An M VP is the ultimate app validation tool and the best way to test your idea in the real world.
If you use AI when building it, you’ll improve it and get it to market faster.
And speed is key when building one for your app.
That’s why we’ll discuss 6 ways you can use AI when building your app MVP.
Let’s dive in!
Market research is key if you want your MVP to succeed.
And using AI for market research when building your MVP can help you get data-driven insights faster .
Researchers agree with that, too.
According to a Qualtrics report , 93% of researchers see AI as an industry opportunity and 80% think it will have a positive impact on the market research industry.
But, why is market research so important?
The main reason is because it will show you if there’s a market need for your product .
And according to CB Insights , having no market need for their product is one of the top reasons why startups fail.
source: CB Insights
If you do thorough market research, you’ll see if your app idea is worth pursuing or if you need to pivot.
And with AI, you can speed up the process and get those insights faster.
Now, let’s discuss some ways you can use AI for market research.
How you can use AI for market research
One of AI’s strong points is analyzing vast amounts of data in a short period of time.
And when you do market research, you end up with a lot of data to analyze.
A good use case for AI in market research is sentiment analysis .
If you’re doing it right, you’ll be engaging with your target audience during your research process.
And you’ll end up with a lot of diverse data from various sources like:
With AI sentiment analysis, you’ll be able to analyze the feedback you get from all of these sources in minutes.
This will save you a lot of time and help speed up your MVP development.
Tools like Lexalytics’ Semantria and Stravito are good choices.
Another good use case for AI is competitive analysis
source: QuickBooks
You can use tools like Determ and Lebesgue to help you do it.
They will help you react quickly to any changes in the market and stay ahead of your competition.
The key to a successful MVP is getting your product to the market quickly .
And if you use AI when building your app MVP, you’ll be able to launch it even faster.
That can be the key to your app’s success.
Getting to market first with a new solution will help you establish brand authority and give you an edge over your competitors.
You’ll be talking with our technology experts.
Also, speeding up your app MVP development with AI will help you both save and earn money .
You’ll have a shorter development timeline and that will reduce your costs.
On top of that, the sooner you get your app on the market, the sooner it will start generating revenue.
And that can be key if you’re operating on a tight budget.
Let’s discuss specific ways you can use AI to speed up MVP development.
How you can use AI to speed up MVP development
A good way you can use AI to speed up building your app MVP is by using it to automate your engineers’ repetitive tasks .
This will increase their productivity and give them time to focus on solving more complex problems.
Coding assistants like Github Copilot and Tabnine are good choices for that task.
They automate the creation of boilerplate code and give intelligent code suggestions – this can significantly speed up development time .
The engineers who use them agree that AI coding assistant increases their productivity and efficiency, as this survey of Github Copilot users shows:
source: Github Blog
Also, you can use AI to help you quickly write your requirements document
A requirements document is crucial for your MVP’s success.
Using AI tools like Metastory and UserTale will help you write them in minutes.
And we’ve barely scratched the surface.
You can also use AI tools to help speed up app design and prototyping.
And that’s the beauty of AI – the (almost) endless possibilities.
We’ve already mentioned that AI excels in analyzing vast amounts of data in a short period of time.
That’s why it should be a no-brainer to use AI for data analytics when building your app MVP.
And there’s another good reason for that, too.
McKinsey’s research has shown that data-driven organizations are:
23 times more likely to get customers
6 times more likely to retain customers
19 times more likely to be profitable
These numbers show just how important good data analytics is in general, not just when building your MVP.
And AI can help you take your data analysis to the next level.
With it, you’ll get data-driven insights faster.
And that will save you time and money and get your MVP to market faster .
Now, let’s discuss some specific use cases of AI for data analytics.
How you can use AI for data analytics
A good way you can use AI for data analytics when building your MVP is for real-time user behavior tracking and analysis.
And you’ll get results, too.
Gallup’s research shows that companies that use user behavior insights outperform their competition by 85% in sales growth and 25% in gross margin.
AI tools like Qualetics and Whatfix are solid choices for this task.
source: Crozdesk
Another way you can use AI data analytics is for forecasting and trend analysis .
This will be especially important once you’ve launched your MVP.
AI can analyze current trends and make predictions about:
User engagement
Growth rates
Revenue potential
This data will be invaluable for your future marketing strategies and feature rollouts and it will help you make data-driven decisions.
And that’s what AI data analytics is all about.
