The world we live in is far from being idle. Technologies and industries evolve rapidly, with maddening speed at times. When Nomtek was founded in 2010, Apple was selling the iPhone 3G. It was the company’s second iPhone and the first to use the 3G network.
We hopped right in, to participate in the development of the mobile world.
3 megabits per second — that’s the dizzying speed 3G promised. Sounds bleak compared to 100 megabits per second possible with 5G. But that’s how fast mobile life was spinning back then.
The Android ecosystem itself was also in its early stages. In October 2009, Android Eclair (2.3) was released, with Motorola Droid reigning as the most popular mobile phone.
By today’s standards, it was a strange-looking smartphone, with a hidden keyboard at that.
So What Do We Have Now? The State of Technology
Much and more has changed since Motorola Droid’s reign over ten years ago. IT systems have become denser, more complex, and more accessible.
Take a Japanese farmer who, in 2016, created a system that uses AI to classify cucumbers. Sophisticated technology such as deep learning has become increasingly present in areas commonly associated with manual labor.
3G was soon replaced by 4G in developed countries, dramatically improving network connectivity and changing how people consume content. 4G helped Netflix conquer the world of streaming services, giving users access to favorite films and series at home or on the go.
Chasing the Bandwagon of the Future
All these new connectivity technologies, more efficient chips, and the evolution of augmented and virtual reality can cause a reverberating wave of changes for industries and people across the globe.
At nomtek, we always knew that investing in our development was the best thing we could make, hence the idea for nomtek labs — our answer to the rapidly evolving world.
As a company made of people who relish discovering innovation, we don’t intend to stand behind or rely solely on old technologies and methodologies.
We are tech enthusiasts who love exploring new sectors and playing with technology.
At nomtek, everyone can participate in a number of initiatives that boost knowledge and develop skills. We have internal weekly guild meetings, free time for self-development, and budget for workshops and conferences.
Artificial intelligence is one of the most inspiring innovations of the last five decades. The technology has transformed the way we play music, shop, and work. Mobile apps have also enjoyed the features AI offers by boosting personalized recommendations, powering chatbots, and introducing automation. Learn how else you can use artificial intelligence in mobile apps.
What Is AI and How It Works?
Artificial intelligence is exactly what you imagine it to be — machines mimicking human intelligence. AI uses machine learning (ML), natural language processing (NLP), and deep learning (DL) technologies to build algorithms that have reasoning and decision-making capabilities.
AI allows companies to process high volumes of data quickly and derive valuable insights. Companies use these data-backed insights to improve capabilities, get more productive, and grow faster.
AI makes mobile apps capable of making decisions and solving problems. User satisfaction improves when they get what they’re looking for, with AI helping in the background. Satisfied users lead to higher app retention rates and Net Promoter Score (NPS).
Companies use AI to build powerful recommendation engines within mobile apps. Recommendation engines analyze past user actions and offer relevant suggestions for the future.
Netflix uses AI to analyze what viewers like and suggest the next movie that matches their preferences. Amazon tracks shopping behavior and recommends more products customers are likely to buy.
AI can analyze data faster than a human and uncover prevailing trends. This helps apps know users better, provide contextual recommendations, and boost engagement rates.
AI simplifies pattern analysis to create more personalized app sessions. Startups can use deep learning and sentiment analysis to enhance the user experience.
For example, AI can help understand why a user abandons an app. Google Analytics or CleverTap (an app analytics tool that uses AI to track user sessions) analyzes touch heatmaps and discovers navigation paths within mobile apps. AI-based analytics help adjust the app to user expectations.
A minimum viable product (MVP) is a way to bring your product into the market quickly, without risking too much time or money on developing features that might be redundant. But building an MVP in its most commonly understood meaning (a working version of your mobile application) isn’t the only approach to validating your ideas and probing market demand.
