Sales & growth ops

Lead scoring

Score local leads on real attributes - ratings, reachability, web presence.

The problem

Why this is hard by hand.

Most lead lists are unscored: every row looks equally promising until a rep wastes time finding out otherwise. Without consistent attributes, you cannot prioritize, so high-value and dead-end leads get the same effort.

biz collect returns the same structured signals for every business - ratings, reviews, whether there is a reachable email and phone, web presence, opening hours - so you can compute a fit or reachability score before a human touches the list. Because the fields are stable, the scoring logic is written once and applied to every lead.

The workflow

How biz collect solves it.

Collect the candidate leads
POST a search for the category and region you sell into, then poll GET /v1/jobs/:id until you have the structured list of businesses to score.
Choose your scoring signals
Decide which fields drive your score - for example, rating and review count for quality, presence of a deduped email and phone for reachability, and a website for web presence.
Normalize the fields
Because every record shares the same schema, normalize the chosen fields into comparable values (for example, 0 to 1) without per-source special cases.
Compute and rank
Combine the normalized signals into a single score per lead and rank the list, so the most reachable, highest-quality businesses rise to the top.
Route the top tier
Send the highest-scoring leads to reps or an outreach sequence first, and tier the rest, so effort follows the score instead of list order.

Fields & endpoints

What you actually use.

ratings, reviews

Quality signals you can weight to favor well-established businesses.

email(s), phone

Reachability signals - a lead with a deduped email and phone is far more workable.

website, social profiles, outgoing links

Web-presence signals that hint at a business's maturity and activity.

live open/closed status, opening hours

Operational signals that help you focus on active, contactable businesses.

stable JSON schema

Same fields every time means the scoring logic is written once, not per source.

Example

Illustrative: prioritizing a regional prospect list

Suppose a growth team has a list of several hundred local businesses from a biz collect search and limited rep capacity. They define a simple score: higher rating and review count raise it, a present email and phone raise it, and a working website raises it.

Because every record has the same fields, they compute the score across the whole list in one pass and route the top tier to reps first. Reps spend their time on reachable, well-rated businesses instead of working the list top to bottom. This is an illustrative scoring approach; the right weights depend on what predicts a good fit for your offer.

Who it's for

Sales and growth ops teams who need to prioritize a finite rep capacity.
Founders running outbound who want to work the best leads first.
Anyone turning a raw local list into a ranked, workable pipeline.

Build it

Everything you need to ship this workflow:

Lead scoring

Frequently asked questions.

How do I score leads with biz collect?

Collect leads with a search, pick scoring signals from the returned fields (ratings, reviews, presence of email and phone, website), normalize them, combine into one score per lead, and rank the list so the best leads are worked first.

Which fields are useful for scoring?

Ratings and review count for quality, deduped emails and phone for reachability, website and social profiles for web presence, and open/closed status and hours for operational signals. Every record shares these fields.

Why does a stable schema help scoring?

Because the same fields come back for every business, you write the scoring logic once and apply it to the whole list - no per-source special cases or field-name guessing that would skew the score.

Does biz collect score leads for me?

No. biz collect provides consistent, structured signals; you choose the weights and compute the score in your own pipeline. That keeps the scoring logic specific to what predicts a good fit for your offer.

Can I start scoring on the free tier?

Yes. The free tier's 200 signup credits plus 20 daily login credits, with no card and free polling, are enough to pull a real list and test a scoring model before scaling up.

Still have questions? Talk to us.