Today, the availability of mobile apps is on the increase, producing a noticeable change in how humans experience computing. Mobile phones have undoubtedly made life ‘on the go’ easier. Imagine not going to a grocery store but still being able to order them from your mobile. Imagine not going to the bank but still transferring money to friends and family with a click of a button from your mobile. All thanks to the app developers and the awareness created by the tech industry about the importance of mobile apps. This white paper explains how Arrk Group helped a customer build a bespoke mobile app to serve the needs of their users and improve user experience in their interaction with the platform.

The customer is a key player in the student discount industry in the UK and was looking to launch a refreshed and rebranded version of the app. The target audience was mainly between 16 and 25, so it was crucial to consider features and colour schemes that would attract those users. The team identified different personas and developed use cases around them. The app needed to be user-friendly, fast, responsive, and engaging enough to attract repeat visits. Special attention had to be given to the user experience around sign-in and sign-up flow for existing users who were migrating from the older platform to the new app. Arrk’s team collaborated with stakeholders to design and iterate user flow versions, identify user journey pain-points, and study competitor features. Timing the app launch with peak sales season required stakeholder approval of a minimum viable product.

The team decided to build native apps for iOS and Android because of the simplicity on offer. It is always easier for native apps to integrate with some key features offered by Apple and Google out of the box, and worth mentioning that these features are always made available on native first as compared to hybrid apps. Swift (for iOS) and Java, Kotlin (for Android) were the chosen languages, and the team has been working through the latest versions to stay up to date. The idea from the onset was to keep the app lightweight and render most of the data using backend services rather than building custom logic on the front end; this helps us stay flexible and push minor changes without publishing a newer version of the app.

JOURNEY SO FAR

The engineering team at Arrk continues to work with the stakeholders to develop bespoke features for the app that fit the long-term vision of the product. Integration with a third party to provide a digital solution to purchase and verify proof of age ID card, the launch of a brand-new home screen, improved onboarding journey for the user, and a dedicated section inside the app to store the latest notifications are a few of the key pieces of functionality developed over the last two years since the time of launch. The engineering team has also achieved unit test coverage of ~80% and considers it a ‘to-do’ task when picking up any new functionality. This is complemented very well by the test automation coverage, which helps us find bugs quickly by running it across various environments and, in turn, saves us much manual effort in regression testing.

The team also understood the importance of capturing analytics and worked on capturing the simplest user interactions within the app. This gives the marketing team a deep insight into user behaviour and spending patterns across demographics, and this helps the business make informed decisions when running brand campaigns in the future.

A/B testing of features, built-in remote configuration to turn a piece of functionality on/off as per business/user need, and staggered releases over a period have been implemented by the team to understand the pulse of the user base and stay on top of their needs. We also use a tool called AppFollow to check the trend for some key statistics and stay abreast of our competitors. AppFollow also provides integration with our customer support portal to quickly reply to any user reviews on the App Store or Play Store, and this comes in handy.

KEY STATISTICS

Listed below are a few of the key statistics that the app has managed to achieve over the past couple of years –

• 100k+ downloads on iOS (app store) and Android (play store) each
• App Store (iOS) rating at 4.5 and Play Store (Android) rating at 3.8, and organically growing
• Upwards of 100k monthly active users combined across both platforms
• Daily user engagement stands at around 2 minutes per user
• Crash-free users above 99.5% for iOS and Android each
• The adoption rate for a new app version is upwards of 90% within the first seven days of release

The engineering team at Arrk continues to tap into the latest trends in the fast-paced app development world and add value to the platform. Keeping it simple but effective has been our mantra, and we intend to do that going forward.

Digitalisation is sweeping every area of modern life, and any business that fails to keep up with this trend will be left behind. Companies need to adapt and utilise digital technology in all areas. But whose responsibility is it to take charge of digital transformation?

Until recently, CDOs (Chief Digital Officers) were primed to take on this new challenge, but change is upon us yet again.

The digital transformation just won’t stand still.

 

The need for a CDO

Long gone are the days when digital technology was an outside-the-box innovation. It’s essential to how modern businesses are run. Those who don’t get on board are essentially sailing against the tide, while competitors sail off into the sunset.

