The Ultimate Guide to Product Experimentation Framework — with Alexandra Ciobotaru from Novorésumé
Do you use data-driven product-led experiments in your company or you’re more into using trial and error to see the outcome of your efforts?
If you’re among the second group, then you’re missing a lot.
Some quick stats for you:
- The SaaS sector is growing at a breakneck speed and there is intense competition between companies.
- According to Forbes, the SaaS industry will be worth around $370 billion by 2024.
With that being said, businesses should always be in the process of running product-led growth experiments to reduce risks and make the product meet customer requirements in this highly saturated market. If you’re still unsure whether you need to switch to a product experiment approach for your business then stay with us.
Let’s dive deep into product experimentation tactics and uncover why implementing and using such a framework can be game-changing for your product growth.
What is a product experimentation framework?
Product experimentation framework is a set of structured ideas that are collected to be tested and used for measuring the impact of the products for continuous improvement.
Benefits of using product experiments
By running product experiments businesses can test their hypotheses before the launch of the product. But product experiments work even after product release as this is a continuous job.
This is useful for both small, medium, and big companies, as detecting the wrong ideas, and reacting to them accordingly is equally important to all businesses, no matter their industry, product specifications, the number of employees, etc.
Product experiments are easy to review and understand. They are a strong ground for maximizing the learning opportunity especially for those who have doubts about whether their product is a good fit in the market and a good choice for customers.
Maybe you think that your idea is great but it’s something that your users may not use. So it’s better to face the risks and minimize the wasted time on building the wrong features.
Experiments help you see the light at the end of the tunnel.
If the result is successful, it is a clear sign that you should put more effort into delivering your idea.
Another benefit is that you can always see the real-time progress and collect valuable insights to map out your next steps.
Step-by-step guide to product experimentation framework
Typically a product experimentation framework follows these 5 simple steps and completing each step thoroughly is crucial to its overall success.
- Create goals — clearly define what you want to achieve and generate ideas.
- Use KPIs for measurement — select key metrics so you can measure the outcome of the experiment.
- Select your audience — Select the segment of your audience that will be impacted by the experiment and why.
- Uncover the areas of improvement — Identify the weakest points of your product and see what solutions could exist.
- Answer the WHYs — Collect data and make data-driven decisions.
Now let’s see what each step means and how to do it right.
Step #1 — Create goals
Having a clearly defined and measurable goal is a must for any product marketing initiative as any strategy should start with a goal. You can generate many ideas and try to realize them but remember that companies have limited time and resources. Prioritize your goals by identifying the problems that you think can be fixed.
Ask yourself: “What problems do you have? How are you going to solve them? What solutions do you have and which ones are the most realistic?”
Ok. You identified your problems and created goals but let’s now listen to your customers. Try to gather their feedback, define problems from their perspectives and ask them how those problems can be solved from their understanding. Having clearly defined problems and setting goals helps you keep all your team members, stakeholders and customers aligned. In this way, you can deal with any problems and conflicts earlier.
Step #2 — Use KPIs for measurement
After defining goals it’s time to decide how we are going to measure them.
At this stage, it’s important to understand how we will know if we have achieved it. For that, we’ll need to choose the key metrics that we’re gonna track.
For realistic results, it’s better to stick with 2–3 key metrics per experiment but you can do multiple experiment tests per KPI.
Additionally, you’ll need to have primary success criteria, which is the most important metric to define success.
Run In-product growth experiments to optimize the key metrics and run A/B tests to see what are the most important KPIs of your user journey such as user activation, trial-to-paid conversion, retention, etc. You can design and create product experiments without coding.
Step #3 — Select the audience
You should have a clear understanding of your audience and define the ideal customer that you’re trying to reach and serve. But when doing experiments, you can focus on a segment of your audience, and serve only the ones that you think are relevant.
What is a segment?
It’s the section of your target audience that has similar characteristics, behaviors, and needs. Once you select your audience you can start validating your hypotheses to them.
If you understand the behavior of different customer segments you can optimize the experience for specific segments for maximum adoption.
Step #4 — Uncover the areas of improvements
Seeing the areas of improvement is a great opportunity to take action and make your product much better. As a general rule, improvements are mostly discovered through a customer journey.
What is a customer journey?
It is the entire experience that the customer has while interacting with the brand. The customer journey map is a great tool to identify the pain points of your customers, identify problems, see potential improvements and possible solutions.
By filling out all boxes in the user journey map, you’ll have a good understanding of your customers’ needs and you can come up with new ideas. Keep in mind that filling out the canvas is not a one-time task. You’ll need to come back after a certain period of time to check what has changed.
Step #5 — Answering the WHYs
Now that you have collected the user data and have uncovered the improvements areas we can get answers to our questions and make data-driven decisions.
This is a critical part as you’ll need to understand what are the barriers that are stopping your users from progressing from one stage to the other in the user journey.
Make sure to always know the reason for your user behaviors. For this, you can create micro surveys where users will have to answer a few questions, conduct both online and offline interviews with them to get valuable feedback.
If you know the reason then you can make improvements to level up the customer experience. So it’s important to invest in data and try to understand your users.
Run the experiment
To start the experiment, first, you need to have a hypothesis. Don’t forget that hypothesis is just your guess at why a specific solution will succeed and it must be defined before defining the best execution of an experiment to test it. Additionally, you’ll have to set the stage for the experimentation process. For this, you’ll need to answer the following questions.
- What resources do I have available?
- What is the testing method?
- What tools do I use?
- Who oversees the experiment process?
- What questions will I ask?
When it comes to the testing part you have plenty of choice options. You can do A/B tests, multivariate tests, face-to-face interviews with your real customers, or create user journeys.
This is especially important for companies that have small teams or don’t have the resources to invest in experiments.
That’s it. This is how the framework looks like. Remember that running experiments, gaining valuable insights, and taking action are skills learned over time.
Should you need any help with setting your growth goals, creating in-app experiences, A/B testing, and measuring results — all without writing a single line of code — schedule a free demo with Userpilot to discuss more.