JevMade field notes / Worked recipe

Show why a sales enquiry receives its priority

This recipe rates fit, buying influence, need, timing, and budget separately, then combines them with weights the sales team can inspect.

Original by Jeroen Erne / NexibeoClassification

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Credits and license

“13 · Lead scoring” by Jeroen Erne / Nexibeo. Read the original source.

This expanded guide is an AI-narrated adaptation of the source’s essential explanation, examples and caveats, not a word-for-word reading. The synthetic voice does not imitate the author or imply their endorsement.

License: MIT

MIT License

Copyright (c) 2026 Jeroen Erne (https://nexibeo.com, https://completeaitraining.com)

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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Our summary

A sales team may want to contact some enquiries before others, but one unexplained score is hard to challenge. This recipe breaks the judgment into several questions about the company, the contact's influence, their needs, timing, and available budget.

Jev rates each part against a description of the intended customer. The program puts the ratings onto comparable scales and combines them using chosen weights. It also applies a firm rule: someone outside the customer profile cannot receive the highest priorities simply by sounding urgent.

The example uses a fictional business and a small labelled sample, with several debatable outcomes. Its priorities are not universal sales rules. Teams need to check the separate ratings, adjust their own weights, and verify whether the resulting order actually helps their work.

Key takeaways

Keep the parts of a priority score visible.
Apply firm eligibility rules outside the AI question.
Review disagreements with the people who use the ranking.

More guides →See the experiments →