gaps between technical fluency and strategic thinking
**Your cheat code:**
The #1 thing that separates callbacks from silence: **quantified business impact.** Not "managed accounts" but "managed 40 accounts totaling $2M ARR with 95% retention rate."
Lead with numbers. Always.
↻ Replay conversation
Knowledge Check
What's the most important thing to emphasize when applying for customer-facing roles in B2B SaaS?
A
A long list of software tools you've used
B
Quantified business impact — revenue numbers, retention rates, and specific metrics that show your value
C
The number of years you've worked
D
The name of the company you worked for
Hiring managers want to know what you achieved, not just what you did. "$2M ARR portfolio with 95% retention" tells them exactly what you're worth. "Managed client relationships" tells them nothing. Numbers are the language of hiring.
Narrowing your target list
Now that you know which roles to target, narrow down the companies. Ask AI to help you build a target list based on what matters to you:
"I'm looking for B2B SaaS companies that are Series B or later, have 100-500 employees, are growing their customer success team, and are based in [city] or fully remote. Give me 15 companies to research."
Then take that list and research each one with Perplexity — recent funding, product launches, Glassdoor reviews, growth trajectory. This turns a scattered job search into a focused campaign.
The people who land jobs fastest don't apply to 200 companies. They deeply target 20-30.
Final Check
What's more effective for landing a job?
A
Waiting for recruiters to find you
B
Deeply targeting 20-30 companies with tailored applications based on AI-powered research
C
Only applying to companies you've heard of
D
Applying to 200+ companies with a generic resume
Targeted beats scattered every time. Twenty tailored applications with company-specific research will generate more callbacks than 200 generic ones. AI makes this deep targeting possible because it does in 5 minutes what used to take 2 hours of manual research.
🧭
Day 4 Complete
"Don't search for a job title. Search for the intersection of your skills, your ambition, and the market's demand. AI finds that intersection fast."
Tomorrow — Day 5
Decoding Job Descriptions with AI
Tomorrow you'll learn to read between the lines of any job posting — and spot what they really want.