Category: Battles

Which mobile carpooling application has the greatest environmental impact?

Reading Time: 8 minutes

Everyday car-sharing is a way of sharing the environmental impact of car travel. There are applications that put drivers and passengers in touch with each other. However, the savings made during a journey must not be outweighed by the impact of the IS of these services. In this article, we will look at the eco-design practices of three daily car-sharing applications: BlaBlaCarDaily, Karos and Klaxit.

Methodology 

This comparative study of mobile applications examines various aspects, such as the size of APK files (the installation files for Android applications), application compatibility and the greenhouse gas (GHG) emissions caused by their use. The results highlight significant differences between applications, underlining the importance of implementing an eco-design approach.

First of all, it’s important to remember that the vast majority of a smartphone’s environmental impact is due to its manufacturing phase. A great deal of energy and materials, some of them rare, are needed to manufacture the product. Therefore, to effectively reduce the impact of a mobile application, it is necessary to ensure that it does not force users to change phones in order to obtain a suitable user experience. This involves evaluating a number of criteria, including but not limited to the following:

Compatibility: an application must be compatible with all user terminals (OS, screen resolution, etc.). We found that some applications were designed exclusively for more recent versions, limiting access for users with older devices. This incompatibility often leads to frequent replacement of devices, which can waste natural resources and increase electronic waste.

Battery use: battery wear and tear is one of the material causes of the need to buy a new phone. One of the factors that wear out the battery is the number of charge/discharge cycles the phone goes through. It is therefore essential that using the application does not require too much energy so as not to accelerate the draining of the battery.

Performance: this criterion corresponds to the application’s response time. Firstly, the aim of an eco-design approach is to enable users who do not wish to renew their phone to have a pleasant user experience, even on older devices. Secondly, longer charging times mean faster battery wear. Finally, if the factor limiting performance is network quality, mobile users will be even more affected.

    – Taille de l’APK : cet indicateur provoque 2 impacts différents. Premièrement, une application avec une taille importante nécessite un échange de données plus important pour être installée ou mise à jour. Deuxièmement, un utilisateur qui souhaite conserver son téléphone longtemps peut être amené à devoir gérer des problèmes de manque de mémoire. En effet, la taille des logiciels et des applications va croissante (on parle d’obésiciel). Dans un objectif de l’encourager dans cette démarche, il est nécessaire que le stockage utilisé par l’application soit le plus réduit possible. Dans cet article, nous allons nous focaliser uniquement sur la taille de l’APK, mais une démarche d’éco-conception doit également être menée sur l’ensemble des données stockées sur le téléphone, comme le cache.

APK size: this indicator has 2 different impacts. Firstly, a large application requires more data to be exchanged in order to be installed or updated. Secondly, users who want to keep their phone for a long time may have to deal with memory shortages. This is because software and applications are becoming increasingly large (known as “bloatware“). To encourage this, the storage used by the application needs to be as small as possible. In this article, we will focus solely on the size of the APK, but an eco-design approach must also be applied to all the data stored on the phone, such as the cache.

During an environmental impact analysis at Greenspector, we examine all these points to provide recommendations that will enable our clients to gain an accurate picture of their situation and reduce their environmental impact.

APK size comparison

First of all, let’s assess the size of each app, once installed on a Samsung Galaxy S9 (Android 11). Given that they all fill the same functional areas, we’d expect them to be roughly similar in size. However, the Klaxit application stands out because of its size. There may be several reasons for this difference. For example, the application uses more external SDKs, or it embeds more uncompressed resources (images, videos, etc.).

Application APK size
Karos48.66 MB 
BlaBlaCarDaily55.70 MB 
Klaxit 84.23 MB 

Application compatibility comparison

Another essential criterion we studied was the compatibility of applications with different versions of Android. For example, an application that is not compatible with a version lower than Android 8 would prevent 7.1% of Android owners from using the application.

Application Minimum Android version requiredNumber of Android phone owners able to download the application
Karos Android 8.0 94.0% 
BlaBlaCarDailyAndroid 7.0 96.1% 
Klaxit Android 7.0 96.1% 

The Karos application therefore enables 2.1% less users to use their car-sharing service. This difference may not seem significant, but let’s calculate the emissions avoided by supporting Android 6.0 instead of just 7.0.

According to ARCEP, 37% of smartphone renewals are due to a partial malfunction (real or supposed), including breakage of non-essential components, battery wear, obsolescence and software obsolescence. 
Let’s assume a fair distribution of these four reasons. We arrive at a renewal rate due to the OS (software obsolescence) of 9.25%.

According to ARCEP, there will be an estimated 48.4 million smartphone owners in France in 2021. Let’s assume that each smartphone owner has just one device. Let’s also assume that 10% of French people need access to a daily car-sharing service (strong assumption). This is equivalent to saving on the manufacture of N smartphones:

N = 10% * 9.25% * 2.1% * 48.4 M 
N = 9.4 k 

According to our environmental assessment model, the entire life cycle of a smartphone, excluding the use phase, emits an average of 59 kgCO2eq. The emissions avoided represent:

