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An Outline on Quality Engineering Services

An Outline on Quality Engineering Services

Finding and fixing bugs after the fact doesn’t work in a world where experience engineering drives fundamental digital transformation, and the cost of poor-quality software is enormous.

Quality is an umbrella term. Depending on roles inside organizations, different minds have disparate associations with quality – analysis, testing, data, planning, improvement, management, customer’s voice, or even lawsuits, product recalls, or disasters.

Fundamentally though Quality is about exceeding customer expectations – every batch, every season, every product. After all, the actual quality value is measured in higher revenues from more significant customer satisfaction and higher operational efficiency and effectiveness from increased productivity and innovation.

 How does the Quality variable inform today’s competitive landscape? 

Especially when gaining new customers or increasing market share, companies must continually develop and improve products. So, then, in a marketplace with fewer barriers or boundaries, customers demand higher quality at competitive prices. This premise creates stiff challenges for product testing and quality assurance. How exactly?

Today’s faster release cycle times, cost pressures, and best-in-class user experiences don’t happen in the Quality Assurance (QA) regime, which ‘assures’ quality. Instead, Voice of Customer (VoC) needs to continually factor in the product design and waste identification and elimination that brings down product costs.

 QA and QE. 

Whereas QA is the overall process of ensuring manufacturers make things properly, Quality Engineering (QE) defines (or ‘engineers’) the system that does it. Quality engineers maintain, improve, and monitor the system.

What distinguishes QE methods and tools is the cross-functional approach involving multiple business and engineering disciplines (like Quality management system, Advanced product quality planning, Quality Function Deployment, failure modes and effects analysis, statistical process control, and root cause analysis).

 Overall QE benefits in the 2020s

Saving money: Both – bug fixing and development times – are costly. Quality Engineers have a certain mastery in identifying issues inside a complex system. The outcome? Developers spend less time tracking down bugs. Additionally, delivering on quality before the build reaches production limits costly hotfixes.

Saving time: When the rubber hits the road, teams often sacrifice testing time to meet delivery deadlines. Quality Engineers save precious time by optimizing testing approaches. How? By automating time-consuming tests, identifying efficiency-enhancing tools, and building shared infrastructure across multiple projects.

Enhancing standards: As apps get complex by the day, their architecture needs testing integration between the various layers. When traditional testing doesn’t cut it, Quality Engineers combine their enhanced architecture understanding with a grey-box testing approach. The result is more thorough testing of the whole system.

Improved Planning: Quality Analysts are primarily code-gatekeepers. However, when QA’s identify issues that require re-architecting the application (time-consuming and costly), Quality Engineers facilitate planning discussions, bring insights to highlight limitations, and coordinate with developers to strategize the best ‘build-test’ approaches. Arresting early pitfalls helps in a faster go-to-market without compromising on quality.

Effective communication: Quality Engineers test systems like end-users and understand traceability in the underlying workflows. Doing this informs their ‘bridge’ conversations with technical and non-technical roles. Their valuable insights highlight gaps from both a user and system perspective and build trust across teams. The outcome? Highest product quality.

 Quality Engineering in the age of Agile and DevOps.

As more Agile and DevOps philosophies proliferate across the software development lifecycle (SDLC), Quality Engineering (QE) governance platforms have grown in prominence.

More Quality Assurance, Less Control

In the new world of mobile and IoT, enterprises embrace shift-left or apply more QA efforts earlier in the development lifecycle. Potential problems are easier to catch and less costly to fix.

Test Early, Test Often

In Agile (and Scrum) environments, the idea is to ship products (or code faster) in more iterative loops. So, when the emphasis on debugging begins before development, the QE governance function is working with desired optimality.

Finally, QE Governance benefits the organization’s digital development initiatives. 

The entire product team (developers, designers, managers, QE’s) is trained and tuned on the development process. This radically increases the quality standards and permeates a quality culture across digital transformation programs.

As processes take root, the nascent QE mindsets have to be guarded in ways that slip back to older methods are alerted and corrected. This step is accounted for in the QE governance mechanisms.

QE actively investigates the relationships between in-process metrics, project characteristics, and end-product quality. This is where QE governance measures metrics at the product (cost and quality), process (efficiency and effectiveness), and organizational levels (employee satisfaction and economics). Based on the learnings, organizations engineer quality improvements in both the process and the product.

