Article 2 of 2. Companion piece: Why chargers underperform

Profitability is the slide every charging board deck now ends on. Ask most operators how they get there, and the answer involves growth: more sites, more hardware, economy of scale.

The market has started moving the other way. Zapmap noted in mid-2026 that operators are shifting focus toward utilisation rather than deployment, and that poorly performing chargers are being pulled out of public use. Their utilisation work with the Green Finance Institute found usage rates holding within a narrow band through 2025 while the network grew 13%. Adding chargers is no longer the same thing as adding revenue.

So the return has to come from the estate you already own. Sites pulling half of what they should. Chargers that look fine on a map and lose money every week.

In our business, we speak with heads of operations and network performance of charge point operators across Europe. We often ask one question: when a site underperforms, what do you do about it?

Twenty-three distinct remedies came out again and again. We decided to organise these into five categories and present them systematically.

Before anything: name the cause

Every operator we speak to does the same thing before lifting a finger. They work out which kind of problem they have, because the fix depends entirely on the cause.

Our companion guide, Why chargers underperform, works through the symptoms that separate these. The rest of this piece assumes you already know which bucket you are in.

The lever menu

Shares below show roughly how many of the operators we spoke with raised each remedy. We have rounded them, and we name no operator, because several of these remedies came from a small number of teams who would be identifiable otherwise.

Pricing

The most-discussed category, at around a quarter of everything raised.

Price is the first reflex almost everywhere. The more interesting position, raised nearly as often, is knowing when to sit on your hands. Several operators described watching a rival run a time-boxed deal nearby, holding their own tariff, and waiting for volume to come back. Cutting in response starts a race nobody wins.

Some teams also cap how far they will discount, because a tariff change carries operational cost of its own once you count reboots and comms. Before you move, benchmark: Zapmap put the July 2026 weighted average pay-as-you-go price at 54p/kWh up to 49kW and 80p/kWh at 50kW and above. If you sit below market and still lose volume, price is not your problem.

Marketing & demand

Around a quarter of everything raised, and the category operators reach for fastest once the hardware checks out.

One rule governs this whole category: never market a site you have not verified. J.D. Power's 2025 US study found 14% of EV owners visited a charger and left without charging. Spending to send new drivers into that experience buys you churn at full price.

The win-back move deserves more attention than its share suggests. Operators describe EV drivers as fickle, so a plain apology after a failed session, plus a nudge to lapsed users once the site works again, recovers sessions for close to nothing. Very few teams run it as a process.

Resident-engagement work on foot comes up from operators running kerbside estates, where the driver has no driveway and no alternative. With on-street charger numbers growing 18% year on year through H1 2026 according to Zapmap, more operators will need this muscle than currently have it.

Physical site & visibility

The smallest category by share, at roughly one mention in eight, and the one with the cheapest wins in it.

Site visits find real problems. Teams that drive their estates turn up payment screens bleached by sunlight, losing customers with nobody any the wiser. But a person walking a large estate is the most expensive diagnostic tool you own. Keep it rare, send it with a hypothesis, and log what each visit cost against what it found. Some operators are piloting crowdsourced field checks as a cheaper way to get eyes across an estate.

Technical / uptime & faults

Roughly one mention in five, and the category where the cheapest remedies live.

This category has changed status. It used to be a margin question. Since the Public Charge Point Regulations came into force, a rapid network has to hit 99% reliability as an annual average, reported to the Secretary of State. One secondary source cites a 2025 Monta survey of over 200 UK operator decision-makers finding fewer than 4% already meeting it. Worth verifying at source, but the direction is clear enough: technical remedies now defend a compliance number as well as a margin number.

Strong teams resolve most of this without leaving the office. A remote reset the moment a status fault appears. A restart scheduled around a known quirk for that hardware type. An engineer only once the fault is confirmed physical. And when the cause belongs to someone else, they route the ticket to the DNO or the manufacturer instead of burning their own hours on it.

Firmware selection is the most underused item on this list. A few teams use a third-party service that tells them which firmware version performs best for a given charger type, then deploy accordingly. Most operators run whatever shipped.

