Skip to content
Start free
SourcesPricingUse casesHelpLog in

Lead generation for SaaS companies: a 2026 playbook

Use cases·1 min read·Updated 2026-05-13·4 sections
On this page (4)
  1. 01Step 1 — Define your ICP as filterable criteria
  2. 02Step 2 — Build the list from 2-3 sources
  3. 03Step 3 — Enrich with email + intent signals
  4. 04Step 4 — AI personalise the first touch

Outbound is back. After three years of "inbound only" preaching, the SaaS playbook in 2026 is: tight ICP definition, multi-source list building, AI-personalised first touch, fast follow-up. The cost of outbound dropped 90% with tools that combine LinkedIn + Google Maps + email enrichment in one flow.

This guide is the operator-level playbook used by SaaS founders shipping their first 100 customers.

01

Step 1 — Define your ICP as filterable criteria

Vague ICPs ("B2B SaaS doing $1M-$10M ARR") don't map to scraper filters. Translate into observable signals: industry (LinkedIn industry tag), company size (LinkedIn employee count range), tech stack (BuiltWith / Kavex tech detector), recent hiring (LinkedIn job posts), funding stage (Crunchbase).

Rate
5 credits / result
Look-alike
1 credit
$0.001
credits never expire
Per 1,000
$5.00
5,000 credits
RUN SIZECREDITSCOST
30 results150$0.15
100 results500$0.50
500 results2,500$2.50
1,000 results5,000$5.00
5 credits a result · 1 credit = $0.001 · a run that finds fewer pays less
02

Step 2 — Build the list from 2-3 sources

Single-source lists are weak. The pattern that works:

  • LinkedIn Lookalike — give Kavex 10 of your best customers, get 30 similar companies
  • LinkedIn Triggers — set up a watch for funding announcements in your category
  • Google Maps — for local-business SaaS (restaurants, salons, dentists)
  • LinkedIn Company People — pull the actual buyer name + role at each target
03

Step 3 — Enrich with email + intent signals

Email Finder + Email Verifier to get to deliverability ≥98%. Tech Stack Detector to score "this company uses our integration" leads higher.

04

Step 4 — AI personalise the first touch

Kavex AI Personalizer takes the lead's context (industry, headline, recent LinkedIn post, tech stack) and writes a 60-word cold email in your sender voice. Reply rates 3-5× higher than generic mail-merge.

Written after running it
Last run
plumbers · London · Google Maps
Rows
30
Time
23s
Cost
€0.06
30 rows × 2 credits = 60 credits · 1 credit = $0.001

Every number on this page comes from that run, not from a price list.

05

Questions people ask

How many leads do I need to send to get 5 demos?

With 60% deliverability + 4% reply rate + 50% qualification: about 400 emails per 5 demos. Tighter ICP + better personalisation can push that to 200 emails.

What's a realistic monthly budget on Kavex?

For a 1,000-lead/month outbound motion: ~10,000 credits ($10). Compare to Apollo Pro ($79/seat/month), Lusha ($99+), Outreach ($100+/seat).

Priced against
Kavex vs ApolloKavex vs LushaKavex vs ClayKavex vs Cognism
Keep readingThe pages people open after this one.
560 in the help centre
01Real estate prospect list building (agents, investors, mortgage brokers)Build targeted prospect lists for real estate: agents by city, mortgage brokers, FSBO leads, expired listings.Use cases02Recruiter sourcing playbook with LinkedIn dataHow recruiters build candidate shortlists from LinkedIn data without LinkedIn Recruiter.Use cases03Competitor monitoring: catch funding, hiring spikes and product launchesTrack funding rounds, C-level changes, hiring spikes, product launches at competitors via LinkedIn — daily alerts for 100 credits.Use cases
Point it at something. See what comes back.Your first 500 Google Maps leads are on the house. No card needed.
Start scraping free →