Every sales team knows the problem. You get a list of 2,000 contacts. You run a campaign. Bounce rate is 18%. Open rate is 22%. Reply rate is 0.8%. Two replies are from people who have left the company. You conclude the campaign didn't work.
But the campaign didn't fail. The list did.
According to Landbase's analysis of outbound sales data, bad outbound data costs enterprise sales teams $600,000–$1.25 million annually in wasted SDR capacity alone. And email databases decay at 22% per year — meaning nearly a quarter of any list you bought six months ago is already out of date.
What Makes a List Bad
Most prospect lists fail for one of five reasons:
- Wrong ICP — the contacts match the job title but not the buying context (company size, industry vertical, tech stack, growth stage)
- Stale data — the contacts have changed roles, left the company, or been promoted out of relevance
- Invalid emails — scraped addresses that were never verified, causing bounces that damage sender reputation
- No intent signals — the list has no indication of who is actively in-market vs. who is completely passive
- Missing context — no information about what the prospect has recently done, said, or signalled that would make personalisation possible
The research from RevSure is unambiguous: companies with a clearly defined ICP see 36% higher conversion rates, and ICP-fit deals close at 68% vs. 22% for non-ICP accounts. The quality of your list determines most of your campaign's outcome before a single email is sent.
How We Build Lists
Stage 1: ICP Definition Workshop
Before we research a single contact, we spend time with the client defining the exact ICP. This means getting specific: not "B2B SaaS companies" but "B2B SaaS companies with 50–200 employees, post-Series A funding, with a sales team of 5+ people, using HubSpot or Salesforce, and actively hiring SDRs." The more specific, the better the list.
Stage 2: Multi-Source Research
We don't use a single database. We combine LinkedIn Sales Navigator, Apollo, Companies House data (for UK companies), Crunchbase funding signals, job posting data (companies hiring for specific roles are often in-market for relevant services), and web presence data. Each source adds a layer of context.
Stage 3: Manual Verification and Enrichment
Every contact is verified before it enters the list. We check that the person is still at the company, still holds the title, and that the company still matches the ICP criteria. We enrich with direct email (not just generic company format), LinkedIn URL, and any recent activity signals — conference talks, published articles, social posts — that allow for genuine personalisation.
Stage 4: Email Validation
All emails are validated through a multi-step verification process before delivery. We target a bounce rate of under 2%. Industry average for purchased lists is typically 8–15%. The difference is material: high bounce rates damage sender reputation, which reduces deliverability of future campaigns.
What the Output Looks Like
A list we deliver includes:
- First name, last name, job title, company name
- Verified work email (direct format, not info@)
- LinkedIn profile URL
- Company website, employee count, industry, location
- Funding stage (where relevant)
- Tech stack signals (where relevant)
- One or two personalisation notes per contact (recent activity, published content, shared connection)
For a typical campaign list of 500 contacts, expect a bounce rate under 2%, an open rate 15–20 percentage points above industry average, and reply rates 3–5x higher than scraped data — because the people on the list are actually the right people, and the personalisation data makes the outreach feel relevant.
The Right List Changes Everything
The best copywriter in the world can't save a bad list. And a mediocre message sent to exactly the right person at exactly the right time will almost always generate a response.
We've seen clients triple their reply rates simply by replacing their existing database with a properly built, verified, enriched list. Same email copy. Same sequence structure. Different list. Completely different results.
If your outreach numbers are disappointing, the first thing to fix is the list.