Portfolio / strategic

Roughly one mention in five, and the category that decides whether any of the others compound.

The most valuable item here is the one operators mention most and formalise least. What you learn fixing one site should decide where you build the next. A rival's strong site nearby is either a signal to follow or a reason to stay away, and the answer sits in your own recovery data.

Operators running large mixed estates put the harder version plainly: at some point you stop spending on locations that will never pay back, and you move that capex to the ones that will.

Run it as a loop, not a rescue

Every strong operator describes some version of the same cycle.

1. A site slips. An alert flags it.

2. You diagnose the cause.

3. You pick the remedy that will most likely fix the cause.

4. You do it.

5. You go back and check whether utilisation recovered.

6. You analyse, learn, and capture the lesson for next time.

Step five is the one a lot of CPOs skip. Skip it and you never learn which lever works on which kind of site, so next quarter you guess again. Teams that formalise it name the stages: alert, diagnose, plan, in progress, verify. The last stage is where the compounding happens.

A cadence that holds this together, from the operators who run it best:

• Weekly: rank sites by the gap against what they should do. Work the top of the list.

• Monthly: review the fixes currently running. Did the number move?

• Quarterly: count which causes dominated your estate, and update your playbook accordingly.

Where the manual version stops working

Scale breaks this. Plenty of European operators now run estates well past a thousand chargers.

You cannot rank a thousand sites by hand every week. You cannot hold the likely cause of each weak one in your head. And you certainly cannot recall, six weeks later, whether the tariff change at site 412 moved the number or whether the season did.

So the loop degrades into a rescue. Whoever shouts loudest gets attention, the same three sites get fixed twice, and the verify step disappears. Operators with large estates describe some version of this without being asked.

What we built

Dodona Network Optimisation exists for this job.

It ranks every site in your estate by the gap between what it pulls and what it should pull, so you open Monday with a list instead of a hunch. For each weak site, it names the likely cause, whether that is demand, price, a fault or placement, so you know which bucket you are in before you spend. Where it can, it triggers the remedy itself, such as a remote reset off a known fault, then writes the outcome back so you can see whether the action moved the number.

Diagnose, act, verify. Across a thousand chargers, without anyone babysitting the list.

We are opening a beta to a small group of operators, and several networks are already in. Bring your five worst sites, or your own data if you are up for it, and we will rank them live in about ten minutes. Reply to this, and we will find a slot.

Sources

• Zapmap and Green Finance Institute, UK charge point utilisation report, 2026

• Zapmap Price Index, July 2026, and UK charging infrastructure statistics, H1 2026

• J.D. Power, US Electric Vehicle Experience Public Charging Study, 2025

• The Public Charge Point Regulations 2023, regulation 7

• Monta UK charge point operator survey, 2025

Companion piece: 23 ways CPOs fix underperforming sites: the remedy playbook

A charger can report 99% uptime and still turn away one driver in three.

That gap is the most useful thing to understand about charging operations right now. ChargerHelp's 2025 analysis of more than 100,000 sessions across 2,400 chargers found reported uptime running between 98.7% and 99.9%, while only 71% of charging attempts succeeded on the first try. Even more uncomfortable: 35% of those failures occurred on chargers that appeared operational. The data is American, and UK numbers will differ, but the mechanism travels. Your dashboard is green. Your driver is gone.

The same gap exists one level up. A site can look acceptable relative to your network average and still pull in half of what it should for its location.

Both gaps cost the same thing: margin. Profitability sits on every board slide in this industry now, and the cheapest route to it runs through chargers you already paid for. Getting there starts with knowing what is wrong with them, because the wrong diagnosis spends real money and moves nothing.

In our business, we speak with heads of operations and network performance of charge point operators across Europe, and with advisors who have worked on thousands of chargers. This guide sets out what those teams look at when a site slips, the five families of cause, the symptoms that separate them, and what each wrong diagnosis costs. The companion piece covers the 23 remedies that follow.

