Lead Scoring

When two or three inquiries arrived a day, nobody needed an order of play. You called all of them. That changed once putting a form in front of every download became standard practice. Leads — people who have handed over contact details — piled up by the hundreds every month while the number of people free to call them stayed at two.

Meetings then stalled in the same place every time. Marketing would report 800 leads passed over for the month and sales would ask how many of those were worth meeting. Marketing counted handoffs; sales counted the share of them that turned into a real conversation. The same 800 was a result to one side and a pile to sift through on the other.

Lead scoring exists to put those 800 in order. It is not a machine for predicting who will buy. It is a way of letting an agreed points table, rather than instinct, decide who gets called first.

Assign points to the facts attached to a lead and to the things that lead has done, then compare the total against a threshold set in advance.

Points come from two kinds of material. The first is who the person is: company size, industry, job title, whether the address is a company domain rather than a personal one. The second is what the person did: opened the pricing page, downloaded a case study, signed up for a free trial.

Keeping the two apart matters because neither settles the question alone. A perfect-fit company that has done nothing is not buying right now, and a three-person company checking the pricing page daily will not stay long even if it does buy.

The calculation has three steps.

1. Pick the items worth scoring. Not by instinct — look back at customers who already signed and find what they had in common beforehand.
2. Set the points per item. Pagedeck uses 20 for a company domain address, 15 for a company with more than 50 people, 10 for a pricing page visit, and 25 for a free trial signup.
3. Set the threshold for handing a lead to sales. Above 60 the lead is promoted to a marketing qualified lead (MQL) and passed on; below that it stays on the list. An MQL is what marketing calls a lead it judges worth a sales conversation.

Deductions and decay belong in the same table. A school or personal address loses 10 points, and something done three months ago is worth less than the same action today. Without decay, a lead whose interest has faded crosses the threshold purely because time has passed. Leads under the line are not deleted but handed to lead nurturing, and once there are more than ten rules the table moves into a marketing automation tool that scores each lead on its own.

The absolute score means nothing. Each team invents its own point values, so another company's 80 and your 80 describe different situations. A report that the average score rose this month is the same kind of number — loosening the values produces it without anything changing.

What tells you whether the rules work is whether outcomes separate by band. Split the conversion rate, the share of handed-over leads that reach an actual sales conversation, by score band. If 30 percent convert above 80 points and 8 percent convert in the 40s, the score is doing its job. If it is 22 percent above 80 and 19 percent in the 40s, points have been assigned but nothing has been sorted. What needs fixing then is which items get counted, not how many points each one carries.

Where to put the threshold is a question about sales capacity. Drop it to 60 and more leads cross than two reps can work through in a day; raise it to 80 and only five arrive a week, leaving them idle. Count how many conversations the team can hold in a week and move the line to match.

The rules do not hold still. Every quarter, trace the customers who signed back to what they did beforehand. Until a few dozen contracts have accumulated there is nothing to trace, so early on it works better to write down what sales picks up on calls.

"Twelve leads over 80 points went over this week. Please get to them today."

Sorted by score, only the top twelve came off the list.

"It scores 90 but it's a three-person company. The behavior points look too generous."

The behavior values are high enough that poor-fit leads clear the threshold.

"I recut the point values from last quarter's closed deals. They apply from this month."

The rules were rebuilt from real contract records, so the kind of lead coming through changes.

At Pagedeck, Ravi writes the rules and Sofia receives what they produce. Monday morning brings her the list of leads that crossed the line over the weekend, and she works down it from the top. More than twenty and she asks Ravi to raise the threshold; fewer than five and she asks why it is so thin.

The quarterly review runs the other direction. Every customer that signed goes on a line along with the score they carried beforehand. If three of them never cleared 60 and closed because Sofia happened to call, whatever those three had in common goes into next quarter's point values.

The most common mistake is reading a high score as a person who will buy. Points look like a probability, so the assumption comes easily. What the number measures is the size of the interest and the fit of the company, not whether that person holds a budget or the authority to decide. Someone who has opened the pricing page five times is often a practitioner who cannot sign anything. Call them with a contract in hand and they get questions they are not ready for; enough of those calls and sales stops trusting the list. Whether someone can actually buy gets checked on the call against something like BANT — budget, authority, need, and timing.

Treating the table as finished once it is built is the other one. Assembling it takes enough effort that completing it feels like an ending. But the point values were pulled out of the behavior of past customers, so they age the moment the thing being sold changes. Move from individual users to company accounts without touching the values and the company contact who downloads one document and waits quietly stays below the line.