10 Ways To Prioritize Your Product

Prioritization is a big buzzword in the world of Product Management. However, there's no clear answer to the question of what tasks you should prioritize and how to prioritize this tasks. It unfolds differently in every single company and often changes over time.

Prioritization can be defined as the act of deciding what is most important or urgent . It's based on the premise that there are only limited resources available and having to make choices.

There are 10 ways to prioritize your product:

1. The backlog of your team

What your teammates want to work on comes first. First-hand knowledge beats second-hand information. So better discuss the topic with them directly. Of course, they can delegate tasks to you but that's not how it works best.

2. Analysis of customer feedback

People need to relate and look for patterns. Whenever there's some buzz about your product, better listen first. Yet it won't be ideal to just follow the trends as those only appear every now and then. Customer feedback needs careful analysis as you can easily fall into echo chambers .

3. Goals of the company

The long-term vision which is usually shared by everyone on your team should come first too – after all, we'll be bound by it eventually regardless of whether we like them or not (or if we don't know it). Make sure that new features will always fit within them: either directly help reach a goal or make reaching a goal easier in general. This way's work goes down the drain if your company's vision changes.

4. Assumptions

These are the things you believe to be true but have yet to confirm them with data or run tests for . They might be part of your vision, but also just good guesses that turned out to be correct, so why not rely on them? You can then use these assumptions as a basis for building future work and measure how close they came to reality. Be cautious though: if all your assumptions prove false, it'll end up wasting everyone's time and energy – even more than what happened with feature creep (but we'll get there).

5. Definitions

Not everything is always clear cut: two people can easily define something differently depending on their field of expertise or ideas. It's essential to understand that we're all biased and that we should never claim to be right, only closer to the truth than other people (and even then it might not hold).

It can take a while for different teams to reach a consensus. Work together with them to create definitions and use these as guidelines whenever you work on something related. You'll save time and make sure everyone is working towards the same goal. It will also bridge any gaps happening between your team and others (like software development, marketing or sales).

6. Conducting experiments

This brings us back full circle to hypothesis tests: they help you run an experiment which will provide data for analysis. This ties in splendidly with the previous section since it means everyone agrees what to do with the data.

This is where the rubber meets the road: your engineers have crafted a great product and now you want to know if it'll be successful or not. You can run experiments on certain aspects of your site, track their performance over time, take note of anything that sticks out as unusual and try to learn from these results.

7. Calculating statistics

This is a pretty broad category, but it's easy to see why understanding statistical tests will help you in your career. For example, marketing folks should know confidence intervals so they can determine how confident they are that an advertising campaign will meet its goals (e.g., 90% versus 95%). Marketers should also be able to recognize when certain data sets don't follow the normal law of large numbers . Engineers need to understand significance tables and p-values , while salespeople should learn about Bayesian inference .

8. Exponential and logarithmic functions

Engineers and financial analysts use these types of equations all the time. For example, if you're involved with building a power plant, it's likely that you'll be required to calculate the time it will take for certain plants to double their output given exponential growth . If you invest in the stock market , then understanding how volatility changes as things such as time or interest rates change can help you make better decisions.

9. Network analysis

Many companies operate on complex networks (e.g., social media) and understanding how those systems work can be very useful. For example, if I'm leading a team of product designers and we want to know why our competitor is growing faster than us, we would conduct network analysis on their product's network of users. We would look at which of our competitor's users are most connected, how those users are connected to each other, and then try to find out why these people are more likely to recommend the competitor over us.

10. Optimization

You can use optimization to not only make things faster or cheaper, but also better . The best example is Google Search . When you search for something on Google , there are thousands of factors that they consider when providing you with the results. They optimize for relevance, placing the information that will be most useful for you at the top of your page instead of having it buried somewhere else.