1. Define underperformance properly

A site underperforms when it pulls less than it should for its location. The average is what hides your problem. A mean built from 400 healthy sites and 40 dying ones reads as acceptable right up until the year-end margin lands. Zapmap and the Green Finance Institute found time- and energy-based utilisation rates moving within a narrow band across every power category through 2025, even as the network grew by 13% and delivered energy grew by an estimated 21%. Aggregate stability tells you nothing about the spread underneath it.

Operators who run this well score each site against an expectation built from its own context: local EV density, traffic, dwell time, competing chargers within the catchment. Then they rank by the gap. Some teams keep a worst-against-achievable list so the operations meeting opens with names rather than a dashboard.

That gap is your starting point. The rest of this guide explains what fills it.

2. The five families of cause

Demand

The hardware works. The bay is clear. There are not enough EVs within reach, or the drivers who are there have never noticed the site.

Symptom signature. Healthy success rate, low session count, flat trend with no step change. New sites show a slow ramp rather than a drop.

How to confirm. EV registration density in the surrounding postcodes against the assumption in your site case. First-time-user share at the site: if it sits near zero while repeat use holds, awareness is your problem rather than driver behaviour.

What operators tell us. Kerbside teams keep returning to housing stock. A street where most residents have no driveway behaves nothing like a street where most do, and the second one will underperform for years whatever you spend on marketing.

Cost of calling it wrong. You cut the tariff at a site with no drivers in range. You lose margin on the few sessions you had and change nothing else.

Physical site & visibility

The most common cause that never appears in a fault log is that nothing has failed.

Symptom signature. Sessions well below comparable sites nearby with similar traffic. Long unexplained availability gaps, which usually mean a blocked bay rather than a fault.

How to confirm. Photographs beat data here. Teams that drive their estates turn up payment screens bleached by sunlight that have been losing customers for months. Nobody reports it because a driver who cannot read a screen does not file a ticket, nor do they return.

Cost of calling it wrong. You run a hyperlocal campaign that successfully drives people to a bay a diesel van has occupied since Tuesday.

Technical / uptime & faults

Symptom signature. Success rate below your network norm. Sessions started well above sessions completed. Faults recurring on the same units.

How to confirm. Cut success rate by charger type, by firmware version and by site age. The comparison usually names the cause on its own. A pattern that follows hardware points at firmware or the vendor. A pattern that follows geography points at grid or comms.

Age matters more than most operators budget for. The ChargerHelp analysis found first-time success falling from 85% at new stations to below 70% by year three. Your 2023 cohort is quietly becoming your problem cohort.

Cost of calling it wrong. This is the expensive one. You market a broken site, and every new driver you attract has a failed first experience. J.D. Power's 2025 US study found 14% of EV owners visited a charger and left without charging. You paid to create those visits.

Price & competitor activity

Symptom signature. A step change, not a curve. Utilisation drops on a date. Sessions shift to a competitor while your success rate stays perfect.

How to confirm. Find the date the drop started, then find what changed in the catchment on that date. Benchmark your own tariff while you are looking: Zapmap put the weighted average pay-as-you-go price in July 2026 at 54p/kWh up to 49kW and 80p/kWh at 50kW and above. If a competitor launched a time-boxed promotion, your problem has an end date and may need no response at all. Several operators describe watching a rival run a time-boxed deal, holding their own tariff, and waiting for volume to return.

Cost of calling it wrong. Two ways to lose. You match a promotion that would have ended anyway and start a race down. Or you sit still through a permanent repricing and lose a year waiting for a recovery that never arrives. The difference between those two mistakes is knowing whether the competitor's move has an end date, so establish that before you touch your own tariff.

Location: wrong from the first day

Symptom signature. No event explains the weakness, because there was never a strong period. The site launched flat and stayed flat.

How to confirm. Compare actual traffic and dwell time against the assumption in the original site case. This is uncomfortable work, since it audits a decision somebody in the business already made and defended.

Cost of calling it wrong. You spend three years cycling remedies through a site that no remedy reaches. Operators who run this well set a limit: after a defined set of interventions, a chronic loser gets switched off, sold, or moved, and the freed capex goes to something that can pay it back. Operators running large mixed estates describe exactly this call. Zapmap has started to see it in its own data, noting that poorly performing chargers are being taken out of public use.

