Lead scoring · and the half of it everybody skips
The score only goes up.
That is the whole problem.
Account Engagement qualifies on two axes: scoring counts what a prospect did, grading describes whether their company fits. Most setups use the first, never subtract from it, and never check it against a closed deal. Eight failures below, each with the check you can run this afternoon and the fix at the model level.
Written from setups I have worked on rather than from a survey. The only figures here are Salesforce's own baseline values, read from its documentation on 28 September 2026, and the rules your account runs today are under Marketing Setup, Automation.
Before the eight
Scoring is a model, not a setting.
A setting is right when it is saved. A model is right only while it still predicts something, and what it predicts here is whether sales will accept the lead and whether the deal will close. That is why every failure below is checked against closed deals rather than against best practice: the deals are the only evidence both teams already agree on.
Every check needs administrator access in Account Engagement and read access to opportunities in Salesforce. None of them changes anything.
Failure 01
The rules were set at implementation and never touched again
Scoring is treated as configuration rather than as a model. The rules were written in the week the account was built, against the product, the pricing and the buying process of that year. Everything around them moved; the numbers did not.
The check you can run this afternoon
Open the scoring rules and find the last edit date. Then pull the deals closed in the last two quarters and read the score each one carried when sales accepted it. If those scores scatter across the range with no pattern, the model is no longer describing your buyers.
The fix, at the model level
Put recalibration on a schedule rather than on somebody noticing. Once a quarter, compare the score distribution of accepted leads against the score distribution of won deals, and move the weights that no longer separate them. It is an hour a quarter, and it is what keeps the model from becoming decorative.
Failure 02
Nothing ever subtracts, so old interest keeps counting
Scores in Account Engagement only go up unless somebody builds them a way down. A prospect who attended a webinar eighteen months ago still carries those points today, and the model cannot tell an active buyer from an old one.
The check you can run this afternoon
Filter prospects above your qualified threshold, then sort by last activity date. On a healthy model most of them did something in the last sixty to ninety days. If a large share have been silent for a year, sales is being handed history rather than leads.
The fix, at the model level
Build decay as an automation rule against inactivity: a dynamic list of prospects with no activity for ninety days, and a rule that subtracts a fixed number of points while they stay in it. Match the interval to your sales cycle, short cycles decay faster, and reduce the score rather than zeroing it, because somebody who engaged heavily and paused is not the same as somebody new.
Failure 03
Disengagement signals score nothing
Unsubscribes, hard bounces and spam complaints leave the score untouched, so a prospect who has told you to stop writing can still qualify. The model has one direction and no way to express the word no.
The check you can run this afternoon
Export prospects who are opted out and above the threshold. The healthy answer is near zero. Then do the same for prospects with repeated hard bounces: a mailbox that does not exist should not be marketing qualified.
The fix, at the model level
Give the model negative rules with the same care as the positive ones. Unsubscribe is the largest deduction, hard bounces and complaints follow, and a careers page visit deserves a small one because it usually means a job seeker rather than a buyer. The point is not punishment, it is that the score should be able to fall.
Failure 04
Buying intent and reading weigh the same
A pricing page visit scores like a blog read, and a demo request scores like a newsletter click. The rules were built on the baseline values the account ships with, which treat activity as activity, and nobody layered intent on top.
The check you can run this afternoon
Take the fifty highest scoring prospects and list which actions built each score. If most of the points came from blog reads and email opens, with no pricing page, no demo and no comparison content anywhere, the model is ranking readers rather than buyers.
The fix, at the model level
Classify every tracked page and asset by where it sits in the decision: awareness, consideration or decision. Score by that class rather than by the type of action, so a decision page outweighs an awareness one by a wide margin. Read your own baseline rules first, in Marketing Setup under Automation, because that is what your points are being added to.
Failure 05
Score is used alone, without grade
Account Engagement qualifies on two axes. Scoring counts behaviour and answers how interested they are. Grading describes fit and answers whether they are the kind of company you sell to. A model that promotes on score alone will promote an enthusiastic reader from a company you cannot serve.