Just like there are many factors to consider when creating the foundation for your digital product, there are many types of MVPs. Context, competition, offer, business model, business objectives, and many other elements determine the best types of MVPs for your project. That’s why there’s no single minimum viable product template that will be accurate for all mobile app projects.
One thing remains 100% sure, though: the necessity to validate your product ideas if you want to succeed. According to a Harvard professor, 65% of startups fail. And the reason for failure is simple — poor and untested product ideas.
What Are the Different Types of MVPs?
Building a minimum viable product is the first step when launching any new project, but there are many different ways to approach an MVP.
Wizard of Oz
Also known as the Flintstone MVP, a Wizard of Oz is a product that doesn’t yet exist but makes an illusion of being a completely functional product. Even though it seems complete on the outside — just like the Flintstone car — there actually isn’t any software present on the inside to do the work.
In fact, all work, e.g., in-app actions are done manually by a developer. Zappos, the online shoe retailer, was built with a Wizard of Oz strategy. In 1999, Nick Swinmurn, the founder of Zappos, searched for a pair of shoes but couldn’t find them in a nearby mall. He discovered that none of the major companies sold footwear online. Soon, he built a simple website and started taking pictures of shoes from stores all over and placing them on his website — no inventory system present whatsoever.
Yes, Nick Swinmurn was doing everything manually, which meant running to the store to fulfill an order that came through the website. Once the sales became significant, he knew it was the right time to invest more money, and that the business would take off.
A Wizard of Oz test can be time-consuming, but it's an excellent option for entrepreneurs looking to validate their product or service before investing large funds.
A single-feature product
When Spotify founders were thinking about setting up their business, they noticed that other media streaming companies often went for expensive websites and apps, without really testing the viability of their products.
So instead of burning through all their funds on a fancy website or complex software development process prior to launch, they created an MVP in the form of a desktop application with music streaming as their core functionality to test the market need. However, their biggest focus was to bring down latency as much as possible, giving the experience no lag. The result? Spotify became the most significant music streaming company in the world.
So when creating a single-feature product, you need to understand that one functionality must work exceptionally well. After confirming that your product is viable, you can add more features as you learn the behaviors and preferences of your users.
The piecemeal MVP development framework relies on existing solutions to deliver a new service. For example, instead of building an entirely new content management system, you use solutions such as Wordpress. You don’t have to invest a lot of time and money to build a prototype or build a whole product from scratch in one go — you can assemble an MVP with existing tools.
This is exactly how Groupon was created, as an asset initially built on Wordpress. If the founders had insisted on building their own CMS first, the company might not have survived.
This approach allowed Groupon to quickly test the business idea with pet adopters, leveraging other software without spending too much money on expensive designs or complex functionality.
Concierge minimum viable product is similar to a Wizard of OZ test. With a concierge MVP, you also manually go through every step of the process with each customer. This gives you the opportunity to get feedback on your product or service and make any necessary adjustments to your product roadmap.
In the book Lean Startup by Eric Ries, Food on the Table is used as an excellent example of the concierge MVP. Food on the Table is an app that figures out what you like to eat based on the recipes you submit. The app then creates a shopping list using coupons to help users save money. To test out the idea, the founder personally collected coupons and compiled lists for each customer without any automation or a big team.
How Do You Build a Minimum Viable Product That Is Immediately Valuable?
To determine whether an MVP concept solves a problem, and therefore is immediately valuable, test whether it does the job.
The JTBD Theory
Jobs-to-be-done (JTBD) is a theory based on the premise that customers “hire” products or services as tools with which to complete tasks.
Even though an MVP can be very cheap, it’s not always free to make. Jobs-to-be-done is a powerful tool for measuring the potential of an idea before any investments whatsoever. It considers two things: what job customers would require your product to do and how well your new product satisfies unmet customer needs and pain points versus existing solutions.