3. The moves your own data can't see

Some causes hide inside your estate. Others sit entirely outside it, and those are the ones your dashboard is built to miss.

Your reporting shows your own sessions, uptime, and tariff. It shows nothing about the catchment around a site. A competitor opening two miles away. A rival cutting its pay-as-you-go rate last Tuesday. Either can pull a healthy site's volume down within days, and neither leaves a mark in the system you use to watch for trouble. The site reads fine on every internal measure. Success rate perfect, hardware green. The drivers just went somewhere cheaper or closer.

This is why a step change matters. When utilisation drops on a given date while your success rate remains steady, the cause is almost never within the unit. Something shifted in the market that day. Zapmap recorded on-street charger numbers growing 18% year on year through H1 2026, the fastest period yet, so the chance that a rival appeared in your catchment keeps climbing. Benchmark your own price while you look. Sit at or below the market rate and still lose volume, and price is not the whole story; a nearby deployment probably is.

You cannot respond to a move you never saw. Most operators learn a rival cut prices weeks later, from a sales rep or a quarterly review, long after the volume left. Watching the catchment, not just the estate, is what lets you make that call while it still matters, instead of writing it up afterwards.

4. The revenue you have already paid for

A charger's cost is fixed. The hardware, the installation and the grid connection behind it all get paid whether anybody charges or not. That single fact decides where the money leaks.

It means an empty socket is never neutral. Every session that walks to a competitor you did not spot, and every quiet hour that passes with the bay idle, is a contribution you have already paid for and did not collect. A busy site can still lose money, and a half-empty one bleeds it slowly enough that nobody flags it until the year-end margin lands.

The first leak is price. When a rival's move is real and lasting rather than a short promotion, holding your tariff out of principle just funds their growth. When it is a time-boxed deal, matching it starts a race down that nobody wins. The difference is whether the move has an end date, which is why you establish that before you touch your own price.

The second leak is time. Most sites do not underperform across the whole day. They fill at peak and sit dead in the trough, and that trough is capacity you are paying for and giving away. Time-of-day pricing pulls price-sensitive drivers into the quiet window. A fleet or depot deal contracts the dead hours to a local operator who values a guaranteed slot more than a low headline rate. Neither touches your peak margin, and both turn idle capacity into sessions. The test is simple: did off-peak volume grow without eroding what you make when the site is busy?

None of this shows up as a fault, because nothing failed. It shows up as a site that quietly earns less than the one down the road, and closing that gap is the cheapest margin you will find.

5. Where the manual version stops working

An hour per site is affordable. A thousand sites a week is not.

You cannot rank a thousand chargers by hand every Monday, hold a likely cause for each weak one in your head, and still recall six weeks later whether the tariff change at site 412 moved the number or whether the season did. So the loop degrades into a rescue: whoever shouts loudest gets attention, the same three sites get fixed twice, and the check-back disappears.

Operators with large estates describe some version of this.

The cost is not abstract. A weak site you never diagnosed keeps paying its grid connection, its maintenance contract and its capital charge while returning a fraction of the sessions it should. Multiply that across the tail of any estate, and you have the gap between the profitability number on the board slide and the one in the accounts. Diagnosis is the cheapest lever in the business, and almost nobody runs it systematically.

What we built

Dodona Network Optimisation ranks every site in your estate by the gap between what it pulls and what it should pull, then lets you quickly analyse the likely symptoms: demand, price, competitive activity, a fault, or placement.

We are opening a beta to a select group of operators in September, and several networks are already in.

Next: 23 ways CPOs fix underperforming sites: the remedy playbook

Sources

• ChargerHelp, first-time charge success rate analysis, 2025 (100,000+ sessions, 2,400 chargers)

• J.D. Power, US Electric Vehicle Experience Public Charging Study, 2025

• Zapmap and Green Finance Institute, UK charge point utilisation report, 2026

• Zapmap Price Index, July 2026

• Zapmap UK charging infrastructure statistics, H1 2026

• The Public Charge Point Regulations 2023, regulation 7