Why Location Intelligence is the Key to EV Charging Network

Picture two charging stations opened in the same month, with the same hardware, the same price per kWh, and the same investment. They sit three kilometers apart. One is busy from morning to night. The other waits for drivers who never arrive. (This is an illustrative scenario, but any operator will recognize it.)  Nothing about the chargers explains the difference. The location does.  Choosing where to build is the most expensive decision in an EV charging business, and the hardest to reverse. Hardware can be upgraded or swapped. A site that has been leased, wired, and permitted rarely can be. Location intelligence replaces that bet with evidence, and it is quickly becoming the foundation of any serious charging network plan. 

Three questions every charging site must answer 

Before a single charger is ordered, a site needs convincing answers to three questions: 

1. Is there demand? Do enough people come here, and do they stay long enough to charge?
2. Is there a gap? Is the area still underserved, or are chargers already waiting for the same drivers?
3. Is it practical? Can drivers reach the site easily, and does the surrounding land make sense for a charging stop?

A location can score well on one and fail the other two. A busy shopping district with five stations nearby has demand but no gap. A quiet road with no chargers has a gap but no demand. The best sites pass all three at once, and finding them across a whole city is not something intuition can do. 

The data layers behind a good answer 

Location intelligence combines geospatial and mobility data so that each layer answers part of those three questions.

Data layer	What it shows	Why it matters for charging
Existing SPKLU distribution	Where charging supply already exists	Reveals crowded zones and blank spots
Points of Interest (POI)	Malls, offices, hospitals, hotels, landmarks	Destinations give drivers a reason to stop
Visitor density and mobility activity	How many people actually come through an area	Separates genuinely busy places from merely well-known ones
Dwell time	How long visitors stay	A charging session takes time, so longer stays fit better
Road accessibility and land use	How easy the site is to reach and what the land is used for	A strong area still fails if drivers struggle to get in

No single layer decides anything. The value comes from reading them together, around each candidate location. 

From layers to a ranking: the gap score 

A stack of maps is not yet a decision. Bvarta turns the layers into a proprietary Gap Score, which combines visitor activity, dwell time, and the number of SPKLU stations already operating nearby. The higher the score, the bigger the opportunity.  The result is a ranked list instead of a guess: the places where many people spend real time and few chargers exist float to the top. 

What this looks like in West Jakarta 

Bvarta applied this approach to West Jakarta in the West Jakarta EV Charging Location Intelligence Report, using data from June 13th to 16th, 2026. The analysis benchmarks 734 existing EV charging station locations, then evaluates candidate areas within a 523-meter catchment (drawn as a radius of roughly 523 meters on the map). It maps 96 existing SPKLU stations in West Jakarta and surfaces 11 high-opportunity clusters. Two of those areas show how different an opportunity can look: 

• Krukut, Priority #1. A Gap Score of 0.72 and more than 1.2 million visitors make it the top-ranked area in the analysis.

• Jelambar. 2,881 POIs, over 261,000 unique visitors, a 75-minute average dwell time, and no SPKLU inside its catchment. Its Gap Score is 0.51, with Medium-High demand. 

The pattern across the report is consistent. The strongest candidates combine a dense mix of destinations, heavy visitor activity with long stays, and good accessibility, while current infrastructure has not caught up. For the national picture of where SPKLU stations are concentrated today, see our analysis of Indonesia’s EV charging distribution map. 

What changes when decisions are data-led 

• Better starting points. Teams agree on where to build first, with a ranked list to point to.

• Fewer wasted sites. Areas that are already saturated, or that lack real foot traffic, are filtered out early.

• Stronger conversations with landlords and partners. Visitor and dwell data give both sides the same facts to negotiate with.

• Sensible sequencing. A rollout can start with the highest-scoring clusters and expand outward as results come in.

See it for yourself: download the free report 

The quickest way to judge location intelligence is to see it applied to a real city. The West Jakarta report is free, and shows which areas have the potential to host a new EV charging station, with a map preview, catchment areas, and ranked opportunity zones.  Download the free EV Report here: https://bvarta.com/evreport/ 

Ready to explore more? Unlock the complete dataset 

The free report is a teaser sample. The complete Bvarta dataset adds: 

• Wider coverage: Greater Jakarta (Jabodetabek) and major Indonesian metropolitan areas.

• EV traffic volume and corridor tracking: real-time and historical EV mobility patterns.

• Station specifications: AC/DC connectors and power output (kW) of existing stations.

• Sales projection: revenue projection for each area.

• POI and location breakdown: retail, commercial, residential, and hospitality drivers. 

• Location type classification: Commercial Hub, Transit Station, Residential Cluster, and Highway Rest Stop. 

If you are weighing a site, a rollout, or a partnership, we are glad to talk it through.  Chat with us on WhatsApp: +62 877 7907 7750 Or write to [email protected] | bvarta.com 

The takeaway 

In EV charging, the charger is the easy part. The hard part is knowing where people will be, how long they will stay, and where no one is serving them yet. Location intelligence answers that before the first dollar is spent, which is why it sits at the center of a well-planned charging network.  Data period: June 13th–16th, 2026 | Focus area: West Jakarta | Source: Bvarta Location Intelligence