hypotheses in product development
Introduction
Today we’ll talk about a cool thing – working with hypotheses in product development. It’s like we’re on a race track and our hypotheses are our strategic overtaking maneuvers that make our product outperform all competitors!
When you work on a product, there are always exciting questions: how to make it better? What needs to change to make users happy? This is where hypotheses come to the rescue! It’s like a puzzle that you solve to open up new possibilities and improve your product.
Let’s figure out why working with hypotheses is not just a joke, but a must-have in the world of product management. It’s like a tool that turns cloudy dreams into clear roadmaps to success!
When you rush to develop a product without well-formulated hypotheses, it’s like playing hide and seek in the dark – it’s unclear where to run and who to look for. Hypotheses are your flashlights in this darkness, helping you see the path to your goal.
Hypotheses are like the secret key to the treasures of effective product management. When you begin to formulate hypotheses, you are like an archaeologist exploring ancient ruins to find treasures. Each hypothesis is an opportunity to unlock the potential of a product, discover hidden user needs and build a development strategy.
So working with hypotheses is not just a guessing game. It is the art of asking the right questions about a product, analyzing data, and coming up with new hypotheses that will lead to innovation and success. Believe me, when you master this art, your product will become a real star in the business horizon!
What is a hypothesis?
What is a hypothesis in the world of product development?
Let’s figure out what a hypothesis is when it comes to developing a fire product. A hypothesis is like the chief detective of your project, which helps to reveal the secrets of user behavior, find the causes of problems and propose solutions so that the product is not just better, but explodes the market!
Let’s take a simple example. Imagine you have a pizza delivery app. You assume that increasing the size of the “Order” button will lead to an increase in the number of orders. So, this is a hypothesis! You assume that change X (making the button bigger) will lead to result Y (more orders).
Or another example, let’s say you’ve decided to improve the filtering of products in an online store so that users can quickly find what they need. Your hypothesis might sound like this: “The introduction of a new filtering system by price and brand will increase purchase conversion.”
Now, a hypothesis in product development is not just a guess or an idea, it is a data-based guess about what changes will lead to the desired results. It’s like a map that helps you find treasures in the ocean of user needs and turn your product into a real diamond!
So don’t be afraid to formulate hypotheses, test them through testing and data analysis – and you will definitely achieve success in the development of your product!
Hypothesis vs. The usual statement: we understand the subtleties
Okay, buddy, let me explain to you the difference between a hypothesis and an ordinary statement so that both you and your grandmother can understand at once!
Look, a common statement is something like, “My cat loves milk.” Well, just a fact that seems obvious. But when it comes to a hypothesis, it’s like a weather forecast: “If today is a sunny day, then my cat will be more fun.” There is already an assumption and some kind of connection between the two phenomena.
Well, okay, let’s use clear examples so that everything falls into place.
Statement: “My grandmother loves to knit sweaters.” It’s like a fact of life that just happens.
Here’s a hypothesis: “If I help my grandmother with household chores every day, she will be happier.” There is already an assumption here that active participation will lead to the grandmother’s happiness.
So, do you understand the difference? A hypothesis is like an attempt to predict, explain the relationship between phenomena, and a statement is simply information about something. And remember, in order to develop a product like a boss, you need to be able to formulate cool hypotheses and test them in practice!
Why formulate hypotheses when developing a product?
Imagine that you have an idea for an app that will help people get news faster and more conveniently. You can formulate a hypothesis that if you add a notification function about important events, then users will use the application more often. This is your working hypothesis!
And that’s why this is so super important. Hypotheses help us understand what changes to make in a product to make it even cooler. They help us test our assumptions and adapt our product strategy on the fly.
Moreover, with hypotheses we can save time and money because by testing them early in development, we can identify potential problems and fix them before launching the product to market.
The process of formulating hypotheses
Step 1: Identify key issues or opportunities that require testing
Identification of major problems or opportunities. Think of it as finding treasure in the business world. You need to unearth key problems or potential opportunities that will form the basis for your hypotheses.
For example, imagine you’re working on a fitness app and users complain that the interface is too complicated. Here the problem has already been highlighted and all you have to do is formulate a hypothesis and test it!
The best way to do this is through data collection. Get into the spirit of detective and start scouring user data, analytics, reviews and more. Remember that everything must be based on facts so that your hypothesis does not turn out to be just fiction.
And now, when you identify your goals and problems, you can already formulate a hypothesis. It must be specific, measurable and have an intended outcome. For example, “Simplifying the application interface will increase usability and the time users spend in it.”
Step 2: Hypothesis Formulation: How to Structure Your Hypothesis
Definition – Let’s start with a clear formulation of the hypothesis. Imagine that you are developing a financial management application. Your hypothesis might sound like this: “Introducing notifications about upcoming payments will increase user engagement and reduce the number of late payments.”