The check you can run this afternoon
Read the rule that sets qualified status. If it names a score and no grade, this is your pattern. Then pull the last twenty leads sales rejected and read their grades: a run of low grades means the filter was missing, not that sales is fussy.
The fix, at the model level
Require both in the trigger, a score above the threshold and a grade at or above the level sales agreed. Build the grading criteria with sales, because fit is their judgement, and validate them against closed deals, because that is the only evidence either side accepts.
Failure 06
Grading still describes the customer you wanted two years ago
Industries you no longer sell to grade well. Verticals you moved into do not. Titles that became important recently are not in the rules at all, so the model quietly downgrades the people you are now trying to reach.
The check you can run this afternoon
Pull the last twelve months of won deals and read the grade each had at qualification. If won deals were coming through at the bottom of the scale, grading is fighting your own strategy. Check it from the other end too: do the current grade A prospects look like the accounts you want this year?
The fix, at the model level
Rebuild the grading criteria from the closed deals rather than from the original document. Industries, size bands, titles, geography, and then test the new rules against last year: would they have graded your won deals correctly? Run the new and the old in parallel for a month before the old ones come out.
Failure 07
Existing customers qualify as new leads
Customers keep reading, and their scores keep climbing, so the model announces them to sales as fresh opportunities. Customer success then hears from a rep about an account they already own.
The check you can run this afternoon
Cross reference everybody currently qualified against accounts marked as customers in Salesforce. The healthy answer is no overlap at all. Anything else means part of your qualified queue is people you already invoice.
The fix, at the model level
Exclude customers from the qualifying rule explicitly rather than hoping nobody notices, and route their engagement to customer success instead. Expansion interest is worth tracking; it is simply not the same signal as a new buyer, and one queue cannot carry both.
Failure 08
Marketing and sales mean different things by qualified
The threshold was chosen by one side. Marketing reads it as interest shown, sales reads it as ready to be called today, and neither wrote that down. The number is agreed and the meaning is not, which is why the argument comes back every quarter.
The check you can run this afternoon
Ask both sides the same question separately: what does the handover promise. Different answers are the finding. A faster version: ask what share of qualified leads sales contacts within a day. If the answer is most of them, the definition is alive. If it is a shrug, it is not.
The fix, at the model level
Give the model a named owner on the sales side who attends the quarterly review, agree what happens after the handover, and let sales return leads with a reason rather than ignoring them. Rejection reasons are the input for the next recalibration, so the loop closes instead of restarting.
What you are adding to
The baseline Salesforce ships, and what it rewards.
Read from the Default Scoring System page in Salesforce help on 28 September 2026. These are the values in a new account before anybody edits them, and they explain failure number four better than any argument: a form is worth fifty, a page view is worth one, and an email open is worth nothing at all.
| Form SubmissionA form on an Account Engagement page. | +50 |
| Form Handler SubmissionThe same value for a handler on your own page. | +50 |
| Landing Page SuccessA submission on an Account Engagement landing page. | +50 |
| Opportunity CreatedWhen the prospect is attached to the opportunity. | +50 |
| Video ConversionA turnstile conversion, with the video connector. | +50 |
| Video Watched 75%+Each time three quarters of a video is watched. | +25 |
| Olark ChatRequires that connector. | +10 |
| Custom Redirect ClickEach click. | +3 |
| File AccessEach time a file is opened. | +3 |
| Site Search QueryRequires site search tracking. | +3 |
| Third Party ClickA click in an integrated third party email client. | +3 |
| Tracker Link ClickEach tracked link. | +3 |
| VisitorEach time the prospect is cookied. | +3 |
| Page ViewEvery page with your tracking code, in a visitor session. | +1 |
| Email OpenZero by default. | 0 |
| Webinar AttendedZero, as are invited and registered. | 0 |
| Event Checked InZero, as is event registered. | 0 |
| Video PlayStarting a video is worth nothing. | 0 |
| Social Message Link ClickZero. | 0 |
| Opportunity WonWinning the deal adds nothing to the score. | 0 |
| Form ErrorOnce per failed attempt, the same for handler and landing page errors. | -5 |
| Opportunity LostThe only large deduction Salesforce ships with. | -100 |
Three things worth noticing before you copy anybody's model. Filling a form is worth fifty times a page view, so a model left on the baseline ranks people who download things. Opening an email and attending a webinar are worth zero, so the two activities marketing reports on hardest do not move the score. And winning the deal adds nothing, while losing one takes a hundred away, which is the only large deduction in the set.
