Using Business Intelligence to Tell Your Product’s Performance Story

Editor’s note: The following is a guest post by Chartio. If you’re interested in writing a piece for us, contact gaby@productschool.com

Product Managers are constantly evaluating how to improve the customer experience. They use data in order to understand their product’s performance and make changes to improve it. While understanding the data as a product manager is fairly challenging, communicating how your product is doing to others accurately can be much more so. Product managers must communicate with many areas within their organizations: marketing, finance and engineering to name a few. Each department has its own unique points of interest.

  • Are we acquiring enough customers per month? 
  • What is the product’s retention rate? 
  • How are customers engaging the product 

Needless to say these are just the tip of the iceberg. How do you begin to build a comprehensive story that keeps all parties abreast of high level progress? What metrics should you be including?

Building Your Product’s Performance Story

While there are many strategies for communicating data. We are going to focus on grouping metrics by objectives to establish a framework for your performance story. Then combining metrics from these different objectives to highlight key wins and provide discussion points for product improvements. 

We will walk through how to use business intelligence (BI) to convey a multi-metric story using a fictitious company, Get Fit. The company owns a streaming exercise video app that currently has roughly 5 million subscribers and is growing. They charge a $10 monthly subscription that gives you unlimited access to popular training programs! This is a great tool for people wanting to get a workout on the go!

Here are some metrics groupings to use as a guide:

Metrics to Forecast Product Success 

These are metrics that are important to management and Finance. They help inform how much the product is impacting the bottom line and whether or not to further invest. They include: 

Monthly Revenue graph
  • Monthly Recurring Revenue (MRR)A product’s recurring revenue for the month. This revenue is usually a subscription fee that the consumer pays to use a company’s services which they engage through the product. Get Fit has been able to acquire new customers month over month which equates to their increase in recurring revenue.
Subscription Metrics graph
  • Average Revenue Per User (ARPU) – The average revenue a customer brings in for a given time period. Monthly is a popular time period as it gives you just enough time to gauge performance and implement changes. So ARPU is calculated as the MRR/Total number of accounts. ARPU helps quantify the revenue impact of acquiring or retaining customers. 

Get Fit’s MRR has been slowly increasing month over month which is inline with their monthly subscribers. They’ve been able to maintain their ARPU at $10 which coincides with their monthly subscription fee. This tells us that they have been able to maintain their customer base. 

  • Customer Lifetime Value (CLTV) – CLTV helps to quantify the revenue impact as well as cost to promote in various marketing channels. Using ARPU you can do the following: ARPU * Average Customer Lifetime = CLTV. The average customer lifetime is how often a customer remains with the company. 

Get Fit’s customers tend to stay subscribed to the streaming app for about 3 years, that would be 36 months since our examples are looking at monthly time frames. So Get Fit’s CLTV = $10 * 36 = $3600.  

Metrics to Grow User Engagement 

Your product is the gateway to your company’s brand and most times serves as the first representative they interface with. Therefore, understanding how your customers are engaging with the experience created by your product is essential. While implementing product features are definitely important, reviewing user engagement can help steer what features get prioritized. Metrics to consider are:

User Engagement Graph
  • Daily Active User (DAU) – The number of active users logging into your product and performing an activity per day. The criteria used to define an active user will depend on your organization or the product itself. Chartio’s tutorial on active users recommends steps on defining active criteria. 

For the Get Fit team, logging into the app is one of the criteria for an active user. They decided that even though a user did not select a workout video, they would incorporate the session time in the app. This accounts for a user browsing through the library and implies a deeper level of engagement. Deciding what defines an active user can be widely debated in organizations so a good event to start with is user login. Get Fit had roughly 1.5 million daily active users in Nov 2019 we see there is a decline as we approach the beginning of the year. This trend of people working out less during the holiday season going into the new year is common.

  • Monthly Active User (MAU) – The number of active users logging into your product and performing an activity per month. Get Fit has roughly 4 million monthly active users on average. With a subscriber base around 5 million this means that everyone signed up for the app is not actively using it. Get Fit plans to design a customer satisfaction survey to understand if there is something they can do to increase logging into the app.
  • DAU/MAU Ratio – Using DAU/MAU ratio can help you tell a story around the stickiness of your product. For example, if you have 1,000 customers engaging your product daily on average and 5,000 customers engaging monthly that is 20% of your customers making repeat visits. The higher this number the better your story as it shows that you have an increase in repeat customers which implies higher engagement.

The Get Fit App had high engagement around the holiday season. Engagement was at 35% in November and started to decline month over month reaching 20% The good news is that this is still pretty good engagement and they expect engagement to increase as spring approaches.

Metrics to Analyze Customer Retention

These metrics serve as indicators in how well your product is keeping customers engaged and causing them to return for another experience.