Measurability – next step: determine how you will measure the success of the hypothesis. For example, you can use the metric of increased user activity after implementing notifications.
Hypothesis vs. Target – remember that the hypothesis is not the goal! A hypothesis is an assumption about the results of a change that you can test. A goal is the end result you strive for.
Alternatives and Limitations – do not forget to consider alternative scenarios and possible limitations. For example, the presence of other factors that may affect success rates.
Examination – the fun begins after formulating a hypothesis! Run an experiment, collect data and analyze the results. If the hypothesis is not confirmed, this is also valuable experience for future research.
Step 3: Define key metrics and experiments to test the hypothesis
Before we dive into the world of hypothesis testing for product development, let’s talk about how to define key metrics and create experiments to test them. Imagine that you are in front of a door of opportunity, behind which are hidden the answers to questions about what will make your product even better. Ready to take on the challenge?
The first thing to do is determine how to measure the success of the product change. These key metrics should be specific, measurable, and related to the product’s goals. For example, if your hypothesis is to improve user engagement, a key metric might be conversion from the home page to the registration page.
For example:
Hypothesis: Adding video product reviews will increase conversion on the product page.
Key metric: Increased time spent on the product page.
Now that you have key metrics, it’s time to use your imagination and create experiments to test your hypothesis. Experiments must be structured, controlled, and capable of producing a clear result about whether the hypothesis worked or not.
For example:
Hypothesis: Simplifying the checkout process will increase purchase conversion.
Experiment: Dividing users into two groups – one to offer a simplified registration process, the other to use the usual one. Measure the conversion of purchases in each group.
Typical mistakes when working with hypotheses
Vague Hypotheses: Why It’s Important to Be Specific
My friends, let’s talk about why in the world of formulating product development hypotheses, it’s more important than ever to be specific. Imagine: you are solving a riddle, but instead of clear directions, you are surrounded by an abundance of mysterious paths. It seems interesting, but where to go and what to do? It’s the same with vague hypotheses – they create confusion and can lead us nowhere.
When we formulate a vague hypothesis, we are playing the lottery with our product. We give it a chance to succeed, but without a clear plan it’s more luck than strategy. When you know exactly where to go, you confidently step forward, rather than wandering in the dark.
For example:
Vague Hypothesis: “Improving the interface will increase user satisfaction.”
This hypothesis leaves a lot of questions: what exactly should be improved in the interface? What specific changes will lead to increased satisfaction?
To make your hypothesis clear and specific, it is worth asking yourself a series of questions. What exactly do we want to change? How will this change affect users? How do we measure the effect? Let us be careful architects, building dreams from the bricks under our feet, and not explorers without a map in a land of unknown possibilities.
For example:
Specific hypothesis: “Increasing the size and contrast of the ‘Order’ button on a product page will increase conversions by 20% per month.”
Now look at this hypothesis – it is precise, measurable, and clearly defines the goal.
Ill-conceived experiments: how to avoid wasting resources
Hey friends, let’s talk about how we, as product creators, can avoid the pitfalls of ill-conceived experiments that can lead to wasted time, money, and stress. Imagine going on a trip but not knowing where to go or how to get there. It’s like wandering aimlessly in an ocean of possibilities. Let’s figure out how to be more purposeful!
When we neglect to carefully design experiments, we risk wasting resources. Ill-conceived experiments often turn out to be wasteful wastes of the evergreen garden of new ideas. We may end up in a situation where a lot of effort has been put in, but the result is not what we expected.
For example:
Ill-conceived experiment: Changing the color of the “Buy” button to a random rainbow color without analyzing the data.
Result: No change in conversion or, worse, a decrease.
How to avoid wasting resources?
To avoid this pitfall, you need to carefully consider each experiment before you run it. Set clear goals, define expected results, highlight key metrics to measure success. Be like detectives who draw up a detailed plan of action before starting an investigation.
For example:
Thoughtful experiment: Change the text on the “Try for free” button to “Start free and get access to all features for 7 days.”
Result: Increase in the number of users registered for the trial period.
Ignoring Data: Why It’s Important to Base Hypotheses on Evidence
Imagine that you are building a ship without taking into account a map of the sea – you can get lost in the ocean of possibilities. Let’s dive into the world of data and find out why it is our invaluable wealth!
Why base hypotheses on facts?
When we ignore data, we risk creating hypotheses based on assumptions and intuitions that may not be realistic. Data is our reliable compass in a world of change. They help us understand where to go, what paths to take, and how to avoid pitfalls.
For example:
Data-based hypothesis: “Increasing the number of product recommendations based on user preferences will increase the average purchase by 15%.”
This hypothesis is based on real consumer preferences, which makes it more likely to be successful.
To successfully work with hypotheses, you need to carefully analyze the data. Use information about user behavior, feedback, results of past experiments. Be like archaeologists, searching through the traces of the past to formulate hypotheses based on facts, not guesses.