Conclusion 

QE makes the proposed benefits of Agile and DevOps more real. Continuously validating product attributes across SDLC, a holistic QE approach critically reduces delivery gaps and boosts production expectations.

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How can banks achieve assured release through effective User acceptance testing?

How can banks achieve assured release through effective User acceptance testing?

As Banks race against time to bring for their customers innovative features as part of ongoing change process , similar urgency is also seen in product replacements and technology upgrades targeted towards better customer experience and to meet demanding regulatory requirements, all at short notice.

Between various types of testing – Unit Testing, System Integration Testing, and User acceptance testing – the keyword ‘user’ in UAT, makes all the difference. Additionally, the use of live data and real use cases makes UAT a critical part of the release cycle.

In light of the above, Banks rely heavily on UAT phase to ensure a successful Go-Live. UAT gains significance as it serves as the last gate in Bank’s release certification. More so, the cost of fixing the defects after release is multifold as compared to fixing early. Added to it is managing complexity of customer’s perception of Bank’s IT systems.

Despite a process backed UAT, many Banks are confronted with functional coverage gaps – too less (or too much) testing invariably leads to a higher defect ratio or a longer time window to production.

Top Three UAT Challenges in Banking

The challenges confronting a typical UAT, merit a deep dive into the factors that negatively impact UAT effectiveness. These include top three challenges as listed in the below figure

Figure 1

  1. Tacit Knowledge held by Business Users are not Leveraged for Test Design
    While UAT testers are skilled at converting available requirements into test designs, it is the business users with their exposure of real-world scenarios and expertise of their business environments, that aren’t consulted or engaged enough. Be it ineffective reviews or reviews missed out due to paucity of time, this lack of coverage shows up as production defects later. Ineffective test design reviews, furthermore, results in rework, extension of execution timelines and a high percentage of invalid defects – all eating up valuable triage time.
  2. Quality of Requirements
    UAT defects could be due to inadequate definition or poor translation of the requirements as incorporated in the functional design. If not addressed as part of UAT test design, these gaps in requirements are likely to turn up as defects in production. Ultimately, it is the requirement faults, rather than coding errors, that accounts for significant leakages.
  3. Quantifying coverage and optimising the test pack are both difficult tasks
    Understood in its conventional form, the requirements traceability matrix makes it difficult for business users to assess risk coverage across all components of the tested applications, such as core systems, interfaces, alerts, reports, and satellite systems. Furthermore, traditional test design focuses on increasing coverage by packing in additional singular tests. This results in bloated test packs that are subsequently difficult to maintain.At Maveric, these slews of challenges triggered a ‘what Next’ thought. The innovation challenge we framed was: What might be a simple solution allowing Banks to accomplish reliability in their results and minimize go-live risks, thereby maximizing value of their UAT testing budgets?

Our efforts to combine deep domain knowledge with cutting-edge technology prowess finally resulted in OptiQ!

What is OptiQ?

OptiQ is a proprietary banking domain-led solution with inbuilt design algorithms that detects relationships between functional attributes and business rules to generate an optimal collection of test scenarios with complete business coverage.

Today UAT teams utilize OptiQ to reduce business risks by creating significant UAT scenarios based on business requirements, regulatory processes, new platform technologies, and business user requirements. It is a powerful proposition, that not only remediates the challenges discussed earlier, but also brings in significant benefits as discussed here:

  • Intuitive UI led Solution for Test Design
    Right from documenting requirements to creating test scenarios for the customer journey and transaction lifecycle, OptiQ’s intuitive UI is simple to use. Today business users report enhanced convenience in reviewing and navigating across various test design components.
  • Questionnaire-driven Model to strengthen Requirements by Business and Application Areas
    A simple questionnaire captures user inputs accurately that were either originally unavailable or outdated or has gaps. This feature radically reduces errors in requirement defects and rework.
  • Functional Decomposition by Business Area
    OptiQ’s approach involves generating test scenarios by deconstructing the requirements and translating them into scenarios constructed hierarchically – into products, modules, transactions, and aligned customer journeys .In this new approach, business users are automatically involved in multi-stage reviews right from the initial stages of test design. This ensures early feedback benefits and avoids voluminous test case reviews. Additionally, OptiQ comes with automated controls to help UAT teams identify and correct gaps in coverage, thereby freeing up business users to review and focus on the quality of test design.
  • Layered Traceability for 100% Coverage
    Moving away from traditional practices, OptiQ demonstrates the breadth of coverage for all UAT test components – including applications, alerts, reports, interfaces, and services. The design algorithm ensures stitching of end-to-end test scenarios across the components, thus providing 100% test coverage.
  • Optimization with Flexibility to improve Strength of Coverage
    All tests are not created equal. OptiQ employs algorithms that provide varying degrees of coverage to maximise test coverage with the fewest possible tests, removing redundant, and low-value test cases. Moreover, OptiQ offers business users with options to increase coverage strength by methodically adding test cases. Bringing their tacit knowledge to bear, this feature leads to higher confidence levels.
  • Automated Test Case Generation
    OptiQ provides automatic generation of optimized test scenarios with 100% coverage, thereby unleashing test efficiency gains. UAT teams can now focus on assuring the coverage rather than manually writing voluminous test cases.

Figure 2

Finally, OptiQ comes with pre-loaded retail, corporate and credit cards test functions that help in accelerating the test design.

In summary, Banks undergoing transformations looking for favourable returns from their UAT investments, have to look beyond the conventional test design. It is precisely there, that model based, Algorithm-driven approaches to Test Design such as OptiQ, not only helps them drastically minimize the risks of go-live but also offers quantum value from their UAT efforts.

Originally published on MEA Finance

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The role of Quality Engineering (QE) in Challenger and Digital Banks

The role of Quality Engineering (QE) in Challenger and Digital Banks

Challenger and digital banks are disrupting the banking sector, showing us the future of banking, just like other sectors, is technology. Retail banking consumers have adopted these challenger banks on a massive scale leading to several banks getting recognition and gaining grounds worldwide.

Even though many of these traditional banks now have their digital footprint with apps and other web services that make transactions more straightforward, there is still a meteoric rise in the adoption of these challenger and digital banks. A common trait in most of these banks is using quality engineering (QE) processes and approaches to drive their methods to provide better offerings than banking incumbents. These banks accelerate development to delivery of defect-free software with the best of continuous quality engineering.

The growth in challenger and digital banks

There has been a rapid growth in these challenger banks globally, and there are at least 102 in just the UK. From history, there has been a gradual adoption of FinTech in the UK, which was at a high point of 71% in 2019, a 5X increase from 2015.

This explosion of challenger banks took off in 2020, where Mastercard reports that 42% of Europeans manage their finances digitally more often than before the banking, and 62% are thinking of moving from physical to digital platforms permanently. Just in January of 2020, UK company Revolut could boast of over 8 million subscribers worldwide, and Monzo was adding 55,000 new users weekly.

Revolut, Monzo, and Starling are the market leaders of UK challenger banks, with all of them becoming unicorns meaning they have a value of over $1 billion. Of all the equity deals announced in 2020, 77% of the investments went to these three top banks in five funding rounds. Monzo raised £60m, Starling raised £100m, and Revolut raised a whooping £445.4m.

What is shaping their growth?

A lot of factors are propelling these banks and increasing their adoption, some of these are:

Better Banking legislation in the UK

This is peculiar to the UK as new banking regulations have made it easier for startups to obtain a banking license in the UK. A direct result of the banking license application process introduced in 2014 allowed banks to pre-run a private, staff-only test mode before opening their services to new customers. The Prudential Regulation Authority (PRA) developed this process to foster competition in the banking sector, and it has since opened up several opportunities that challenger banks are taking.

New improvements in technology

There have been rapid improvements and developments in technology, especially in the cloud computing space, that have allowed these challenger banks to offer scalable services. AWS and other cloud providers now support scalable IT infrastructure that allows for iterative development. The alternative would have been on-premise physical hardware changes in their data center every time they need to change infrastructure, which would have reduced growth and increased costs.

Impact of COVID-19

The world is just moving on from the heels of a pandemic that confined us to our homes, which meant no opportunities to visit traditional banks. This has led to the shift of customers to digital services for their finances, with more investors putting large sums of money into these businesses. Many of these challenger banks already operate on the digital platform, giving consumers a sense of control of their finances by focusing on customer experience

Frictionless experience

This is perhaps one of the most significant forces driving the growth of challenger banks as they position themselves to offer an overall experience to traditional banks. These banks use mobile apps, and history has shown people are willing to change their habits when it comes to technology, just like they did with how they buy things or music and book hotel rooms with apps. The same has extended to the banking sector, with these banks offering attractive features such as ease in setting up accounts, attractive rates/fees, different products, etc.