Improving your app’s user experience (UX) is one of the best ways you can use AI when building your app MVP.
And just because you’re building an MVP, that doesn’t mean you can ignore UX.
On the contrary, a good UX is key to your app’s success .
And investing in it yields great results, too.
For every dollar invested in UX, you get $100 in return – that’s an ROI of 9,900%.
source: Adam Fard
That’s a very compelling reason to invest as much as possible in improving your MVP’s UX.
And AI can help you take it to the next level.
Let’s go over some of the ways you can use it for that task.
How you can use AI to improve your MVP’s user experience
One way you can use AI to improve your app MVP’s UX is by improving your app’s user onboarding experience.
App onboarding is one of the most important steps in your users’ journey .
It tells your users everything they need to know about your app and its features.
If your MVP has bad user onboarding, it will turn off a large number of potential users.
And AI can help you tailor it to each users’ preferences.
A good example of this are Duolingo’s placement tests .
source: Duolingo Blog
They customize their lessons based on users’ performance in the placement test, ensuring that they’re tailored to their skill level.
Another good way you can use AI to improve your MVP’s UX is by improving its security .
AI cybersecurity tools like Darktrace ’s Enterprise Immune System and Crowdstrike’s Falcon are good choices.
They will improve your MVP’s security and help you counter threats in real-time.
In turn, this leads to a better UX because your users will know that their information is safe from threat.
And a better UX is exactly what you need in your MVP.
Personalization is the name of the game in today’s market.
Using AI when building your MVP will help you do it at scale .
And your users want personalization and the stats prove it.
Hubspot’s research shows that personalized call-to-actions (CTAs) perform 202% better than basic CTAs.
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And a Twilio Segment report showed that 56% of customers say they will become repeat customers after a personalized experience.
Your competitors are likely using AI for personalization, too.
Twilio’s report also showed that 92% of businesses
That’s why you can’t afford to ignore it.
Now, let’s discuss some specific ways you can use AI personalization in your MVP.
How you can use AI to add personalization to your MVP
There are a number of ways you can use AI to personalize your MVP.
Which one you choose will depend on your specific business needs.
But, a simple and low-cost option is integrating an AI chatbot .
You can add a customer service chatbot that will help solve the most common problems your users might have with your app.
Another innovative way you can use an AI chatbot is using it as a learning tool for your users.
This is particularly useful if you’ve got an educational app.
Another good way you can personalize your MVP is by adding an AI-powered recommendation system .
This is a great option if you’re building an e-commerce app.
Of course, building one from scratch is too expensive and time-consuming if you’re developing an MVP.
Luckily, Amazon offers their recommendation engine as an API you can integrate into your app through Amazon Personalize .
source: AWS
And the best thing about it?
It’s got a proven track record – McKinsey estimates that it’s responsible for generating 35% of Amazon’s yearly revenue.
Considering their revenue was $514 billion in 2022, that means that their recommendation is responsible for 180$ billion of their revenue.
That’s a pretty compelling reason to go with AI personalization.
Would you ever use an app littered with bugs?
Of course you wouldn’t. Your users wouldn’t, either.
That’s why testing and quality assurance (QA ) are so important and you can use AI to make your QA engineers more efficient when building your app MVP.
source: LiveAbout
They’re essential processes without which your MVP won’t succeed.
And with AI, you’ll be able to get them done faster without sacrificing quality.
The main advantage of automating testing and QA is that automated testing can run 24/7.
This means that your QA engineers will be notified immediately after a bug happens.
And that’s just a few reasons why it’s a good idea to use AI to automate your testing and QA processes.
Now, let’s talk about exactly how you can do it.
How you can use AI to automate testing and quality assurance
One way AI can automate testing and QA is by automating various testing methods .
Some testing methods you can automate are:
Unit testing
Integration testing
Regression testing
Performance testing
AI will be able to identify test scenarios, make test scripts and then run them without human intervention.
Tools like TestCraft and TestSigma are good choices for this task.
source: TestSigma
Also, you can use AI code review tools to analyze your codebase .
They’ll be able to find potential bugs and code that can be optimized for better performance.
And a bug-free, well-performing app MVP will have a much better chance of success.
Using AI when building your app MVP should be a no-brainer.
AI will not only help you get it on the market faster, but it will also improve it.
And you can use it in a number of ways during your MVP’s development.
If you want to learn more, check out our other articles on MVP development and get in touch with us if you need an MVP.
