Solutions
Lead qualification, before you send a single message
Most teams qualify leads after they send, when the silence tells them who never fit. Nidaflow qualifies first: every lead it delivers has a fit, a reason with its source, and proof that the person works there now.
The problem, and what it costs
Qualification usually happens in the wrong place. A rep pulls a list, sends to all of it, and learns from the replies who was never a buyer. By then the messages are gone.
Every send to someone who does not fit has a price. It uses up your daily sending limit. It puts your name in front of a person who will remember it badly. And it hides the few real replies in a pile of noise that someone has to read.
The slower version is checking by hand. A person opens each profile, reads the company page, guesses the size, and decides. That is real qualification, but it does not scale, and two people reading the same row will often disagree.
What teams need is a judgement they can read and argue with: this lead fits, for this reason, and here is the source.
How Nidaflow qualifies, step by step
Step one: define who fits. Paste your website and Nidaflow saves a draft buyer profile with the titles that buy, your market and who your competitors sell to. You edit it until it says what you mean. A search uses the profile only if you say yes.
Step two: search in plain words. Describe the role, the seniority, the kind of company, the size and the market. Nidaflow looks at many more people than you will ever message.
Step three: read the evidence. Every lead is judged against your offer and your buyer profile, using everything gathered about the person and the company. The result is one label, Strong, Good or Possible, with a one or two line reason that cites its source.
Step four: see the checks that can be proven. Company size, market, industry, role and funding appear only where a data field proves them. Each is Passed or Not met. A check we cannot prove is not shown, and it is not guessed.
Step five: no evidence, no Strong. A thin row cannot be graded Strong, and a reason can cite only what the row holds. If a company sells something similar to you, the row says so, because that changes how you write to them.
Step six: prove the job. A person is delivered only when Nidaflow can show that they work there now, with the source and the date on the row. People who cannot be proven are left out. People who have moved are checked again at the new company.
What you get
- A fit you can read: Strong, Good or Possible, with the reason and the source.
- Checks that are shown only when the data proves them.
- Leads that do not fit are left out, and leads whose job cannot be proven are left out too, and neither is charged.
- Possible leads are delivered and charged, so you can decide how far down to go.
- The same qualified list goes straight into a sequence across email, LinkedIn and WhatsApp.
- The whole app works in English and Arabic, right to left.
Example: qualifying 1,000 people
Example. These numbers are illustrative, not a customer result. A search looks at 1,000 people.
400 are left out because they do not fit. 210 are left out because Nidaflow could not confirm that they still work there. Neither group is charged, so 610 people never reach your outreach and cost you nothing.
390 are delivered, each with a label and a reason: 60 Strong, 150 Good and 180 Possible. That is 780 credits at 2 credits each.
You choose to reach the 210 Strong and Good first, and keep the 180 Possible for later. Reaching those 210 in one sequence adds about 1,400 credits for emails, sequence entries, messages and recent news, so the whole run is about 2,200 credits.
The qualification itself, the part that decides who is worth a message, is the first 780 credits. The rest is the outreach you chose to run.
Who it is for, and who it is not for
It is for teams that already know who they sell to and are tired of finding out the hard way who they do not. It suits founders doing their own outbound, sales teams with a clear profile, and agencies that must show a client why each person was chosen.
It is not a score. Nidaflow does not give a number out of any scale, and it does not predict who will buy. It is also not for imported lists. If you upload a CSV, Nidaflow finds emails, phone numbers and company facts for it, but it does not run the fit check or the job proof on those rows. Qualification applies to leads that Nidaflow finds.
Questions, answered.
What does qualification mean here?
Each lead is judged against your offer and your buyer profile and given one label, Strong, Good or Possible, with a short reason that cites its source. The person's current job is also proven. Leads that fail are left out and not charged.
How does a lead earn Strong?
By evidence. A thin row cannot be graded Strong, and a reason can cite only what the row holds. A lead with little on file is more likely to be Possible than Strong.
Is there a score from zero to one hundred?
No. Nidaflow gives three labels and a reason. It does not give a numeric score and it does not predict who will buy.
Can I qualify a list I upload?
No. An imported CSV is enriched with emails, phone numbers and company facts. It does not get the fit check or the job proof. Leads that Nidaflow finds do.
What happens to leads that do not fit?
They are left out of your list, and the app tells you how many were left out and that they were not charged. You are charged for delivered leads only.
How do you prove that someone still works there?
With one of four sources: their LinkedIn profile shows the job as current, a profile record shows it with a matching company domain, the company's team page names them, or their own recent post mentions the company. The row shows which source and the date.