How Quality Engineering (QE) is playing an instrumental role in digital and challenger banks?

Digital and Challenger banks move with digital transformation and are always the first to adopt new technologies to their systems. With their technologies, they set new benchmarks to deliver products to the markets faster and cater to the customer’s needs before they even complain. Traditional quality assurance (QA) methods are no longer impactful for supporting accelerated digital transformation programs. Digital and Challenger banks conduct software application testing in parallel to their development efforts. This fundamental shift in software testing is brought alive through quality engineering principles. Most QE teams work closely with the product developers and operations team to process quicker and consistent releases using test automation methods. This is how QE succeeds over traditional QA plots and plays a central role in helping them provide a consistent and reliable service to their customers.

Everything in the banking sector needs stability and security as mistakes could be very costly and irreparable at any juncture. QE keeps challenger and digital banks a step ahead of all these issues, so their teams do not stagnate at any point in the development cycle. QE mimics how the end-users think and interact with products to deliver an improved customer experience. Embraced with shift-left testing approaches, quality engineering teams bring superior agility and substantial cost advantage for faster time-to-market. Ditching all of the old methods and embracing quality engineering means these banks can deliver quality and speed, which consumers value today.

In today’s world, because there are so many options for consumers to use, mistakes are hardly forgotten and could mean the end of a brand or company. Quality Engineering makes sure the banks detect and correct any defects before they go out into the market and shine a bad light on them. The fast-moving pace of this industry puts challenger and digital banks on their toes to keep innovating and setting new quality engineering standards to beat the odds. Quality engineering is an industry discipline which banks have to consider and induce in its culture to speed up digital transformation.

The Award Winning Story of Allica Bank

Build-out-the-bank QE Programme

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How does testing happen in challenger and digital banks?

Cloud implementation has made it possible to build on the DevOps teams and make testing a continuous process throughout the product cycle. Once the testbed is implemented into the cloud, functional and non-functional testing can detect errors early before releasing the product.

Combining this testing method with quality engineering practices will make it possible to release products earlier but still retain their excellent quality. The team can make changes along the way and implement them into the system instead of stopping the process and making significant changes at the end of the product cycle, which are usually more complicated to handle.DevOps and Agile methods going mainstream have made test automation necessary to reach the end objectives faster.

Maveric’s Intelligent Quality Engineering (IQe) solution is a domain-led master piece for accelerating quality journeys, driven with cognitive powers and embraced with no-code model.

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Wrapping up

Digital and Challenger banks aren’t going anywhere soon, with different companies popping up in the space trying to offer new services to customers. The critical thing for digital-only banks to remember is to make sure the channel through which customers access their services is always available. The competition is heating up in this space, and staying relevant is getting more difficult, especially for smaller startups.

Ensuring they take full advantage of mobile apps and smartphones is the only way to start gaining their footing in this field along with innovation. There are still many challenges consumers face with banking, and if you can provide an outstanding experience while solving these problems, it builds trust and reliability.

Quality engineering will play a significant role in the future of digital and challenger banks, and companies that are willing to embrace technology will be at the front of this change. In the banking industry, there are many quality dimensions to conquer, and it is important to make sure there is nothing hazardous for several clients using the systems daily. This is why you should encourage and foster digital transformation in your business, and the fastest way to do that is through QE.

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Top QE Best Practices for Accelerating Digital Transformation

Top QE Best Practices for Accelerating Digital Transformation

Digital transformation is the implementation of digital technology into all aspects of business, and over the years, it has grown rapidly, especially in the banking industry. Innovation has produced newer technologies for keeping customers satisfied and increasing efficiency simultaneously.

Important key progress in digital transformation includes increasing adoption of increased use of machine learning (ML) & AI, cloud technology for reduced costs, and focus on the long-term effects of digital transformation initiatives. Digital transformation will continue to see tremendous growth in the coming years that will continually disrupt the status quo.

Let us first understand why quality engineering (QE) practices are in super demand for combating the present wave of hyper digitalization.