Etot = 9.4 * 59 = 554 T CO2 eq 

Comparison of GHG emissions

a) Explanation of our methodology

Pour évaluer les émissions de gaz à effet de serre des applications, nous avons suivi une méthodologie rigoureuse basée sur la collecte de métriques pendant le parcours automatisé sur un téléphone réel : la consommation d’énergie de l’appareil, la quantité de données mobiles échangées et le nombre de requêtes HTTP effectuées. Grâce à ces données mesurées et le modèle d’évaluation d’impact environnemental Greenspector Studio, nous sommes en mesure de réaliser une estimation des émissions de CO2. Une explication plus précise du modèle utilisé est détaillée dans cet article : https://greenspector.com/fr/methodologie-calcul-empreinte-environnementale/ 

Assumptions used in the environmental assessment

  • Location of users: 100% in France
  • Location of servers: 100% in France
  • Devices used: smartphones only

b) Explanation of the route

These measurements have been carried out on the basis of user journeys that we have broken down into short stages. We are looking at the situation from the point of view of a passenger wishing to travel daily from the centre of Nantes to Carquefou. These routes have been set up in such a way that the same functionalities are evaluated, namely “listing available drivers” and “having details of a particular journey”. Each route is therefore made up of all or some of these stages:

  • Launching the application
  • Scroll to the home page
  • Load a list of available drivers
  • Load details of first journey

These different stages give us an overview of several elements generally present in a mobile application, such as a scrolling page or a complex element (integration of a route map). The launch stage is also very important because it can provide us with essential information, for example on the caching of data or the time taken to launch the application.

In order to obtain the most reliable measurement possible, we are writing a GDSL script to automate the execution of 5 identical series of tests. GDSL is a language developed by Greenspector that can be used to script test runs on Android and iOS smartphones. For more information, see our dedicated article.

Measurement context

  • Samsung Galaxy S10, Android 10
  • Network: Wi-Fi
  • Brightness: 50
  • Tests carried out over at least 3 iterations to ensure reliability of results

C) Results 

Once the measurements had been taken, the results were analysed to establish an assessment of the carbon footprint of the route chosen for the three car-sharing applications. A table comparing the results was drawn up. The following results are expressed in grams of CO2 equivalent.

Application CO2 emissions (g CO2e)
Karos 1,32
BlaBlaCarDaily 1,88
Klaxit 2,15

The results show a certain disparity between the different applications, which clearly demonstrates the impact that the design and development of an application can have on its greenhouse gas emissions. In this article, we will confine ourselves to a superficial analysis, including only comparative elements for the sake of brevity. For example, the choice of implementation of the interactive map will not be analysed. However, in the context of an application optimisation project, the analysis would be extended to provide more exhaustive recommendations.

In addition to our study on CO2 emissions, it should be emphasised that the environmental impact of applications goes beyond greenhouse gas emissions alone. The manufacture of a smartphone generates other pollution factors. Taking other environmental factors into account, such as aquatic eco-toxicity or the depletion of abiotic resources, would enable us to understand the issues linked to digital pollution in their entirety.

Analyse

Les résultats de l’évaluation environnementale ont montré que le parcours Klaxit était plus émetteur en GES que les deux autres, à hypothèses équivalentes. La cause de ses moins bonnes performances est double : la quantité de données échangée de Klaxit est très importante comparée aux consommations d’énergie et la consommation en énergie se démarque du meilleur parcours, Karos. 95% des consommations de données du parcours de Klaxit se font lors du lancement de l’application.

Application Amount of mobile data exchangedEnergy consumption
Karos 115 ko 9,1 mAh
BlaBlaDaily336 ko 13,1 mAh  
Klaxit 3150 ko 12,7 mAh 
Capture d'écran de l'application Klaxit

On inspecting the Klaxit screen, we noticed the presence of an image carousel, a practice we tend not to recommend to our customers: as well as making navigation unintuitive, the animation leads to continuous energy consumption. As it happens, none of the images in this carousel are cached, which leads to very large data exchanges from the very first screen of the application.

In terms of energy consumption, the Klaxit application is not really more intense than the others. In fact, it’s the number of steps required to complete the same functions that is greater, which lengthens the user journey and consequently increases energy consumption. In fact, compared with Karos, additional scrolling and loading are required. Reviewing the user path and proposing optimisations to shorten it would bring the Klaxit application up to the level of the other two.

So, by simply taking measurements on a rudimentary path, we find two fundamental levers for action in digital eco-design: upstream conception and design (optimisation of the user path, carousel), and development practices (image caching). These two areas for improvement need to be considered together, in order to bring together two key players in the design of digital services: designers and developers.

Conclusion

The analysis highlights the fact that some applications are lagging behind in terms of eco-design. However, there are ways of improving digital services. By better understanding every aspect of a mobile application, we can identify opportunities to reduce the ecological footprint while improving the user experience. For example, designers and developers need to work together to encourage more sustainable and responsible use to ensure the environmental benefits of using a virtuous service. We are ready to support any company wishing to improve its approach to application design.

From Green Pitch to Green IT: are the Champions League finalists’ apps in the game?

Reading Time: 8 minutes

The world of football is one of the most popular and influential sectors of our society. Millions of fans come together every week to support their favourite team and experience moments of passion and excitement. However, it’s time to be aware of the environmental consequences of this all-consuming passion. In this article, we will look at the eco-design practices of the applications of the 4 semi-finalist clubs in the 2022-2023 Champions League.

Calculation methodology

In our comparative study of the mobile applications of the 4 semi-finalists in the Champions League, we examined various aspects, such as the size of the applications, their compatibility and the greenhouse gas (GHG) emissions caused by their use. The results highlight significant differences between the applications, underlining the importance of implementing an eco-design approach.

