What is the Battery Status API?

The Battery Status API is a deprecated web specification that allowed websites to access information about a device’s battery level, charging status, and estimated time until full or empty. Originally intended to help developers create energy-efficient web applications, it was later removed from modern browsers due to significant privacy concerns.

The initial concept behind the API was straightforward and seemingly beneficial for users. It was designed to give web developers a window into a device’s power source, primarily for mobile phones and laptops.

A website could, for example, check if a user’s battery was critically low. In response, it could automatically switch to a ‘low power’ mode, perhaps by pausing non-essential animations, stopping video preloading, or reducing the frequency of background data synchronization.

This functionality was introduced by the World Wide Web Consortium (W3C) and saw implementation in major browsers like Google Chrome and Mozilla Firefox. The goal was to align web applications with the capabilities of native applications, which have long had access to this kind of system information.

On paper, it represented a step forward for the mobile web. It promised a smarter, more considerate browsing experience that could help users squeeze out a few extra minutes of device life when they needed it most. However, the potential for misuse soon overshadowed these intended benefits.

How the Battery Status API Worked

The technical mechanics of the Battery Status API were relatively simple, which contributed to its quick adoption and, eventually, its widespread abuse. It operated through a JavaScript interface that was accessible via the browser’s `navigator` object.

A developer would make a call to `navigator.getBattery()`. This function did not return the data directly but instead returned a `Promise`. A Promise is a JavaScript object representing the eventual completion or failure of an asynchronous operation.

Once this Promise resolved successfully, it provided access to a `BatteryManager` object. This object was the container for all the battery-related information that the API exposed to the website’s code.

The `BatteryManager` object had several key properties. The most important were `level`, a number between 0.0 and 1.0 indicating the battery percentage, and `charging`, a boolean value (`true` or `false`) that showed if the device was currently plugged into a power source.

For instance, a `level` value of 0.82 meant the device had 82% battery remaining. This high level of precision was a critical factor in the API’s later privacy issues.

The API also provided two time-based properties: `chargingTime`, which estimated the seconds until the battery was fully charged, and `dischargingTime`, which estimated the seconds until the battery was empty. These values were often estimations and could be unreliable.

Beyond just reading the status once, the API was event-driven. Developers could attach event listeners to the `BatteryManager` object to react to real-time changes. These events included `levelchange`, `chargingchange`, `chargingtimechange`, and `dischargingtimechange`.

This event model allowed a web page to dynamically adapt. For example, a video streaming site could reduce the stream’s bitrate automatically when a user’s device fell below 10% battery, or a web-based game could pause processor-intensive physics calculations.

Here is a simple code example showing how it was implemented:

navigator.getBattery().then(function(battery) {
  // Log the initial battery status
  console.log("Battery Level:", battery.level * 100 + "%");
  console.log("Is Charging?", battery.charging);

  // Add an event listener for changes
  battery.addEventListener('levelchange', function() {
    console.log("New Battery Level:", battery.level * 100 + "%");
  });
});

The core problem was not the code’s complexity but the data’s uniqueness. Security researchers demonstrated that the combination of battery `level` (a highly specific number) and `charging` status was surprisingly unique to a single user at any given moment.

This combination could be used as a short-term identifier, or ‘fingerprint’. This fingerprint could track a user as they moved between different websites, even if they cleared their cookies, used a VPN, or browsed in ‘incognito’ mode.

A user’s battery level of 91.5% (`0.915`) while charging is a specific state. Few other users visiting the same set of websites in a short time frame would have the exact same value. This turned a user experience feature into a powerful tracking mechanism.

Because of this demonstrated privacy risk, browser manufacturers made the decision to deprecate and remove the API. The potential for harm was deemed far greater than the limited utility it provided for legitimate use cases. The web development community has since moved toward other methods for performance optimization that do not compromise user privacy.

Case Study: E-commerce Price Manipulation

Scenario A: GoFlights’ Predatory Pricing

GoFlights, a popular online travel agency, saw the Battery Status API as a tool for revenue optimization. Their data science team formed a hypothesis: users with a low battery are more anxious and more likely to make a purchase quickly without shopping around.