Why QE practices are advised rather than QA Models for digital transformation?

Development in digital transformation has necessitated the development of QE for better and efficient testing. Here are a few reasons why you should move from QA models and adopt QE practices in their workflows:

  • QE simulates how the end-users think and interact with products to deliver an improved customer experience in any industry, with tremendous success seen in testing mobile applications.
  • Most QE teams work closely with the product developers and operations team to process quicker and consistent releases using test automation methods.
  • QE helps teams to integrate several automated processes and integrate new tools early in the developmental cycle to ensure the products are released faster with test automation. This allows them to use quality test automation frameworks to guarantee faster releases and provide quality products.
  • With the shift-left testing processes in QE methods, developers can quickly find defects and push the products out to markets faster. Shift left testing allows developers to fix defects as soon as they discover them at low cost, faster than QA models and ensure customer satisfaction.
  • Mobile apps are becoming increasingly complex every day, and new IoT devices make it difficult for QA models to keep up with this rapid evolution. QE practices ensure testers can access the latest information and real-time scenarios to detect real-world defects faster before they become harmful to the finished product.
  • Device sharing is a common feature in today’s age, and this puts an increased security risk across systems and devices. QA models typically focus on only the security requirements of standalone applications meaning the process would be carried out across different systems. On the other hand, QE methods can handle all the security risks when data is shared across multiple systems.

QE Platform

Top QE Best Practices for Accelerating Digital Transformation

In the banking industry, there are many quality dimensions to surmount, and it is important to make sure there is nothing at risk for several clients using the systems daily. This is why you should encourage and foster digital transformation in your business, and the fastest way to do that is through QE.

Here are the top five QE best practices for fostering the culture of continuous quality to accelerate digital transformation journeys

  • Use Automated Web Services Testing on Time

    Automated web services are the most common way of communicating with legacy systems that you can use across several areas. Detecting the issues early on in this stage could save your team a lot of time and effort on downstream work. Through this, you can check and quickly detect if a web service has misleading responses or it is incomplete.

    Another important aspect to consider is that third parties typically provide and maintain them, so it would be beneficial to have a dedicated Defect Management Team to handle it.

  • Determine Performance Metrics that Best Define Customer Experience

    Apart from understanding what a company wants in a digital transformation, QE teams will also run tests across several aspects, including accessibility, security, functional and non-functional tests. These tests will explain how the modifications in their business goals and processes have affected customer experience.

    Other metrics that could also help measure their customer experience to other similar apps on the market, including their direct competitors. Over time, these metrics will help increase customer experience in a company’s digital environment and be aware of customers’ expectations in the industry.

  • Communicate with your Clients in the Easy-to-Understand Language

    Products typically have a lot of features that need to be delivered fast. This also means your client will make change requests to dissect into several tasks and user stories. When you get to the final stages and user acceptance testing levels, you have to provide these details in a list that your client can understand and follow through to speed up approval.

    Throughout the development process, make sure the list gets updated and linked to your Product Backlog. You might consider a specific workflow so that when you implement these features in your tracking application, dependencies mapping will be easier.

  • Develop Automation Methods While Communicating with Other Teams
    Automation is a great strategy for extracting vital information about consumer responses and behavioral data. In particular, metrics like the number of users, time spent, bounce rate are very important, and you can collect this automatically. You can easily link this information with conversion rates and other customer experience statistics that inform your performance.

    This method also requires your QE team to collaborate with the development team to create codes that include development tools, frameworks and technologies. The ability of your QE team to scale QE through different environments is a factor in making this work.

    platform available

  • Continuous Performance Testing Through Specialized Teams

    Grouping your teams to work with a focus of the feature through web services to web and mobile applications requires more skills from testers, but it provides reliable results compared with working based on specific technology areas. Efficient testing plays a role in this and has important considerations to consider.

    You should take steps to test every Micro Service when it’s available and, if possible, do the testing across several environments. Through the testing, develop test timeframes for production-like environments.

    The other two key spaces are functionalities consuming 3rd party services and public website areas as they could create negative reactions if they have a poor performance.

Conclusion

Many of these QE strategies and best practices for digital transformation take time to integrate with your process fully and could be very challenging. You should make sure every member of your team is carried along through the adjustment period as it is a complete paradigm shift from what some know. A great way to make the process easier is to use a governance layer through the test organization to ensure the tactical and strategic vision stays on track.