First of all, the vast majority of a smartphone’s environmental impact is due to its manufacturing phase. A great deal of energy and materials, some of them rare, have to be used in the manufacture of the product. Consequently, to effectively reduce the impact of a mobile application, it is necessary to ensure that it does not force users to change phones in order to obtain a suitable user experience. This involves a number of criteria, including but not limited to the following:

  • Battery use: battery wear and tear is one of the main causes of the need to buy a new phone. One of the factors that wear out the battery is the number of charge/discharge cycles the phone goes through. It is therefore essential that using the application does not require too much energy so as not to accelerate the draining of the battery.
  • Performance: this criterion corresponds to the application’s response time. There are 2 reasons why this criterion needs to be taken into account. Firstly, the aim of an eco-design approach is to enable users who do not wish to renew their phone to have a pleasant user experience, even on older devices. Secondly, longer loading times mean more electricity used, and therefore faster wear and tear on the battery.
  • Application size: this indicator has 2 different impacts. Firstly, when the application is downloaded, a large application requires more data to be exchanged. Secondly, users who want to keep their phone for a long time may have to deal with problems of memory shortage. In order to encourage this sobriety approach, the amount of memory used by the application needs to be as small as possible. In this article we will focus solely on the size of the application, but a sober approach must also be taken to all the data stored on the phone, such as good cache memory management.

During an environmental impact analysis at Greenspector, we examine all these points to provide recommendations that will enable our clients to gain an accurate picture of their situation and reduce their environmental impact.

Analysis of results

Comparison of application sizes

First of all, we evaluated the size of the APK files of the selected applications. We found considerable variations in their size, ranging from light, space-saving applications such as Inter Milan to larger ones such as Real Madrid. These differences can have an impact on mobile device storage memory and data consumption when downloading and updating applications.

The size of the application may vary depending on the phone. The following results were obtained with a Samsung S10 running Android 12.

Application compatibility comparison

Another key criterion we looked at was the compatibility of applications with different versions of Android. We found that some applications were designed exclusively for more recent versions, limiting access for users with older devices. This incompatibility often leads to frequent replacement of devices, which can waste natural resources and increase electronic waste.

ClubMinimum Android version requiredPercentage of Android phone owners able to download the application
Real MadridAndroid 6.097,9%
Manchester CityAndroid 6.097,9%
Inter MilanAndroid 7.096,2%
AC MilanAndroid 5.099,3%

Comparison of greenhouse gas emissions

Explanation of our methodology

To assess the greenhouse gas emissions of applications, we have followed a rigorous methodology based on data measured on real phones concerning the energy consumption of mobile devices, execution time and the quantity of mobile data exchanged. Using this measured data and a model developed by our teams, we are able to estimate CO2 emissions. For a more detailed explanation of the methodology, please see our dedicated article.

Defining the journey

These measurements were carried out on the basis of a user journey that we divided into short steps. The criterion for choosing this journey was that it could be carried out on all 4 applications so that a comparison could be made:

These different steps give us a view of several elements that are typically present in a mobile application, such as a scrollable page, a complex element (a calendar in this case) and a video. The launch steps is also very important, as it can provide us with essential elements of understanding, such as data caching or the time taken to launch the application.

In order to obtain the most reliable measurement possible, we are creating a script to automate the execution of 3 identical series of tests.

The results

After carrying out a detailed analysis, we drew up a comparative table of the results, highlighting the applications with the lowest GHG emissions and those with the largest environmental footprint.

The following results are expressed in tonnes of CO2 equivalent.

The results obtained show a wide disparity between applications, demonstrating the extent to which the way in which an application is designed and developed has an impact on greenhouse gas emissions. In order to keep this article succinct, we are only going to analyse one element that explains this difference. But bear in mind that the analysis can (and should) be taken further to highlight all the critical points of the applications.

In addition to our study on CO2 emissions, it should be emphasised that the environmental impact of applications goes beyond greenhouse gas emissions alone. Experts such as mining geologist Aurore Stéphant have highlighted other aspects to consider when assessing the ecological footprint of the digital sector. In a recent conference entitled “Mining rush in the 21st century: how far will the limits be pushed?“, she addresses crucial issues such as the consumption of natural resources in the production of smartphones, the extraction of the minerals needed to manufacture them, and all the waste resulting from mining. There are many ethical issues to consider in our use of digital tools.

Video impact

During our comparative analysis, we identified a subject that largely explains the differences in environmental impact: video. Videos have become a central element in many applications, and their growing consumption is contributing to the increase in greenhouse gas emissions from the digital sector. The growing popularity of high-resolution video is leading to intensive use of hardware resources on mobile devices. Smartphones need to be equipped with more powerful processors and batteries to process and display this content, which can lead to more frequent replacement of devices. What’s more, they need servers to store and distribute the content, as well as solid network infrastructures to enable smooth streaming. These servers and infrastructures have material and energy requirements at the time of manufacture, and consume a significant amount of electricity.