Based on this idea, they implemented a dynamic pricing rule. Any mobile user browsing their site with a device battery level below 20%, and who was not currently charging it, was shown slightly inflated prices for flights and hotels.

The price increase was subtle, usually between 4% and 7%, small enough that most users would not notice. To enhance the effect, the system would also hide certain promotional codes and ‘last-minute deal’ banners from this user segment, creating artificial urgency.

What Went Wrong

The strategy worked for a few months, generating a small lift in average order value. However, a technology journalist discovered the practice by accident. While searching for a flight on their phone, which had a low battery, they saw a price of $450. A few minutes later, after plugging in their phone and refreshing, the price dropped to $420.

Intrigued, they investigated further and confirmed the link between battery level and price. They published an investigative article that quickly went viral. The public outcry was immense, with users feeling manipulated and exploited. The hashtag #BatteryScam trended, and GoFlights faced a significant brand crisis.

The Fix

The company’s leadership was forced into damage control. They issued a public apology, claiming the feature was an ‘ill-advised experiment’, and immediately removed the battery-based pricing algorithm. To regain customer trust, they launched a ‘Transparent Pricing’ guarantee and offered discount vouchers to affected users.

The incident cost them dearly, not just in lost sales during the boycott but also in the long-term erosion of brand loyalty. It became a textbook example of how unethical use of user data can backfire spectacularly.

Case Study: B2B Lead Generation Exploitation

Scenario B: CloudCorp’s Aggressive Sales Tactics

CloudCorp, a B2B SaaS provider, integrated the Battery Status API into its lead generation forms. Their sales team theorized that a potential customer filling out a demo request form on a device with a low battery was a ‘hot lead’ in a moment of urgent need.

They configured their CRM to flag any incoming lead from a device with under 15% battery as ‘High Priority’. These leads were immediately routed to the company’s most tenacious sales representatives with a directive to call within 60 seconds of form submission.

The follow-up email and call cadence for these flagged leads was also set to be twice as frequent as for standard leads. The goal was to capitalize on the perceived urgency and close a deal before the prospect’s phone died or they had a chance to research competitors.

What Went Wrong

The strategy was a complete failure. Prospects were alarmed and annoyed by the instant phone calls, often viewing the practice as invasive and ‘creepy’. They felt pressured rather than helped, and the aggressive follow-up led to a high number of unsubscribe and ‘do not contact’ requests.

Feedback on third-party review sites mentioned CloudCorp’s ‘desperate’ sales tactics. The conversion rate for the ‘High Priority’ segment was actually 30% lower than for regular leads. The company was actively damaging its reputation and alienating potential customers.

The Fix

During a quarterly review, the sales operations team identified the negative trend. After correlating the poor performance with the ‘High Priority’ flag, they investigated the source and uncovered the flawed battery-level assumption. The feature was immediately disabled.

They transitioned to a more intelligent lead scoring model based on firmographics and on-site behavior, such as which case studies a prospect downloaded. This approach led to more relevant and welcomed sales conversations, ultimately improving their lead-to-customer conversion rate.

Case Study: Publisher Ad Network Fingerprinting

Scenario C: AdMetric’s Covert Tracking

AdMetric, a digital advertising network, faced a growing challenge: the decline of third-party cookies. To maintain their ability to track users and offer targeted advertising, they turned to browser fingerprinting techniques.

The Battery Status API became a key component of their fingerprinting script. They collected the precise battery level, the charging status, and the estimated discharging time. They combined these data points with other signals like the browser’s user agent string, screen resolution, installed plugins, and system fonts.

This combination created a highly unique identifier for each user’s device. This fingerprint allowed AdMetric to follow a user across all the publisher websites in its network, building a comprehensive profile of their interests and browsing history without relying on a single cookie.

What Went Wrong

The practice was exposed in a widely-circulated academic paper on web privacy. The researchers specifically identified the Battery Status API as a significant enabler of cookie-less tracking and named several networks, including AdMetric, that were using it.

The report triggered a response from browser vendors. Mozilla was the first to act, removing the API from Firefox and explicitly citing the privacy research as the reason. Other browsers soon followed suit, rendering AdMetric’s primary tracking method obsolete.

