Lead generation software for six specific jobs
This is what teams actually do with a finder and a verifier. Each of these is a real workflow with its own shape, its own plan requirements and its own way of going wrong.
Turn a list of companies into verified decision makers
Your target account list already exists. What you do not have is the person, and the research to get there is where a sales development rep's week disappears.
Plan to look at: Growth, for bulk jobs up to 10,000 rows and native CRM export.
- Upload the account domains and run a domain search across all of them in one job.
- Filter to the departments and seniority levels that sign for your product.
- Exclude role addresses and anyone already in the CRM.
- Verify what is left and push the deliverable rows into the sequence.
Keep several clients apart and prove where every address came from
An agency running outreach for a set of clients has a problem a single company does not: the data cannot mix, the quotas cannot mix, and when a client asks where an address came from there has to be an answer.
Plan to look at: Scale, for workspaces, roles, the audit log and the API.
- A workspace per client, each with its own quota, saved searches and suppression list.
- Role based access control, so a contractor sees one client and not the rest.
- An audit log of every search, export and API call, with who ran it and when.
- Per client export straight into that client's own CRM.
Find the work address for a named candidate at a named employer
Recruiting runs in bursts. An open role means fifty profiles in two days, then nothing on that role for a month. Paying per attempt punishes exactly that pattern, because most of those fifty will not resolve.
Plan to look at: Starter for a solo recruiter, Growth for a sourcing team.
- Take the name and the current employer from the profile you are reading.
- Resolve and verify the work address, which is where a candidate actually reads mail during the working day.
- The names you cannot resolve cost nothing, so a low hit rate on a hard role is not an expensive day.
Re-check what you already have, before the big send
The addresses in your CRM were correct on the day they were entered. Staff turnover alone means a meaningful share of a B2B database stops being deliverable within a year, and nothing in the record changes to tell you.
Plan to look at: Growth for scheduled re-verification, Scale for the API.
- Save the list and set it to re-verify on a schedule.
- Rows that stopped being deliverable are flagged before the campaign, not by the campaign.
- A re-check of an address you already verified does not spend your limit again in the same period.
- With the API, verification runs at the moment a record is created or updated.
Verify a badge scan list before the follow up goes out
Badge scanners and webinar sign up forms produce typos, personal addresses and deliberately fake entries. Sending to that list the day after the event is how a warm audience turns into a deliverability problem.
Plan to look at: Starter or Growth, depending on the size of the event.
- Run the whole list through bulk verification the day you get it.
- Drop the undeliverable rows and separate the consumer addresses from the work ones.
- Send the follow up to the rows that passed, while the event is still recent.
A new sending domain has no reputation to spend
When you move to a new sending domain, every bounce counts double, because the domain has no history to absorb it. The first campaigns from a new domain decide how the next year of your mail is treated.
Plan to look at: Growth or Scale, depending on how large the base list is.
- Clean the whole base list before the first send from the new domain.
- Start with the rows that came back deliverable and leave the catch-all rows for later.
- Keep the suppression list attached, so a rejected address never comes back into a send.
What a sales prospecting software purchase has to survive
The person approving this is not going to run a search. They are going to ask four questions, and the answers are all on the security page.
- Where the data comes from and on what legal basis we hold it.
- What happens when a person asks to be erased, and how we prove it happened.
- Who inside the buying company can see and export what.
- What the spend does when usage grows, which is where a per unit credit model stops being predictable.