A great example is Clay Christensen’s research for McDonald’s. During customer interviews, Christensen realized that people were “hiring” milkshakes because they're easy to consume with easy-to-dispose packaging and appetite-quenching qualities — perfect for those with time restrictions in the mornings. By understanding what was a milkshake’s job-to-be-done, Christensen’s team created a better milkshake, one that addressed the specific needs and wants of the customers.
You can measure hundreds of different metrics, but they will get you nowhere near making good product decisions. By picking a North Star metric, however, you can focus on what helps you build a foundation for data-based decisions that matter. A North Star (or master) metric will very quickly give you the answer to a basic question: is the product evolving according to your expectations, or not?
I’ll describe a simple framework that helps our clients find a master metric for building better products that reflect what users do and what decisions they make inside the app.
Organize a North Star Metric Meeting
Before the meeting
Invite stakeholders and at least one technically versed person. Mobile analytics requires experience and the terminology can sometimes overwhelm the stakeholders. Having someone who gets analytics and can translate complex terms into layman’s words is an asset.
Master metric meetings can be held remotely, so you can use Miro (or a similar tool) to organize thoughts.
During the meeting
#1. Set a goal
You start the meeting and set up a goal. In this case, it should be “looking for the master metric that currently matters.”
To better explain the goal, describe what is a good metric and what is a North Star metric if it’s not obvious to all people at the meeting (e.g., not every developer has experience in defining metrics, hence I recommended inviting someone versed in analytics to the meeting).
Definition of good, great, and North Star metrics
A good metric lets you measure the usage of a specific feature with direct value to the user.
However, the definition of usage itself can get tricky and deceitful if you don’t understand it correctly. For example, metrics such as the number of sign-ups or the total number of registered users aren’t really going to help you build a better product because they give you neither valuable nor actionable insight.
If you make metrics more granular, say, the number of new users per week or how many times a day/week a user opens your app, you can correlate the results with some other action (e.g., change in design, reduction of the number of steps in a process). In other words, you can get a learning opportunity.
Now the even more granular “percentage of users who do the same thing inside your app X number of times a day/week” is a metric that influences decision-making the most.
With all that in mind, a definition of a North Star metric emerges: every other metric you measure means nothing until this master metric hits a predefined goal.
The most important persona
Now that everyone is on the same page as to the qualitative aspect of metrics, we’re going to focus on bringing to light everything we know about the most important user persona in the current state of the product. Master KPI will refer to this group of people.
#3. Establish a process
Have your meeting attendees work together in a group to find a North Star metric. Set a time limit of ten minutes, for example. Every person works separately, without seeing the results until time runs up.
Use post-it notes in Miro for this step.
Don’t brainstorm here — it’s easy for extroverts to dominate brainstorming sessions. Introverts, too, have great ideas, but they won’t share them if they can’t be heard.
A key piece of advice in this step is to not think about any limitations — just write down what’s the master metric according to you.
When time is up, talk over your results.
When the master metric exercise is complete, all stakeholders should think about the limitations that make a certain metric unsuitable to become a master metric. The constraint can also be that the metric is simply unmeasurable.
Difficulty accessing necessary data
Once everyone has learned about the ideas of other team members and business constraints, we repeat the ideation process for the master metric.
The iteration should look like this:
come up with and share ideas
eliminate or modify all proposed metrics so that they don’t have business constraints and are technically plausible
The technical feasibility of a metric also justifies the presence of a technical person — a developer with the knowledge of analytics will be able to tell how difficult is the implementation of that idea or if it’s even possible.
This sifting process should be exhausted to the point of giving you a list of validated metrics.
There’s little room for democracy when voting for a master metric — one designated person has to be the decision-maker. Every stakeholder gets 2 to 3 dots to use for voting on the best master metric. Keep in mind that the number of dots a metric gets is only for the informational purpose of the decision-maker.
It will be up to that person to ultimately make the decision which metric becomes the master metric.