The Fix

With its fingerprinting model broken, AdMetric’s targeting effectiveness plummeted. The company was forced to pivot its entire business model. They abandoned active user tracking and invested heavily in privacy-forward technologies like contextual advertising, which targets ads based on the content of a webpage rather than the history of the user.

The shift was costly and difficult, but it ultimately made their business more resilient to the web’s ongoing privacy evolution. The episode highlighted the danger of building a business on technologies that exploit user privacy loopholes.

The Financial Impact of Privacy Missteps

The financial consequences of misusing an API like the Battery Status API extend far beyond any short-term gains. The primary risk is the severe and lasting damage to a company’s reputation, which directly impacts its bottom line.

For an e-commerce company like GoFlights, the public backlash from their price surging scandal resulted in a tangible drop in bookings and revenue. The cost of a public relations campaign to restore brand trust, coupled with the loss of loyal customers, can easily run into millions of dollars.

Furthermore, these practices invite regulatory scrutiny. Under privacy laws such as the GDPR in Europe or the CCPA in California, using device data to discriminate on price without explicit and transparent user consent can lead to massive fines. These penalties are often calculated as a percentage of a company’s global revenue, representing a significant financial threat.

In the B2B space, the financial impact is seen in the sales funnel’s efficiency. CloudCorp’s strategy increased its customer acquisition cost (CAC). They were spending marketing budget to generate leads, only to have their invasive sales process destroy the opportunity, wasting that initial investment and damaging their brand’s professional standing.

The true financial benefit lies in proactively respecting user privacy. Brands that build a reputation for ethical data handling foster stronger customer loyalty and achieve a higher lifetime value (LTV). Trust is a valuable asset that pays long-term dividends.

By avoiding manipulative tactics, companies reduce customer churn and build a more sustainable and resilient business. The ROI of privacy is not a short-term metric; it is measured in long-term brand equity and the avoidance of catastrophic fines and reputational crises.

Strategic Nuance: Myths and Realities

Understanding the full story of the Battery Status API requires moving past its intended purpose and examining its real-world consequences. Several myths surround the technology and its deprecation.

Myths vs. Reality

Myth: The API was created to provide better, energy-saving user experiences on websites.

Reality: While that was the official intention, its most impactful application in the wild became user tracking and behavioral manipulation. The potential for privacy abuse was so great that it completely overshadowed its limited UX benefits, leading directly to its removal from the web platform.

Myth: Only sophisticated ad-tech firms had the knowledge to use the API for fingerprinting.

Reality: The code to access the battery status was extremely simple. Many third-party scripts and analytics libraries included it as a data point, meaning even small websites could have been unknowingly participating in large-scale tracking networks.

Myth: Removing the API was a major setback for creating power-aware web applications.

Reality: The actual benefits for power saving were minimal. Modern operating systems and browsers are highly optimized for power management. A far more effective strategy for developers is to focus on general performance optimization, like reducing JavaScript execution, which benefits all users and saves more battery life than reacting to the power state.

Advanced Alternatives and Advice

Focus on Core Web Vitals, Not Power State: Instead of trying to guess a user’s context from their device’s battery, concentrate on building a universally fast and efficient website. A performant site naturally consumes less power. Use tools like Google’s Lighthouse to audit your site’s performance and improve metrics like Total Blocking Time. This is a more reliable and respectful way to be ‘battery-friendly’.

Respect the ‘Save-Data’ Header: A much better, privacy-preserving signal is the `Save-Data` client hint request header. When a user enables a ‘data saver’ or ‘lite’ mode in their browser, this header is sent with their request. This is an explicit signal from the user to reduce data consumption. You can use it to serve lower-resolution images or disable video autoplay, directly honoring the user’s choice.

Implement Ethical Personalization: If you want to personalize your website’s experience, use signals that users provide transparently and willingly. This can include on-site behavior (like pages viewed), items added to a cart, or explicit preferences they set in an account profile. This approach builds trust, unlike using covert signals from a device’s hardware state to make assumptions about their behavior.

Abisola

Meet Abisola! As the content manager at ClickPatrol, she’s the go-to expert on all things fake traffic. From bot clicks to ad fraud, Abisola knows how to spot, stop, and educate others about the sneaky tactics that inflate numbers but don’t bring real results.

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