After the list
Rebuild or tune, and the test is not how many failed.
Tune when one of the eight is active and the structure underneath it is sound: a weight to move, a negative rule to add, a threshold to lift. Rebuild when three or more are active, because they compound. Decay that does not exist makes the threshold meaningless, a missing grade makes the threshold arbitrary, and customers in the queue make the whole number untrustworthy. Patching one rule at a time inside that structure moves nothing.
The honest test: would another rule improve the answer, or would it add complexity to a model that is already wrong? If it is the second, the model is the work, not the rules.
What a rebuild costs here is published rather than quoted. A scoring and grading rebuild, back tested against your own closed deals, is €2,250 for 45 hours, about two weeks elapsed. The read only data check on the Salesforce side is €500. The checks on this page cost nothing and you do not need me to run them.
What good looks like
Eight sentences, and none of them is sophisticated.
Qualification needs a score and a grade
Interest and fit are different questions, and the handover requires an answer to both.
The score can fall
Inactivity decays it and disinterest subtracts from it, so the number describes now rather than ever.
Decision content outweighs reading
Pages are classified by where they sit in the decision, and the points follow that rather than the action type.
Grading describes this year's customer
The criteria come from the deals you closed, not from the document written at implementation.
Customers are excluded by name
Their engagement routes to customer success, because expansion and acquisition are not the same signal.
The threshold came from closed deals
It is a finding rather than a round number, and it moves when the evidence moves.
Sales owns half of it
A named person on that side attends the review and returns rejected leads with a reason.
Recalibration is scheduled
Quarterly for weights, annually for grading, and immediately after a change to what you sell.
Next to this one
Where the rest of the model is written out.
The twenty seven check audit
Scoring is four of them. The other twenty three are configuration, sync, deliverability, database health and reporting. Run the full checklist.
When the leads never arrive at all
A scoring model cannot qualify a prospect that never reached Salesforce. Read the twelve sync errors.
Account level scoring
The same failures, one level up, where contact engagement rolls into an account score. Read the six ABM patterns.
The symptom, priced
Sales ignoring marketing leads is one of six faults with a published repair price. See what the repair covers.
Asked often enough to answer here
Questions
What is the difference between scoring and grading in Pardot?
Scoring is behaviour and grading is fit. The score goes up when a prospect does something, so it answers how interested they are. The grade is a letter describing how well the company matches the kind of customer you sell to, so it answers whether the interest is worth acting on. A model that uses one without the other qualifies either enthusiastic strangers or a good fit who has never shown up.
Does Pardot score decay on its own?
No. The score rises with activity and stays there unless you build a way down. Decay is an automation rule you create yourself: a list of prospects with no activity for a set number of days, and a rule that subtracts points while they stay on it. Without it, the queue slowly fills with people who were interested last year.
What should the qualified threshold be?
Whatever the deals you already won were carrying when sales accepted them. Pull the last six to twelve months of closed won opportunities, read the score and grade each had at handover, and set the threshold there. A round number chosen at implementation is a guess, and it is usually the reason the two teams disagree about lead quality.
Should existing customers be able to become qualified leads?
No, not through the same rule. A customer reading product content is a signal worth having, but it belongs to customer success, not to the new business queue. Exclude accounts marked as customers from the qualifying rule and route their engagement separately, otherwise a share of what marketing reports as qualified leads is people who already pay you.
How often should a scoring model be recalibrated?
Once a quarter for the weights, once a year for the grading criteria, and immediately after any change to what you sell or who you sell it to. The quarterly pass is an hour: compare the scores of accepted leads against the scores of won deals and move whatever no longer separates them.
Serhii Skrypnyk · Senior Salesforce Administrator and developer · 7 Salesforce certifications · on the platform since 2018. Reviewed 28 September 2026.