Product management metrics and analytics are the best way to ensure that you are building off of facts instead of just assumptions. But analyzing too many parameters and implementing the right analytic tools can get complicated.
Hence, we dive into the nitty-gritty of using metrics, why and how they work, and how to rally your team around your new data and use your findings to create effective change.
Why product management metrics and analytics are essential?
In the absence of metrics and analytics, you are pretty much shooting in the dark. You are working with assumptions. To make decisions that are best for our product, we use different analytical tools and metrics are crucial. Among the many benefits metrics and analytics have, a few of them are as below:
- Better user experience as we involve the end-users in the test and validation process.
- The decisions are data-driven. We no longer take actions based on assumptions. Instead, they are data-centric.
- With the help of metrics, we can take the required action steps to reach the product-market fit.
- With metrics and analytics in place, we are using a scientific decision-making heuristic to craft and implement the strategy.
For example, there are some frictions in the workflow of your marketing website which when removed, will increase the engagement by 5%. Now, we start by making a hypothesis that friction might be due to the marketing copy or size of the buttons. We test our hypothesis with the sample size by defining some success criteria. As per the findings, we make decisions. Without a hypothesis, our action would just be based on people’s opinions.
What are the different types of metrics and analytics?
As discussed above, analytics play a crucial role in the product development lifecycle to make data-driven decisions. We will talk about some of the analytics tools and frameworks below:
By implementing funnel, we can segment the customer data as per the stages they are in a sales funnel. It will help us run a personalized campaign directed towards specific objectives.
For example, if you run an email marketing campaign with a 20% open rate, a 10% click-through rate, and a 10% click on the links.
You can categorize these users in different groups and run separate campaigns for each group to move them from one stage to another in the sales funnel. By doing so, you can reduce your customer acquisition cost and increase customer lifetime value.
2. Dave McClure’s AARRR Framework
The AARRR framework is one of the most useful metrics for any startup marketer. AARRR stands for Acquisition, Activation, Retention, Referral, and Revenue and is widely accepted as 5 essential metrics for any startups.
The AARRR framework is customer-centered and focuses on the sales journey of the customers. From the acquisition of customers to revenue, it tracks down every activity.
The important thing is to have a standard definition in your team for each of the metrics. What would you consider as activation or retention? These are dependent totally on the type of organization and the industry. For instance, money transfer can be an activation metric.
3. COHORT analysis
Cohort analysis analyses the behavior of a group of users instead of individuals over time. There could be many users or customers who would take similar actions when triggered by particular features or marketing activities. Instead of analyzing individual behavior, we analyze a cohort to understand their behavior and initiate the required steps.
What are the important metrics to watch for?
The importance of metrics for any business will depend on the industry they belong to and their sales cycle. However, here are some metrics that can be equally important in all the industry:
1. Churn rate
The annual percentage of people stopping to use the product or subscribe to it annually.
2. Customer acquisition cost
Customer acquisition cost is the cost incurred by companies to turn their potential users into users.
3. Customer lifetime value
Customer lifetime value represents the amount of money a customer will spend on your product or service throughout their lifetime.
4. Gross merchandise value
Gross merchandise value is an essential metric for e-commerce businesses, which refers to the total amount of sales the company makes over time.
To implementation, these metrics, different analytics tools like google analytics, mix panel, and others can be used too.
How to bring in team members to rally down?
Product managers create a tracking plan as per which the development team implements the required tools. The reports and data are then shared with UX designers, executives, marketing teams, and anyone who needs it. Analytics data is shared with the team to understand what is happening with the product. They keep measuring the data, but product managers must explain what should be tracked and what exactly is the expectation from measuring those data.
Limitation of Analytics:
Analytics will provide us with data but will not explain the “why” behind it. Moreover, it is up to the product managers and the team members on how they interpret the data. It won’t give you feedback about what you haven’t done. Sometimes what we haven’t done is equally important as what we have. For instance, we do not get insights on what features should have been added or removed.
The best way to avoid confusion and complications is by starting with one metric. Build the momentum from there. Research on what metrics will suit your company best, and the measuring culture grows from there.
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