--- title: How does scoring setup work in TargomoLOOP? description: Learn how scoring works in TargomoLOOP. Step-by-step guide to selecting datasets, setting min/max ranges, logic, and weights to create accurate location scores and heatmaps --- [Skip to content](https://info.targomo.com/targomoloop/help/how-does-scoring-setup-work-in-targomoloop#main-content) ![Targomo-logo-email-logo-template.png\]](https://info.targomo.com/hs-fs/hubfs/Targomo-logo-email-logo-template.png?height=40&name=Targomo-logo-email-logo-template.png) - [Sample About Page](https://www.targomo.com/en/about/) - [Sample Contact Page](https://www.targomo.com/en/contact/) - [Default HubSpot Blog](https://info.targomo.com/blog) Open main navigation Close main navigation - [Sample About Page](https://www.targomo.com/en/about/) - [Sample Contact Page](https://www.targomo.com/en/contact/) - [Default HubSpot Blog](https://info.targomo.com/blog) How can we help you? - There are no suggestions because the search field is empty. 1. [TargomoLOOP Knowledge Base](https://info.targomo.com/targomoloop/help?hsLang=en) 2. [Location scoring and GeoAI revenue and other predictions](https://info.targomo.com/targomoloop/help/location-scoring-and-geoai-revenue-and-other-predictions?hsLang=en) 3. [Location scoring and GeoAI revenue and other predictions](https://info.targomo.com/targomoloop/help/location-scoring-and-geoai-revenue-and-other-predictions?hsLang=en#location-scoring-and-geoai-revenue-and-other-predictions) # How does scoring setup work in TargomoLOOP? ## Scoring in TargomoLOOP helps you combine multiple data points into a single score (0–100) to evaluate and compare locations. #### What is scoring? Scoring converts different datasets (e.g., population, income, footfall) into a **standardized score** and combines them using weights. - **0 = worst value** - **100 = best value** This allows you to: - Compare locations easily - Visualize results as **heatmaps** - Build **data-driven expansion decisions** --- #### Step-by-step: How to set up scoring ### 1. Select datasets 1. Go to **Settings** 2. Click on **Score** 3. Click on **Add data** 4. Select the **datasets** you want to include (e.g., population, income, demographics) 5. Click Next --- ### 2. Configure scoring parameters After selecting datasets, you need to define how each one contributes to the score. --- ### Key parameters explained #### 1. Min and Max values Defines the scoring range: - **Minimum value → score 0** - **Maximum value → score 100** Any value: - Below min → stays 0 - Above max → stays 100 👉 You can: - Auto-calculate using **“My Network”** - Or manually override for more control --- #### 2. Logic (More is better / Less is better) Defines how the metric should behave: - **More is better** → e.g., population, income, footfall - **Less is better** → e.g., competition, rent, vacancy --- #### 3. Weight Defines **importance of each dataset** in the final score. - Higher weight = more influence - Lower weight = less influence --- --- #### How the final score is calculated - Each dataset is normalized to **0–100** - Then combined using **weights** - Result = **final score per location** --- #### Best practices ### 1. Use realistic Min/Max - Avoid extreme values → leads to flat scores - Use your **network data** for better calibration --- ### 2. Keep datasets meaningful - Don’t add too many variables - Focus on **what actually drives your business** --- ### 3. 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