In this case, we see the following results for the amount of mobile data exchanged for each application:

ClubAmount of mobile data exchangedTest execution time
Real Madrid12.4 MB3min 52s
Manchester City73.3 MB4min 08s
Inter Milan211.3 MB3min 57sec
AC Milan5.8 MB4min 01s

If we take the case of Inter Milan, we can see that this application consumes much more data than its competitors. There are several reasons for this:

  • Non-optimisation of the video: the results of the 30s video viewing steps are very interesting because they allow us to compare the data exchanged by the applications for a single video.
  • Autoplay: feature commonly used on websites and streaming platforms to automatically launch videos or multimedia content as soon as the user accesses a page or application. This practice has a significant environmental impact. Autoplay leads to increased energy consumption, as videos are launched and loaded automatically, even if the user is not actually watching them. The case of the Inter Milan application is quite striking in this respect, as autoplay is activated on all pages containing video. This is particularly the case on the home page, which means that a lot of data is exchanged each time the application is used, even if the user only wants to watch the score of a match.

Video consumption plays a major role in the differences in environmental impact between applications. Mobile developers can help to reduce this impact by optimising video compression, favouring low-resolution delivery by default and encouraging responsible use of video functionalities. Users, for their part, can adopt more conscious viewing practices and limit their video consumption wherever possible. A combination of efforts from all the players involved can contribute to a more sustainable and responsible use of mobile applications.

Video optimisation solutions

Fortunately, solutions do exist and a more in-depth analysis can drastically reduce the impact of videos on the environment.

One approach is to optimise video compression. By using efficient codecs and advanced compression algorithms, it is possible to reduce the size of video files while maintaining acceptable visual quality. This reduces the demand for bandwidth when broadcasting videos, thereby reducing the CO2 emissions associated with their transmission. Intelligent management of video resolution can also help to reduce the carbon footprint of applications.

Alongside these technical measures, it is also important to encourage responsible use of video. Making users aware of the environmental impact of excessive video broadcasting, and encouraging them to adopt practices such as limiting background streaming and reducing resolution when high quality is not required, can have a significant effect on reducing CO2 emissions.

Finally, by combining technical solutions with responsible practices on the part of users, it is possible to considerably reduce the environmental impact of videos in mobile applications. It is essential that developers, content providers and users work together to encourage more sustainable and responsible use of this popular and ubiquitous feature. By acting collectively, we can preserve the quality of our digital experiences while minimising our impact on the environment.

Conclusion

The 2023 Champions League semi-finalists, Real Madrid, AC Milan, Inter Milan and Manchester City, need to consider the environmental impact of their operations. While these clubs enjoy a global reputation and a passionate fan base, it is essential to recognise the environmental footprint associated with their operations, including the use of mobile applications. However, it is encouraging to see that solutions exist to improve this situation. By better understanding these aspects, we can identify opportunities to reduce the ecological footprint while improving the user experience. We are ready to support these clubs as they move towards greater environmental sustainability. Together, we can develop appropriate strategies, implement innovative practices and promote environmental awareness among fans. The aim is to create a genuine synergy between sport and the protection of our planet.

Players in the world of sport, measure the ecological footprint of your application now and take concrete steps to reduce your environmental impact. Together, let’s score goals for sustainability and protect our sport and our planet.

For each site and each application, measured on a Samsung Galaxy S10 (Android 12), the measurements were carried out using scripts based on GDSL (Greenspector Domain-Specific Language). This language is used to automate actions to be carried out on a phone. The measurements were carried out between 3 and 5 May 2023.

Each measurement is the average of 3 homogeneous measurements (with a small standard deviation). The power consumption measured on a given smartphone using a wifi network may be different on a laptop using a wired network, for example. For each iteration on the websites, the cache is emptied beforehand.

On the footprint projection side, the parameters taken into account for these rankings are :

  • Viewing ratio: 100% Smartphone
  • Viewing ratio: 100% Worldwide
  • Server location: 100% Worldwide

The number of users considered for the calculation is 100,000 per day.

Lydia vs Pumpkin

Reading Time: 3 minutes

For this first battle of 2021, we compare two payment applications between relatives: Lydia and Pumpkin. The advantage of these applications? Immediate repayment between friends in just a few clicks via a phone number. No more need to go through the traditional tedious steps of collecting an IBAN, adding it to a list of beneficiaries and the action of a transfer order (which will sometimes be received within 48 hours). Let’s find out together which application has the least carbon impact and the least consumption for your smartphone.

About Lydia: Created in 2011 this French fintech specializes in mobile payment and allows its users to pay and manage their money from the application.

About Pumpkin: Created in 2014 the French application offers payment between relatives and recently allows its users to take advantage of cashback.

The fight

All the spotlights are on the fighters, and the match can finally begin.

In the first part of the battle to measure the impact of the launch phase of the application, on this side, Lydia (0,104 g eqCO2) wins the first round by impacting 2% less than the Pumpkin application (0,106 g eqCO2).

During the second round which corresponds to the usage scenario, collecting a payment, Lydia takes the lead (0.181 g eqCO2) which leads against Pumpkin (0.314 g eqCO2) with a 42% lower carbon impact.

To put an end to this confrontation, we have set up two decisive rounds of observation of the rest phases of each opponent. If the Pumpkin application earns points by showing an 8% lower carbon impact for the foreground inactivity phase compared to Lydia, it is the most impacting on the background inactivity phase by 4%.

The bell rings, end of the match!

The winner

The Lydia app wins this match.

If we add the Carbon Impacts of all the scenarios measured, the Lydia application leads with a 26% lower carbon impact than the Pumpkin application.

