Reasons to Master No-Code Machine Learning

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With no-code AI, it's easier than ever to make better decisions, faster.

Here’s a scenario: You’ve been watching the rapid rise of artificial intelligence over the years. You understand its importance and the value it would bring your team, and, ultimately, your business.  

You Google “learn machine learning,” or “machine learning tools for data science,” to get a basic idea of where (and how) to start, and are inundated with search results like this: 


A featured snippet that lists the steps to learn machine learning
That's a lot of steps...

Basically, you conclude very quickly it takes a lot of time, steps, and energy to learn the coding language of technical machine learning. 

And you’d be right. Mastering machine learning is incredibly hard and requires a hefty time investment. And, even if you do master machine learning, creating data models from scratch can take months, and that's on top of everything else you need to do. 

But machine learning doesn’t have to be reserved for technical programmers. Thanks to no-code machine learning platforms, analysts have the power of data predictions to help them move faster, which means they can help their business to think creatively and proactively without blowing the budget.

Here’s a list of reasons to master no-code machine learning.


Related Reading: How No-code Machine Learning Algorithms Work


Traditional ML vs the No-Code ML Process

The Traditional Machine Learning Process

Before we dive into all the reasons why you need no-code tools for your business, it’s helpful to understand the differences between traditional and no-code machine learning. 

When searching for how to approach the machine learning process you may come across this post (or a post like it) and get 5-10 steps on how to collect data, build a model, train it, improve it, etc. 

Typically, the traditional model looks like this:


The typical traditional machine learning process.
The traditional machine learning process looks overwhelming.

And the language used to walk through the process typically looks and feels overly technical, which would understandably leave anyone who isn’t fluent in programming or data science feeling overwhelmed.

The No-Code Machine Learning Process

No-code ML simplifies this process into this: 


The no-code machine learning process
The no-code machine learning process is a lot easier.

This is a much simpler route for someone looking to make data predictions for their team who doesn’t have the time to master the technical skills or understands the value machine learning brings but can’t afford it. 

The best no-code machine learning platforms provide easy drag and drop data predictions, so you can simply edit your queries by replacing identifier and prediction columns and setting aside columns you don't want to use.

The best part? This shorter process has also reduced the amount of time to create a prediction. From months to seconds. So you can quickly predict metrics like churn, loan-to-value, the tenure of a contract, and so much more.

Benefits of No-code Machine Learning 

Now that we’ve seen the differences, let’s explore the reasons why mastering no-code machine learning will benefit your and your team.

1. Become data-driven without a data science team

Most companies that want to be data-driven don’t often have a data science team, cannot scale one, or aren’t aware of data scientist tools available to them. In fact, 83% of businesses say that AI is a strategic priority but struggle to find the data science talent.

This creates roadblocks, as what often happens is companies struggle to find the talent, or need to shift around budget to offer a competitive salary to in-demand data scientists. 

The high demand for model-building would also create bottlenecks for analytics in their day-to-day work. 

Another common issue is teams turn to their business analysts to try and tackle predictive analytics. And, as you’ve seen earlier, without the technical background, anyone without a data science background walking into building data models will ultimately feel overwhelmed and underqualified, which doesn’t make for high morale. 

But with a no-code machine learning tool, teams like yours have a great alternative and provide results in seconds rather than days/weeks.


No-code machine learning
No-code machine learning gives you the power to make predictions instantly.

2. Create machine learning-driven products and scale them

Customers want personalization, efficiency, and content and product curation. To do that, products need data input and output that appeals to the user’s needs. 

The problem is, while most businesses may have the fuel to build these products, if they aren’t leveraging the speed and accuracy of no-code machine learning, they fall behind competitors who use predictions to:

  • Make informed decisions about their product
  • Reduce time to market
  • Deliver one-to-one experiences
  • Improve UX

Machine-based learning personalization provides a more scalable way to deliver the kinds of unique experiences your customers and prospective customers expect.

3. Eliminate costs while improving profit

No-code machine learning can also help you increase profit opportunities. 

For instance, take dynamic pricing, a way to base prices on current market conditions. Uber does it. Airbnb does it. Airlines do it too. Basically, anything that has rising and falling prices is probably using a dynamic pricing method.

By plugging your historical pricing data into machine learning algorithms, you can predict how much a customer is willing to pay at certain times. Which is great if you have a lot of daily transactions between customers. 

You can also use historical data to make predictions on where to cut costs, where to invest time and capital, and where to improve customer retention. 

Tectonic London, for instance, leveraged no-code predictions in their app development to answer questions like "Which tourists spend more money when they visit the UK?". The team learned that the more times a tourist visits London, but not necessarily stays overnight, the more likely they are to spend.


A graph showing dynamic pricing
Using historical data, Tectonic London understood where to focus time and attention.

See how Tectonic London used no-code predictions in their app development to understand where to invest their time and capital. 

4. Improve decision-making

Often, companies rely on reporting, business intelligence, or ad-hoc data analytics using spreadsheets to draw insight based on historical data available at a point in time. 

And while there’s nothing inherently wrong with this method, the challenge is this process is creates roadblocks, as it’s:

  • Resource-intensive
  • Data can be stale
  • Prone to human error
  • Reduces time to decision-making

Machine learning-powered teams can work off of live, up to date information, which means they’re making informed decisions. And, if using a no-code machine learning platform like yours truly, they’re making those decisions quickly, accurately, and scaling their efforts.


Use Cases With No-Code Data Predictions

The power of no-code machine learning opens up so many possibilities, for businesses of all sizes. We’re seeing one of the most transformative technologies democratize data. No-code machine learning empowers teams of any skill-level to think creatively about how their data can drive or optimize their work.

Of course, for those just starting out on the no-code path, it can be daunting to know where to start. Sometimes, it makes good sense to deploy predictive analytics in areas where you can see quick wins, like churn prediction

After that, you could branch out with lead conversion. Your sales team likely has thousands of leads, but needs help deciding which ones to chase down. No-code machine learning algorithms can predict which of those leads have the most propensity to convert. Conversion models determine the likely revenue each individual customer will generate over the entire relationship and time it takes to convert them. Allowing sales reps to focus their efforts on those likely to be most revenue generating eventually closing deals faster.

Want to see more? We have a full library of case studies, from credit risk scoring to accident severity. 

Want to explore a use case in person? Tell us what you want to predict!

No-Code Machine Learning is Fast, Simple and Economic

As you can see, the no-code machine learning process is much shorter and simpler than the traditional process which also requires the learning of technical skills. With a no-code machine learning platform, you can do all of the same things—except without the expensive team of data scientists and improve business and product decisions quicker. 

Most importantly, no-code machine learning allows you to be more creative with your data. And with a tool like Obviously AI, you can become a data-driven company without having a data science team or scaling one. 

The no-code space is growing. It’s important to understand how different platforms compare against one another, especially when making decisions for your business. Read our blog post to see how our no-code machine learning process stacks up against Google ML’s own “no-code” process.

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