Definition
Lead scoring assigns points to each lead based on how well they fit your target customer and how they have behaved, so sales teams can focus on the leads most likely to buy.
Detailed Explanation
Scores usually combine two kinds of signals:
- Fit: does the lead match your ideal customer profile? Examples: industry, company size, location, budget, job title.
- Behaviour: how engaged are they? Examples: requested a quote, visited the pricing page, opened emails, attended a webinar.
Leads above a threshold may become marketing qualified leads (MQLs) and then sales qualified leads (SQLs) once sales confirms interest. Scoring can be done in a CRM automatically, or in a simple spreadsheet for small teams.
Good scoring is reviewed regularly against real outcomes: do high-scoring leads actually buy more often?
Nepal Context
Many Nepali businesses receive enquiries through Facebook, WhatsApp, phone, and forms, with no consistent way to prioritise them. Even a simple scoring rule, such as “has a budget, has a date, is in our service area”, helps teams respond to the best leads first. Insurance, education consultancies, real estate, and B2B services benefit most.
Practical Examples
- An education consultancy gives extra points to leads who have taken an English test and chosen a country.
- A solar installer prioritises leads who have shared their monthly bill and roof size.
- A B2B software firm scores leads by company size and whether they booked a demo.
Key Takeaways
- Combine fit and behaviour signals.
- Start simple and refine with real sales outcomes.
- Use scores to set response priority, not to ignore leads entirely.
Common Mistakes
- Overcomplicated models nobody trusts.
- Never checking scores against actual sales.
- Scoring on vanity actions like page likes.
Related reading: insurance marketing in Nepal and CRM marketing.