Several answers can explain the differences in impact and energy and data consumption: Pumpkin presents several additional screens compared to Lydia:

  • Security screen at launch (pin code)
  • Contact directory synchronization pop-up during payment collection scenario
  • Animation during the confirmation of validation of the transaction
  • The news feed on the home page

For those who like numbers

ApplicationsVersionDownloadsPlaystore GradeApp weight
Lydia10.101 000 000+3,8112MB
Pumpkin5.19.0500 000+4,5119MB

For each of these applications, measured on an S7 smartphone (Android 8), the measurements were carried out through our GREENSPECTOR Benchmark Runner, allowing automated tests to be carried out.

Details of the scenarios:

  • Loading the application
  • Foreground application inactivity
  • Background application inactivity
  • User scenario: collecting a payment (30 seconds)

Each measurement is the average of 5 homogeneous measurements (with a low standard deviation). The consumption measured on the given smartphone according to a Wi-Fi type network can be different on a laptop PC with a wired network. For each of the iterations, the cache is first emptied.

To assess the impacts of infrastructures (datacenter, network) in the carbon projection calculations, we relied on the Greenspector methodology based on real data measured from the volume of data exchanged. This evaluation methodology takes into account the consumption of resources and energy in use for the requested equipment. As this is a very macroscopic approach, it is subject to uncertainty and could be refined to adapt to a given context, to a given tool. For the Carbon projection, we assumed a 50% projection via a Wi-Fi network and 50% via a mobile network.

To assess the impacts of the mobile in the carbon projection calculations, we measure the energy consumption of the user scenario on a real device and to integrate the material impact share, we rely on the theoretical wear rate generated by the user scenario on the battery, the first wearing part of a smartphone. 500 full charge and discharge cycles, therefore, cause a change of smartphone in our model. This methodology and method of calculation have been validated by the consulting firm specializing in eco-design, Evea.

Facebook app vs Facebook web

Reading Time: 3 minutes

For this week’s battle, we are comparing the Facebook application with its web version on Chrome. Note that the measurements were taken from an account connected to the social network.

L’application Facebook created in 2014 and founded by Mark Zuckerberg is an online social network that allows its users to post images, photos, videos, files and documents, exchange messages, join and create groups and use a variety of applications. In 2017, the social network had more than 2.1 billion subscribers.

The fight

All the lights are now turned on the fighters and the match can finally begin.

In the first part of the battle to measure the impact of the launch phase of the application, on this side it is the web version of Facebook (2.48 mAh) which wins the first round by consuming 30% less than the application (3,28 mAh). During the second round which corresponds to the usage scenario, it is the application version (10.13 mAh) which leads to that of the web (21.52 mAh) with a energy consumption lower than 53%. To put an end to this confrontation, we have set up two decisive rounds of observation of the rest phases of each opponent. The web version displays a consumption of less than 30% for the inactivity phase in the foreground but is the most consuming side of the inactivity phase in the background with 3% more than the application version.

The bell rings, end of the match!

The winner

It’s the web version of Facebook that wins this match. The Facebook application is the best in terms of energy consumption, with an overall score of 14.06 mAh to 26.33 mAh, i.e. 39% less battery consumption compared to its web version. However, the web version on Chrome displaying Facebook consumes 71% less data on the user scenario side.

If we project the journey for one minute in carbon impact, the Facebook application consumes 1.42 gEqCO2 or the equivalent of 12.71 meters made in a light vehicle against 1.06 gEqCO2 for the web version or the equivalent 9.48 meters. It is therefore the web version of Facebook that should be preferred!

For those who like numbers

ApplicationVersionDownloadsPlaystore gradeApp weighting (MB)Exchanged data (MB)Memory consumption (MB)Energy consumption (mAh)Carbon Impact (gEqCO2)
Facebook269.0.0.50.1275 000 000 000+4.322712.56321.4516.061.42
Facebook via Chrome81.0.4044.1385 000 000 000+4.32207.35781.8126.331.06

The measurements were carried out by our laboratory on the basis of a standardized protocol, respecting a specific user scenario (launch of the app, timeline scrolling). The other scenarios are the launch of the application (20”), inactivity in the foreground (20”) and inactivity in the background (20”). This methodology makes it possible to estimate the embedded application complexity and its energy impact during the use phase.

The Carbon Impact calculation is based on a projection according to the OneByte methodology of the Shift Project for the server and network part. Assumption calculated according to network and datacenter impact in France, for network connectivity 50% Wi-Fi, 50% mobile network, device life based on 500 full charge / discharge cycles.


Retrouvez la battle de la semaine dernière : Petit Bamboo vs Meditopia Des idées de battles ? Contactez-nous !

Petit Bamboo vs Meditopia

Reading Time: 3 minutes

For this special stay-at-home battle, two online meditation apps will oppose: Petit Bamboo vs Meditopia.

In the left corner Petit Bamboo, application created in 2014 which has more than 5 million active users and which is also a French leader app in meditation. The app is also available in German or Spanish.

In the right corner Meditopia, a French meditation and mental well-being application with more than 3 million users worldwide. The company was created in 2017 and claims to be the best French meditation application.

The weighting

At weighing Meditopia is the heavier application with a weight of 61,7 MB. Its opponent Petit Bamboo is lighter with a weight of 51,3 MB, or 17% less.

The fight

All the lights are now turned on the fighters and the match can finally begin.