Sample Miro board with the whole process:
After the meeting
Remember that a North Star metric isn’t set in stone
A North Star metric is a way to focus on many different measuring options, which is great for successful product development that’s guided by predefined goals. But you have to keep in mind that a North Star metric is valid for a set period of time — once you achieve the predefined metric goal, you should find a new North Star metric to avoid the problem of local optimization. The key with North Star metrics is to find a global optimum. So without working on at least a few North Star metrics, your product might not mature properly.
Having a North Star metric is important, but it doesn’t mean that the one you pick initially should guide your product’s journey forever — there’s a high likelihood that that first North Star metric will change.
Don’t get too caught up in an accuracy frenzy
Don’t get discouraged by the results with the first North Star metric you define. Choosing that first metric is the most difficult part of the process. The data environment isn’t yet saturated enough for you to make highly accurate decisions — don’t worry about that, just pick the first metric that seems good and iterate to set the baseline for further measurements.
Set a target level for every North Star metric
Choosing a North Star metric is only one part of the process — the other is to assume what’s the satisfactory target level of that metric.
You can think about it as a kind of business gambling — you assume that a metric changes by X when you do Y. This approach is the quintessential element of scientific research and the foundation for making hypotheses and experiments.
If you don’t define a target level for your North Star metric, there’s a chance that its role in your product’s success will be blurred (you won’t know if it was the North Star metric that had a direct impact). And in a scenario where your product fails, you’ll try hard to rationalize it.
Thinking about how much you can squeeze out of a given metric before you actually start the implementation takes away the ability to rationalize post-factum.
Consider the Lean Analytics Cycle
You can use the Lean Analytics Cycle diagram to find and validate North Star metrics, plus transition from one metric to another:
Mobile apps are a great channel for businesses wanting to reach a larger audience. But designing apps with a positive user experience can be a daunting task. From understanding your audience to building the right features, many factors go into the design process. Here are the best practices that can help enhance your mobile app user experience (UX).
What Makes a Mobile App Successful?
With a mobile app, businesses can reach more customers and incentivize them to make a purchase. But not all companies are successful in their efforts to develop a mobile app that becomes a reliable revenue stream. A staggering 99% of consumer apps fail.
A number of elements make a successful app — idea validation, user personas, mobile analytics, and comprehensive marketing strategy, are just a few of the necessary building blocks that increase a mobile app’s chance on the market.
For many businesses, it can be difficult to maintain consistent customer experience during the mobile journey. This article outlines some of the best UX practices that'll improve user retention and satisfaction.
What Is UX in Mobile Apps?
Mobile UX describes how the design and performance of an app impact the user’s perception of a mobile application.
User personas are a fundamental part of the user experience (UX) design process. To ensure you’re delivering the best experience for your target audience, you should create user personas before developing a mobile app. One of the most common mistakes business owners make when building an app is they often assume they know what their customers want.
But the only way to learn what are the motivations and goals of your customers is through user research and the development of comprehensive user personas. Once you know who your target audience is, you’ll have enough validated data to guide your UX design decisions.
What Is a User Persona?
A user persona (or buyer or marketing persona) is a fictional, yet realistic, portrayal of the most important user group. Designers use them during the design and development process to implement solutions based on the understanding of what your customers want.
Step into the shoes of your target customers to understand user needs, motivations, and expectations. A solid understanding of your main user groups is the cornerstone to designing an efficient and useful app.
Why Do You Need a User Persona?
You need to know who your end user is and how they interact with your product to be able to create a relevant and engaging product. If you don't have an established target audience and know little about your consumers, chances are that much of your time and money spent on app development will go to waste.
When you build your app with personas in mind, you’re able to create personalized experiences that resonate with target users.
Improved retention rates (cited by 51% of respondents)
Increased lifetime value, due to repeat visits, personalized marketing, and the trust of the individual (cited by 45%)
Increased sales (cited by 41%)
Marketing personas are invaluable during the product design process. They are an inherent part of your mobile app marketing strategy, helping you communicate your vision and ensure that you deliver a consistent message across all of your communication channels.