How to Compare Customer Coverage Across Multiple Branches

When managing multiple branches, one persistent challenge is the lack of clarity around how customer coverage compares from one location to another. As a result, teams often struggle to make informed decisions. Without a structured way to compare customer coverage across multiple branches, they may rely on assumptions rather than spatial evidence. MAPOG helps solve this by enabling centralized mapping workflows that visualize branch reach, highlight coverage gaps, and bring spatial clarity to data that would otherwise remain fragmented.

Key Concept: Why to Compare Customer Coverage

Although branch-level data may seem complete, without spatial comparison, key coverage gaps often remain hidden. By contrast, when you compare customer coverage across multiple branches, patterns like blind spots, overlaps, and uneven reach begin to emerge. As a result, teams can prioritize outreach, balance workloads, and coordinate more effectively.

Step-by-step guide to compare customer coverage 


1. Open Your Map


Start by logging into MAPOG and opening the pre-existing Branch Location Map. Then, go to the process custom location section and select Add by Uploading CSV/Excel to begin uploading your customer data.

Interface showing branch Location Map and CSV/Excel upload option.

2️. Create a Customer Location Type


Next, click the Select custom location template Settings icon to define your customer data attributes.

Showing Custom location template settings

Choose Add More Location Type, name it something like “Customer Coverage”, and define attributes such as Branch Name, Visit Frequency, and Purchase Amount—making sure each is assigned to its correct attribute type. Once done, click Save.

Custom location template showing fields for Branch Name, Visit Frequency, and Purchase Amount.

3️. Upload Your Customer File


Now, select the location type you just created from the drop-down. Browse and upload your customer data (CSV/Excel) file containing coordinates and attribute details.

Interface showing uploading customer data CSV file with selected location type  ready for import.
4️. Match Attributes and Submit


After uploading, choose a unique ID, match each attribute to the corresponding column in your file.

Interface showing Attribute matching  with excel columns aligned to customer data fields

For placement select either Coordinates or WKT. Then, click Submit to plot your customer points on the map.

Interface showing selecting coordinates for placements of customer points

5. Style by Branch

Once your customer points are plotted, go to Map Layers, open the Customer List Layer Panel, and click Add Style Layer.

Interface showing style layer option in the layer panel

In the Category section, select Branch Name as the attribute to categorize points according to that.

Image shows selecting Branch name as attribute on order to visualize points according to branches to Compare customer coverage across branches

After that, color-code customer points by branch and adjust point size for visual clarity and then click save style.

Shows branch-based color coding and point size controls to visually compare customer coverage.

Then, after styling, click on each customer point ID and hit the Pencil icon to open Edit Point Details.

Shows Edit Point Details window to open window for editing points

Here, you can update attributes and add relevant images to enrich each point. Once done, click Save to apply your changes.

Shows attribute fields for updating attributes and adding images to enrich and customer coverage comparison

6. Show Legend

To wrap up, go to the Customer Layer Panel and select Show Legend. This adds a visible key to your map, showing which colors correspond to which branches, making it easier to interpret customer distribution at a glance.

Customer Layer Panel with legend enabled, showing branch color codes to help compare customer coverage at a glance.

Your customer coverage map is now ready, visually showing which branches are clustered with customers and which need more attention.

Visualizing clustered customer data points to compare customer coverage across multiple branches.

Industrial use and benefits

Across sectors, comparing customer coverage across branches unlocks new clarity. For instance, in retail, it highlights which outlets are overserved and which lack footfall. Meanwhile, field service teams can identify overloaded hubs and rebalance technician zones. Similarly, NGOs can compare outreach density across field offices and redirect resources to under-served areas. Even banks and telecoms benefit by visualizing customer spread across branches, making it easier to optimize staffing, marketing, and expansion strategies.

Conclusion 

Ultimately, comparing customer coverage across branches helps teams shift from scattered data to clear, map-based insight. Teams visualize customer clusters, spot under performing branches, and assess resource distribution to make grounded, effective decisions. Through centralized workflows and intuitive styling, MAPOG makes this process efficient, turning raw location data into clear, actionable insight.

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