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Elevating Human Experience with the Right Mobile Banking Quality

Elevating Human Experience with the Right Mobile Banking Quality

Mobile banking has rapidly spread in the banking sector and has become an integral part of its operations. Apart from improving customer loyalty and advocacy, banks can greatly benefit from reducing operating costs. As per a research finding, about 72% of all banking customers use their bank’s mobile app. In keeping mobile banking performance up, innovations can identify the key areas of improvement.

Every day there are great strides made in adapting to customer behaviour and meet the ever-increasing demands of customers. Innovations such as artificial intelligence (AI), analytics, blockchain, big data, and machine learning are at the forefront of automating the processes. There is a lot of competition in the field, and the only way to stay relevant is by delivering an excellent human experience.

Here are a couple of ways of improving the human experience by delivering excellent mobile banking quality:

Customer Focus and Personalization

Personalization can help users have control of their financial positions even at the most basic level. Even though banks are looking to reduce their operational costs with mobile banking, their efforts should be customer-focused. Mobile banking benchmarking can help get a view of their present position and how to close the gap. Understanding what the customers want is a big part of this and fully understanding how to deliver it to different demographics.

Users love having control of what they see and what they can do in their mobile banking apps. Machine learning is a key component of this process, and its development in the banking sector has opened up a lot of doors for adaptability. Machine learning techniques can help banks target people based on demographics and give them their preferred options for customizing their mobile banking use.

Mobile banking should have increased use of analytics and data to determine how their customers interact with apps. Banks can use this information to optimize their services and deliver excellent mobile banking quality that will satisfy customers. This personalization can go beyond the look and services to include budgeting tools, appointment scheduling, and financial advisors for investment pointers.

Automated Analytics

Remove Pain Points in the Experience

The entire customer journey should be a smooth and easy experience. Any wrinkle or challenge along the customer’s journey in transacting with the bank can cast a dim light on the entire experience. From logging in to account information access and management, banks should streamline the whole process. Fingerprint login, quick navigation, easy transfers, and quick access to account information are paramount.

If allowances on your app allow users to perform actions that they would normally need to visit a branch location, this greatly improves the customer experience. That convenience you deliver to the customer will be integral in keeping them and your overall mobile banking performance. This reduces in-person visits at bank branches to only important ones, which helps reduce these banks’ operational costs.

The goal should be to develop an end-to-end experience without any hiccups from start to finish. This will help you stand out in the digital banking industry. A good model to examine is digital-only banks as they are successful in attracting customers with simple and transparent offerings. Simplicity is the key to reducing support calls for resolving issues. Cut down on the scrolling users and include search bars with natural language filters and commands.

Customer Feedback

Customer voice is the trump card…

The adaptation of mobile technology also means developing new challenges and obstacles to overcome in perfecting the process. Constant adaptation and keeping a tap on customer’s needs are the keys to keeping a close connection with customers. This is where customer reviews play a large role in cementing that relationship and keeping the customers happy.

Quality customer service is truly determined by anticipating the customer’s needs and giving them those services before they even request them. This calls for tools to help monitor trends, consumer requests, and actionable data on the industry so they can remain at the forefront of the pack. More than ever, with the increasing population in the space, users are looking for mobile banking apps that push the boundaries and deliver better mobile banking quality than others.

Swift customer service tools on banking apps make for their users’ pleasant experience and ensure their loyalty. Banks should conduct periodic assessments of their mobile apps by analyzing their customer’s views and reviews. The information sources for such assessment can be both internal systems of records such as CRM, Customer Service feedback tools, Chat bots and external sources like playstore reviews, google reviews etc. These sources of data have to be thoroughly analyzed to draw out interferences that can help you in improvising the quality of your mobile banking application.

customer lens

Conclusion

Delivering a consistent and elevated human experience with great mobile quality is a continuous task. Innovations in technologies can do a much better job of keeping up with this process daily and delivering consistent mobile banking performance. A great analytic tool can push the boundaries and help apps key in on the important areas that need development and optimization.

Maveric’s DEEP (Digital Experience Enhancement Platform) solution closely evaluates customer experience quality and provides continuous improvement strategies that assure superior human experience (HX). It benchmarks your mobile application against industry peers and your toughest competition and advocates continuous improvement strategies.

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