In the first part of the battle to measure the impact of the launch phase of the application,  Petit Bamboo (2,5 mAh) wins the first round by consuming 34% less than his opponent Meditopia (3,8 mAh). In the second round that corresponds to the use scenario,  Petit Bamboo (6,1 mAh) still leads to Meditopia (7,6 mAh) with a 20% lower consumption. To end this confrontation, we have set up two decisive rounds of observation of the rest phases of each opponent.  Petit Bamboo is still the leader of the battle with a consumption of less than 23% for the background inactivity phase and 3% for the foreground inactivity phase.

The bell rings, end of the match!

The winner

The Petit Bamboo application won this match with an overall score of 11.4 mAh to 14.8 mAh, or 23% less battery consumption compared to its opponent Meditopia. If we project the journey for one minute in carbon impact, the Petit Bamboo application consumes 0.11 gEqCO2 or the equivalent of 1 meter made in a light vehicle against 3.82 gEqCO2 for Meditopia, or the equivalent of 34 meters.

However, the two applications are different in regard to the data management. Indeed, Petit Bamboo forces downloading programs for listening while Meditopia does not. Thus, Meditopia consumes 36.5 MB of data during the user scenario, where Petit Bamboo consumes only 222 KB. When downloading programs on the Petit Bamboo side, the storage space suffers.

The choice is difficult: if your priority is to consume less battery, opt for Petit Bamboo application especially if you are one of the users who have an expensive data plan or a bad network connection. Prefer Meditopia if your storage space is precious to you.

For those who like numbers

ApplicationVersionDownloadsPlaystore gradeApp weight (MB)Exchanged data scenario (MB)Memory consumption scenario (MB)Energy consumption (mAh)
Petit Bamboo3.7.51 000 000+4.751.30.22230311.4
Meditopia3.10.41 000 000+4.561.736.556914.8

On a 1-minute usage scenario, Meditopia has a consumption equivalent to that of a video games app such as Clash of Clan. As for Petit Bamboo, its consumption is similar to a social app app such as Snapchat. (Source: Study Consumption of top 30 most popular mobile applications)

The measurements were carried out by our laboratory on the basis of a standardized protocol, respecting a specific user scenario (launch of the app, first meditation program). The other scenarios are the launch of the application (20”), inactivity in the foreground (20”) and inactivity in the background (20”). This methodology makes it possible to estimate the embedded application complexity and its energy impact during the use phase.


Read the previous battle : 7 Minutes Workout vs Home Workout. Any battle ideas? Contact-us!

7 Minutes Workout vs Home Workout

Reading Time: 3 minutes

For this special “stay at home” battle, two applications offering full-body workout will oppose:  7 Minutes Workout vs Home Workout.

In the left corner 7 Minutes Workout, the application, which has more than 3,000,000 users, offers sports training lasting 7 minutes based on the HICT (high intensity training circuit).

In the right corner  Home Workout, app part of the Leap Fitness Group which offers daily exercise routines for all major muscle groups.

The weighting

At weighing Home Workout is the most caloric application with a weight of 43 MB. The  7 Minutes Workout application is 14% lighter with a weight of 37 MB.

The fight

The athletes are getting ready to compete on a full-app challenge program!

The first part of the program naturally consists of observing the launch phase (or warm-up) of the application. 7 Minutes Workout (1,71 mAh) wins the first round by consuming 24% less than its opponent Home Workout (2,25 mAh). During the second round which corresponds to the scenario of the user journey (carrying out a beginner sports program), it is always 7 Minutes Workout (5,61 mAh) which leads to Home Workout (6,92 mAh) with lower consumption by 19%. To put an end to this confrontation, we have set up two decisive rounds to observe the rest phases of each opponent. While we are at the stretching stage, Home Workout takes over on 7 Minutes Workout by consuming 18% less in the inactivity stage in the foreground. The applications are neck and neck for the inactive phase in the background, however 7 Minutes Workout takes over by consuming 6% less than its opponent!

The bell rings! End of training!

The winner

Without any surprie, the 7 Minutes Workout app won this match with an overall score of 9,48 mAh to 11,19 mAh, or 15% less battery consumption compared to its opponent Home Workout. Note that 7 Minutes Workout is also less consumer in terms of data exchanged, 16 KB against 2,8 MB for Home Workout.

If we project the journey for one minute in carbon impact, the 7 Minutes Workout application consumes 0,10 gEqCO2 or the equivalent of 0.88 meters performed in a light vehicle against 0,39 gEqCO2 for Home Workout or the equivalent of 3.51 meters.

For those who like numbers

ApplicationVersionDownloadsPlaystore Grade Application weight (MB) Exchanged data scenario (KB) Memory consumption scenario (MB)Energy consumption (mAh)
7 Minutes Workout1.363.111 10 000 000+4,8370.0162799,48
Exercices à la maison1.0.42 50 000 000+4,8432.837711,19

On a 1-minute usage scenario, 7 Minutes Workout’s energy consumption is equivalent to a direct messaging application such as Line. As for Home Workout, its consumption is similar to an application such as a social network such as Facebook Like. (Source: Study Consumption of top 30 most popular mobile applications) .

The measurements were carried out by our laboratory on the basis of a standardized protocol, respecting a specific user scenario (launch of the app, search for a workout, workout exercices). The other scenarios are the launch of the application (20”), inactivity in the foreground (20”) and inactivity in the background (20”). This methodology makes it possible to estimate the embedded application complexity and its energy impact during the use phase.