That said, with so many different types of technology and areas of implementation, managing a digital transformation is no mean feat. That’s why, in recent years, the role of CDO became increasingly common among businesses.

In 2017, PwC found that 19% of companies have a CDO or equivalent, up from 6% in 2015. The numbers varied by country, with a digital leader at 62% of French companies, 39% and 35% in Germany and the UK respectively, and an average of 38% across Europe.

 

The problem with a CDO

Much like digital technology itself, modern business is dynamic. Already we’re seeing a new trend on the horizon, with CEOs (Chief Executive Officers) taking on the responsibility of the CDO. Why? In short, digital transformation is quickly becoming the top priority for businesses.

Typically, CDOs report to the CEO of a business, freeing up their time to focus on other aspects of the company. The CDO themselves don’t have the authority to commit resources – financial and staff – where it’s needed. Or at least not with the immediacy that’s required.

 

Shifting responsibilities

That’s exactly why firms are fast realising that the digital transformation is exactly where the CEO’s focus is needed. They have that authority, along with the position and ability to get the board on side. So, when firms are hiring a new CEO, they are typically looking for someone capable of taking on the CDO role themselves – rather than someone who will delegate such a crucial responsibility.

MIT’s Sloan Review found that a massive 41% of digitally mature companies – those who are closer to an ideally transformed organisation – put the responsibility of digital transformation with the CEO. Similar figures are true for digitally developing companies with 31%.

It’s only those early on in their digital transformation where things differ. Most commonly for these companies, it’s the IT department and CDO (23%) who take charge of digital technology. Clearly, there’s something to be said for the pattern on businesses shifting responsibility as the digital transformation moves further down the line.

 

Why the shift?

While an IT-centric approach is useful in the early stages of digital transformation, it isn’t the sole concern. In fact, as organisations mature digitally, the IT department typically has less control over the digitalisation process.

Why? Digital transformation isn’t just about technology. Far from it, people and process are just as, if not more important than the technology being used.

With a CDO focussed solely on technology and its applications, rather than the people and business more broadly, there’s only so far they can take the transformation. The result, in some cases, is a technology-led transformation with sophisticated technology that doesn’t meet the requirements or get the buy in it needs from the business to be a success.

CEOs on the other hand know all about a business. They know the culture, the workforce and the objectives both overall and in various departments. Or at least they should. If this can be combined with digital competence, effective management and the vision to apply the right digital tools where required, we can certainly expect to see more CEOs managing digital transformation moving forward.

 

If you want to find out how far along the digital transformation journey your company is, why not take our Digital Maturity Assessment? 

Data underpins most of the technologies popular today, and big data refers to large datasets that cannot be handled by traditional databases. Big data is high-velocity, high-variety and high-volume, requiring particular methods for managing or processing that differ from traditional data management technologies.

We are collecting more and more data from many different sources in all manner of formats.  It enables us to make better predictions about future patterns but also presents management and analysis challenges.  

Artificial Intelligence

Artificial intelligence is the simulation of human intelligence by machines. Though these technologies are still in their early stages, big data is being used to feed AI programs and make them more viable. Access to more data than ever before means we can develop smarter machines.

At the moment, this is resulting in Virtual Personal Assistants, Smart Homes – including technologies such as Google Home and Amazon Echo, and Google DeepMind, which beat the world Go champion.

Computer game systems can monitor user behaviour by analysing natural language in the in-game chat, and serve a penalty to deter abusive behaviour. Google Translate is approaching the accuracy of human translators by analysing sentence patterns in millions of documents.

User focus in content creation

Leveraging big data for content creation is still set to be a big trend. For example, Netflix produces programmes based on data collected from their users’ viewing preferences.

The Netflix-owned US version of House of Cards was commissioned based on data that showed a large pool of their users liked the British House of Cards, Kevin Spacey films and the film director David Fincher. This played a large role in their commissioning the David Fincher directed House of Cards series starring Kevin Spacey, and it was very popular.

The company has also awarded a $1 million prize to the team who improved their viewing matching system by 10%.

Moving to the cloud

Data processing is moving to the cloud, instead of being conducted on-site. This can be done with Amazon’s data warehouse, Google’s data analytics service or IBM’s cloud platform, for example.

Popular open source data analytics tools like Hadoop were designed to work on clusters of in-house machines but they can also be deployed in the cloud.