For example:
Data-based hypothesis: “Reducing the number of steps before placing an order based on analysis of consumer behavior will increase conversion at the checkout stage.”
This hypothesis is based on specific data about user difficulties during the purchasing stage.
Tools for working with hypotheses
Popular online tools and platforms for formulating and testing hypotheses
Let’s look at a few popular online tools that will be your faithful companions in creating innovation and improving the user experience. Ready for an adventure? Let’s start!
1.Optimizely is a convenient A/B testing and personalization tool that allows you to test different versions of pages, design elements and product functionality.
Use case: You have created a hypothesis that changing the color of the Buy button will increase conversions. With Optimizely, you can easily set up an A/B test and compare which option actually attracts more customers.
2. Google Optimize is a free A/B testing tool from Google that helps you experiment with web pages and analyze their performance.
Use case: You want to test the hypothesis that changing the title on your home page will improve user retention. With Google Optimize, you can set up a test and track changes in user behavior.
3.Hotjar provides tools for analyzing user behavior on a website, including heat maps, session recordings and surveys.
Usage example: Let’s say you have a hypothesis that users don’t find the “Call us” button because it is invisible on the page. With Hotjar, you can analyze user behavior and confirm or refute your hypothesis.
Recommendations for choosing tools depending on the needs of the team
Choosing tools is like choosing a suit; it should suit you in both size and style. Let’s figure out how to determine which tool is right for your team!
For a team passionate about analytics and experimentation:
Recommendation: A/B testing tools like Optimizely or Google Optimize are great for those who are eager to test every hypothesis in the field and extract valuable data from every test.
Use case: Your online store team assumes that changing the order in which products are displayed on the home page will increase conversions. With Optimizely, you conduct an A/B test and find the best option.
For a team focused on user experience:
Recommendation: User behavior analysis tools like Hotjar can help you understand how users interact with your product and where problems arise.
Use case: Through Hotjar, your team discovers that most users do not scroll to the bottom of the service description page. This becomes the basis for the hypothesis about the need for brevity and clarity of the text.
For a team focusing on design and visual experience:
Recommendation: Prototyping and design tools like Figma or Adobe XD can be a great choice for teams working to improve user experience.
Use case: After receiving feedback from users that the site is difficult to navigate, your team uses Figma to create a new prototype with improved structure and navigation.
Summing up: why correct work with hypotheses is the key to successful product development
Imagine that we meet at the top of the innovation mountain, where we turn around and look at the path through the whirlwind of testing and research. Why is good hypothesis work the key to success in the product world?
Imagine that hypotheses are stones that you lay down as you walk along the smooth path of product development. If you put them away for future use and wisely, they will become the basis of your success. Properly formulated hypotheses will help you understand what works, what doesn’t work, and in what direction to move.
Let’s say your development team assumes that improving page loading speed will increase user satisfaction. You formulate a hypothesis and conduct testing, the results of which show an increase in the average time on the site. This indicates that your hypothesis was correct and further development in this direction makes sense.
Hypotheses are not just assumptions, but they are also powerful tools that help a team stay on the same page, move forward, and achieve success. Correct work with hypotheses allows you to reduce risks, speed up the product development process and achieve greater focus.
For example:
A marketing team decides to test the hypothesis that changing the headline in their weekly newsletters will lead to an increase in email opens. After conducting A/B testing, they find out that the new headline actually attracts more attention from users.
So, dear friends, hypotheses are your guide in the world of endless possibilities for developing and improving a product. Remember that careful work, patience and data analysis will help you discover new horizons and bring your wildest ideas to life. Let your product development path be strewn with valuable hypotheses and successful solutions!
An invitation to further study the topic and implement best practices in your activities
It’s time for the final act of our exciting journey into the world of formulating product development hypotheses. We explored, experimented, learned from our mistakes and gained valuable experience. But this is just the beginning of our journey! Friends, I want to invite you to further immerse yourself in the topic and implement best practices in your daily activities.
Hypotheses are only a small part of a wide range of product management tools. Explore, go deeper, master new techniques and approaches. Study successful cases and analyze mistakes. Always remain in search of new knowledge and ideas!
Apply the acquired knowledge in practice. Don’t stop there, but become a master of the subtle art of formulating and testing hypotheses. Incorporate best practices into your professional repertoire and share them with colleagues.
Imagine that your development team has come to the conclusion that improving the user interface of an application will make it more intuitive. You conduct additional research, formulate a hypothesis, and successfully implement changes in practice. As a result, user satisfaction increases and you learn valuable lessons for future projects.
Friends, the world of hypotheses is endless and full of possibilities. Introduce new ideas, learn, test and grow. May your path to success be littered with experiments and successful decisions. Don’t be afraid to take risks and strive for excellence in every project you put your mind to. I invite you to continue this exciting path and apply the best practices in your activities!