The Carbon Impact calculation is based on a projection according to the OneByte methodology of the Shift Project for the server and network part. Assumption calculated according to network and datacenter impact in France, for network connectivity 50% Wi-Fi, 50% mobile network, device life based on 500 full charge / discharge cycles.

Marmiton vs 750g

Reading Time: 3 minutes

For this special “stay at home” battle, two applications offering cooking recipes will oppose: Marmiton et 750g.

In the left corner  Marmiton, a French application launched in 2000 which lists more than 71,000 cooking recipes. Marmiton also has 12.8 million unique visitors each month.

In the right corner 750g, created in 2010, is the second site offering recipes and culinary advice the most visited in France (8 million unique visitors each month). This site and application offers more than 80,000 recipes.

The weighting

At weighing 750g is the most caloric application with a weight of 90 MB. The Marmiton application is 61% lighter with a weight of 56 MB, which makes it still a relatively heavy application.

The fight

The fighters are getting ready to go on the grill!

In the first part of the match which naturally consists in observing the launch phase of the application, 750g (2.75 mAh) wins the first round by consuming 7% less than its opponent Marmiton (2.93 mAh). In the second round that corresponds to the use scenario (search for a chocolate fondant recipe), it is always 750g (7.69 mAh) which leads to Marmiton (10.48 mAh) with a lower consumption of 36%. To end this confrontation, we have set up two decisive rounds of observation of the rest phases of each opponent. While we are at the tableware stage, the two applications consume in an equivalent manner for the observation phase in the foreground (1.24 mAh). Nevertheless, in the observation phase in the background, Marmiton is in the lead with 14% less consumption.

The timer sounds, end of cooking for our two applications!

The winner

Without any surprise, the 750g application wins this match with an overall score of 12.6 mAh to 15.4 mAh, i.e. 18% less battery consumption compared to its opponent Marmiton, for whom the check is salty… Note that 750g is also less consumer in terms of data exchanged, 286 KB against 693 KB on the side of Marmiton.

Note that these two applications are particularly rich in elements listed by Exodus Privacy as falling under tracking and analytics tools: 11 for Marmiton, 17 for 750g… It makes people squint on your plate.

For those who like numbers

ApplicationVersionDownloadsPlaystore GradeApplication weight (MB)Exchanged data (KB)Memory consumption (MB)Energy Consumption(mAh)
Marmiton5.2.43 5 000 000+4,59069364215,47
750g4.2.6 1 000 000+4,45628633912,63

On a 1-minute usage scenario, Marmiton’s energy consumption is equivalent to a navigation application such as Google Chrome. As for 750g, its consumption is similar to an application such as a social network such as Instagram. (Source: Study Consumption of top 30 most popular mobile applications)

The measurements were carried out by our laboratory on the basis of a standardized protocol, respecting a specific user scenario (launch of the app, search for a recipe). The other scenarios are the launch of the application (20”), inactivity in the foreground (20”) and inactivity in the background (20”). This methodology makes it possible to estimate the embedded application complexity and its energy impact during the use phase.

Babbel vs Duolingo

Reading Time: 3 minutes

For this week’s battle, two online language learning apps will oppose: Babbel vs Duolingo.

In the left corner Babbel, a paid online language learning app created in 2007 in Berlin. When it was founded, the german startup was the first company to offer an online language learning service. Today, Babbel offers learning 14 languages.

In the right corner Duolingo, created in 2011, the application also offers language learning, but it is free of charge. Duolingo offers a richer catalog than Babbel’s: 37 languages.

The weighting

At weighing Babbel is the heavier application with a weight of 90 MB. Its opponent Duolingo is lighter with a weight of 56 MB, or 61% less.

The fight

All the lights are now turned on the fighters and the match can finally begin.

In the first part of the battle to measure the impact of the launch phase of the application, Babbel (1.5 mAh) wins the first round by consuming 25% less than his opponent Duolingo (2 mAh). In the second round that corresponds to the use scenario, Babbel (13.5 mAh) still leads to Duolingo (19.5 mAh) with a 31% lower consumption. To end this confrontation, we have set up two decisive rounds of observation of the rest phases of each opponent. Babbel is still the leader of the battle with a consumption of less than 34% for the background inactivity phase and 54% for the foreground inactivity phase.

The bell rings, end of the match!

The winner

Without any surprise, the app Babbel wins this game on a global score of 17.2 mAh at 25.5 mAh, or 32% less battery consumed compared to his opponent Duolingo. Note that Babbel is also much less consumer in terms of data exchanged, 224 KB against 4.9 MB on the side of Duolingo.

For those who like numbers

ApplicationVersionDownloadsPlaystore GradeApp weight (MB)Exchanged data (KB)Memory consumption (MB)Energy consumption (mAh)
Babbel20.36.010 000 000+4.5900.224147.917.2
Duolingo4.37.1100 000 000+4.7564.9230.725.5

On a 1-minute usage scenario, Babbel has a consumption equivalent to that of a video games app such as Candy Crush Saga. As for Duolingo, its consumption is similar to a browser app such as Opera Mini.(Source: Study Consumption of top 30 most popular mobile applications)

The measurements were carried out by our laboratory on the basis of a standardized protocol, respecting a specific user scenario (launch of the app, first lesson). The other scenarios are the launch of the application (20”), inactivity in the foreground (20”) and inactivity in the background (20”). This methodology makes it possible to estimate the embedded application complexity and its energy impact during the use phase.