This means that data and analytics operations are more easily scaleable as cloud hosting is more flexible. It means that companies can trial computing their data in their cloud. This also eases pressure on companies to find the technical talent to run their in-house clusters.

However, there are still technical challenges with hosting any kind of data in the cloud, but particularly in big data, such as needing a very high speed internet connection to handle the high velocity of data.

Cybersecurity and data privacy challenges

Storing more data creates even more opportunities for hackers to exploit personal user details. It’s just as well that £1.9 billion has been announced by the government to help protect companies and their customers from cyber attacks.

Many high-profile cyberattacks, such as the LinkedIn data breach that impacted 17 million users, highlights the urgent need for the government and businesses to protect their data. Consumers are becoming more aware of the data that they allow to be collected and demanding better protection.

New European Union regulations in the form of the GDPR (General Data Protection Regulation) insist that companies improve the security around the data they are collecting, and, perhaps more importantly, gain explicit consent from users to collect their data.

Data self-service platforms

Our ability to analyse big data is going to develop further with platforms that enable business users to make sense of data. Data self-service platforms are a viable alternative for companies with no in-house data analysts or data scientists, and include platforms such as Trillium and Hunk.

These have arisen partly in response to businesses demanding real-time responses to their data, as well as a skills shortage in data scientists. Gartner predicts that the global business intelligence and analytics software market will grow to £14.7 billion in 2017.

Move to stream processing

Traditionally, companies have tended to batch-process data. Continuous analysis of data is now required as businesses recognise the need to process quickly. Speed is crucial in operations such as fraud detection, trading and system monitoring.

Stream processing handles high volumes of data in real-time as it is being collected by the server. It was first used in the finance industry when the stock exchange moved from floor-based trading to electronic trading and is now commonplace.

For example, fraud detection systems process millions of card transactions in real time, so companies can detect potential fraud through analysis of spending patterns. The electricity generators and distributors monitoring hundreds of thousands of homes and businesses in real time can use stream processing to ensure adequate availability in the right locations.

Collecting more data

It’s just as well that businesses are moving to the cloud, as the amount of data we collect is only going to keep on growing. The world is set to create 180 trillion gigabytes of data annually by 2025, according to International Data Corporation (IDC).  The Internet of Things will generate vast amounts of data in many formats; including sensory data, video, audio and natural speech. Companies will need to leverage this to improve services for their customers.

The smart home market has the ability to amass even more data than we previously imagined. Our devices know what time we get up, how we operate our homes, and which groceries we buy. Our smart cars know exactly where we travel to and our fuel consumption. This data can be used to improve sustainability, for example by turning off lights when we’re not using them, or efficiency by diverting resources to where they are most needed.

Companies will also be making better use of their ‘dark data’, which is data not currently being leveraged for a business purpose, and can be paper-based. This could include analysing expense and travel reports for salespeople to determine productivity, for example.

Data lakes

In the enterprise, there will be an increase in what are known as data lakes, making it easier to draw out business insights. Data lakes are centralized repositories that hold a vast amount of data in its native format.

The advantages of using data lakes include it being a low-cost form of storage for large amounts of data that is easily scalable, and supporting multiple programming languages and frameworks because the data is unstructured.

They have potential to help organisations work in a more coherent manner by storing all organisational data in one place. Users can be issued different security permissions to prevent anyone gaining access to all of the data to ensure security.

Data is going open source

Big data is dominated by open source tools such as Hadoop, and database mining tool RapidMiner. It’s no surprise that the future of big data is open source.

Sharing data is going to be important in developing new technologies. For example, companies like Google and Facebook share their data to progress the field of deep learning.

Google is partnering with the medical field as one London NHS trust has already shared patient details with its AI technology DeepMind to test an alert system for kidney injuries.

Final remarks

Big data has longevity and is much more than just a tech industry buzzword. It must not be seen as an isolated area of tech since it underpins the development of many areas of modern technology.

Big data drives the progress behind breakthrough technologies transforming our environment, such as machine learning and the Internet of Things, or how modern security agencies tackle crime.

The option to move to the cloud enables more companies to take advantage of big data in a way that is scalable. Making use of more data, and open data-sharing, is the future.