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Lead Scoring.
Lead scoring assigns points to contacts in order to rank them by their likelihood to buy. The points come from two sources: information about the person and the company (fit) and observed behaviour (interest). Above a defined score, a contact is considered ready for handover; the threshold is an operational decision, not an industry value.
Lead Scoring — Explained in Detail
The purpose is ranking, not weeding out. When more enquiries come in than can be handled carefully, without a model it is the order of arrival or gut feeling that decides who gets a call first. Lead scoring replaces this with a transparent rule. The emphasis on transparent matters: a model whose scoring nobody can explain is ignored by sales, and an ignored model is worse than none at all, because it also creates maintenance work.
A simple model has four components. Fit points for characteristics that match the offer: industry, size, region, the person's function. Behaviour points for actions that indicate buying interest: viewing the pricing page, repeat visits, downloading a quote document, replying to an email. Negative points for signals that point the other way: unsubscribing from the newsletter, visiting the careers page, a competitor's address, a private free-mail address in B2B. And decay, which reduces points again after a few weeks of inactivity, so that old enthusiasm does not keep counting for ever.
An example: a consultancy receives around sixty enquiries a month and can handle about twenty of them thoroughly. Instead of working through them in order, it awards points for company size, canton, the role of the person enquiring and a visit to the fees page; job applications and enquiries outside its offer receive negative points. The twenty highest scores are contacted first, and the rest receive a quick, standardised reply. After three months it checks whether the orders actually won were at the top of the list. This review is exactly what turns a guess into a model.
Lead scoring is the wrong investment when the feedback loop is missing. If you do not record which contacts eventually became orders, you can never correct the weights; the points then remain a formalised opinion. Nor is it worthwhile at low volumes: with a handful of enquiries a month, a careful manual review is quicker and more accurate than any rulebook. Finally, a model needs maintenance. If the offer or the target group changes, the weights quietly go out of date; a review date belongs in it from the start.
Related Page
Marketing Qualified Lead (MQL)Frequently Asked Questions About Lead Scoring
Not necessarily at the start. A simple model with five to eight criteria can be kept in a spreadsheet as long as the volume remains manageable. A CRM becomes worthwhile as soon as behavioural data should flow in automatically, several people work at the same time or the history needs to remain traceable over months. The more common mistake is not the missing tool but a model whose hits nobody checks afterwards.
The threshold is derived from your own capacity, not from a benchmark. Working backwards is practical: how many contacts can sales handle carefully per week? The threshold is set so that roughly that number exceeds it. It is then adjusted based on results: too many worthless handovers means raising the threshold, too much idle time means lowering it.
The deliberate deduction of points for signals that speak against a deal. Typical examples are visiting the careers page, unsubscribing from the newsletter, an email address belonging to a competitor or a location outside the service area. Without negative points, very active but unsuitable contacts climb to the top: job applicants and students often generate more page views than genuine prospects.
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