Find the battle of last week : RocketChat vs Slack
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The battle of the week: Leboncoin vs Locanto

Reading Time: 3 minutes

In just a few years, websites connecting individuals through classified ads have been a huge success. Already very popular at its debuts, Leboncoin has quickly established itself in the ranking of the most consulted e-commerce websites in France, in 2019 it occupies the second position. Today’s match therefore pits the French leader Leboncoin with Locanto, the German website present on the international scene.

In the left corner Leboncoin, French leader in classifieds created in April 2006. Leboncoin is also the second most popular e-commerce website in France.

In the right corner Locanto, German free classifieds website created in June 2006, available in 5 languages in 60 countries.

The weighting

At weighing Leboncoin is the heavier application with a weight of 94 MB. Its opponent Locanto is lighter with a weight of 10 MB, or 89% less.

The fight

All the lights are now turned on the fighters and the match can finally begin.

In the first part of the battle to measure the impact of the launch phase of the application, Locanto (1.6 mAh) wins the first round by consuming 11% less than his opponent Leboncoin (1.8 mAh). The difference in consumption is quite marked also on the product searching phase. Indeed, Leboncoin (8.9 mAh) dishes Locanto (11.3 mAh) K.O with a lower consumption of 21%. To end this confrontation, we have set up two decisive rounds of observation of the rest phases of each opponent. During the foreground phase, Leboncoin is still the master of the game, consuming 2% less. For the inactivity phase in the background it is a perfect draw!

The bell rings, end of the match!

The winner

It’s the Leboncoin app that wins this energy battle with a total score of 12.7 mAh at 14.9 mAh, consuming 14% less than Locanto. battery life with Leboncoin. Nevertheless, on the data exchanged side, occupied memory and storage space, it is Locanto which is the least consumer. In economic terms, if your data plan is limited, it will cost you less with Locanto.

For those who like numbers

ApplicationVersionDownloadsPlaystore GradeApp weight (MB)Exchanged data (KB)Memory (MB)Energy consumption (mAh)
Leboncoin4.36.8.010 000 000+3.9942.9585.312.8
Locanto2.7.125 000 000+4.4100.9317.714.9

On a 1-minute usage scenario, Locanto has a consumption equivalent to that of an application of video games as Clash Royale. While Leboncoin is getting closer to the consumption of an application of direct messaging such as Skype. (Source: Study Consumption of top 30 most popular mobile applications)

The measurements were carried out by our laboratory on the basis of a standardized protocol, respecting a specific user scenario (launch of the app, product searching, product overview). The other scenarios are the launch of the application (20”), inactivity in the foreground (20”) and inactivity in the background (20”). This methodology makes it possible to estimate the embedded application complexity and its energy impact during the use phase.

Find the battle of last week : Twitter : video vs image vs gif
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RocketChat vs Slack

Reading Time: 3 minutes

Today’s match will oppose two collaborative communication platforms for professional teams: RocketChat and Slack. Collaborative platforms have replaced emails to facilitate exchanges between individuals and teams and also have improved their productivity.

On the left corner RocketChat, is an open-source collaborative communication platform launched in 2016 and has one of the largest numbers of members of the GitHub developer community.

On the right corner Slack, collaborative communication platform created in the USA in 2013. Slack has 10 million active users per day.

The weighting

At weighing RocketChat is the heavier application with a weight of 94 MB. Its opponent Slack is lighter with a weight of 90 MB, or 4% less.

The fight

All the lights are now turned on the fighters and the match can finally begin.

In the first part of the battle to measure the impact of the launch phase of the application, Slack (1.2 mAh) wins the first round by consuming 17% less than his opponent RocketChat (1.4 mAh). In the second round that corresponds to the use scenario, Slack (6.5 mAh) still leads to RocketChat (8.4 mAh) with a 29% lower consumption. To end this confrontation, we have set up two decisive rounds of observation of the rest phases of each opponent. Slack is still the leader of the game with a consumption of less than 3% for the background inactivity phase. For the foreground inactivity phase it is a perfect draw!

The bell rings, end of the match!

The winner

Without any surprise, it’s the Slack app that wins this game with an overall score of 9.9 mAh at 12.1 mAh, a 18% difference in consumption against its opponent RocketChat. For the data exchanged, it is the same observation, the application Slack is less consuming by 84%.

For those who like numbers

ApplicationVersionDownloadsPlaystore GradeApp weight (MB)Exchanged data (KB)Memory consumption (MB)Energy consumption (mAh)
RocketChat3.5.1100 000+2.5941.1176.112.1
Slack19.09.10.010 000 000+4.5907.3181.29.9

On a 1-minute usage scenario, Slack has a consumption equivalent to that of an application direct messaging such as Line. As for RocketChat, its consumption is similar to an application such as Microsoft Outlook. (Source: Study Consumption of top 30 most popular mobile applications)

The measurements were carried out by our laboratory on the basis of a standardized protocol, respecting a specific user scenario (launch of the app, product searching, product overview). The other scenarios are the launch of the application (20”), inactivity in the foreground (20”) and inactivity in the background (20”). This methodology makes it possible to estimate the embedded application complexity and its energy impact during the use phase.

Find the battle of last week : United Wardrobe vs Vinted
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