Customer Rentention Metrics
  • Retention Rate (RR) – The percentage of customers who remain subscribed with the product after a certain period of time. Again we can use the month as a time period. The formula can look like this: [(Customers at the End of the month) – (New Customers)]/(Customers at the Beginning of the month) * 100

Get Fit’s retention rate has fluctuated between in the 80% range with a dip of 72% at the beginning of 2020. Post holiday season is usually a time when people tend to stop working out. As 1Q progresses, people start thinking about getting fit again remembering those New Year’s resolutions to get in shape. 

  • Customer Churn Rate (CR) –  Measures the number of customers lost over a given time period. This is a great indicator to start investigating why customers are leaving. Is it pricing? Maybe there’s a product feature that is causing a less favorable customer experience? Here are three ways to look at churn for your business.

Metrics to Measure Product and Feature Popularity

These are another set of metrics integral to the performance story as features impact the product’s design. The following two metrics take us a step deeper into how customers are spending time engaging with the product.

  • Number of Sessions per User – Measures how often users come back and use the site. How many logins or site visits. To calculate session length, you need to be able to track exactly when a user starts using an app and when they stop. While most analytics tools will calculate this for you, the equation for average session length is 

Sum of Individual Session/ Total Sessions in That Timeframe 

  • Number of User Actions per Session –  Tracks not just how many times a user opened an app. It displays which actions a user made and which feature(s) they used while using the app. This metric is used to understand the popularity of a certain feature since it was introduced and compared to a particular period of time. Also, you can compare these metrics of churned and retained customers and get an idea of what makes the users interested in your product.

Metrics to Evaluate User Satisfaction

These metrics measure direct feedback received from customers usually via a survey. While this feedback can be valuable it should also be taken with a grain of salt. A lot of times you will receive feedback from customers who are extremely loyal to your brand or have had an extremely dissatisfying experience. So tread wisely as you review this feedback and incorporate into your story!

  • Net Promoter Score (NPS) – This metric measures the number of loyal customers who are likely to recommend a product (promoters), and those customers who hate it (detractors). To calculate NPS, ask users to rank your product from 0 to 10. Detractors would give it from 0 to 6 points, users with 7-8 points are neutrals, and those who gave it 9-10 are promoters. NPS = % of Promoters – % of Detractors. Here’s some more information and best practices on how to use NPS.
  • Customer Satisfaction Score (CSAT) – This metric helps measure feedback on specific features and customer journeys within your product. Like the NPS score it uses a scale for customers to rate a feature from 1-10 or 1-5. The scores are summed up and divided by the number of respondents. 

Putting it All Together

Get Fit Metrics Graphs

As a product owner your story should be a customer-centric one. Knowing your MRR allows you to communicate the impact product decisions make to the business. ARPU allows you to quantify revenue on a customer level. This metric should be one of your guides when making any design decisions.

Looking across these metrics we can tell a clear performance story about the Get fit business::

  • Get Fit Is growing despite losing some customers each month.
  • Get Fit has maintained their ARPU at $10 which is inline with their monthly subscription fee. This can be an opportunity to increase ARPU with additional services.
  • The product appears to be less sticky due to the MAU/DAU ratio but we have not seen an impact on retention. This is something to keep an eye on.
  • Get Fit’s customer retention rate has been in the high 80’s range the last two months.  

The above bullets can serve as headlines for various management meetings at Get Fit. They all potentially address goals for the different organizations in the company to make the Get Fit App a successful product. There is increasing revenue and a high retention rate. Analyzing that ARPU is at $10 has encouraged a meeting to discuss brainstorming a new potential service. Finance is also looking to set a performance goal of getting the retention rate above 90% over the next 2-3 quarters.

Speak to your Audience

When creating your performance story, find a powerful insight to use as a highlight and build around it. One phrase I like to remember is that your audience wants to hear more about the great pearls you found, not your hunt for oysters. The goal is to inform but also make recommendations with your insights. As a product manager your guiding storylines throughout your product’s life cycle is:

  • Stickiness: Attracting new users and ensuring they continuously stay engaged.
  • Business: Making an impact to the bottomline.
  • Feature Adoption: Integrating the product into a customer’s daily routine.
  • Customer Feedback – Gauging customer loyalty and satisfaction.

Below is a matrix that can help with building your performance story. As you focus on a topic for your story, use the below metrics as a guide.

StickinessBusinessFeature AdoptionCustomer Feedback
MRRXX
ARPUX
CLTVXX
DAU/MAUXXXX
DAU/MAU RatioXXXX
Retention RateXXX
Churn RateXXX
Sessions/UserXX
Actions/UserXX
NPS/CSATXX

The World Has Gotten Really Good at Collecting Data

Chartio has made it possible for anyone, not just analysts, to query their businesses data. They state, “The world has gotten really good at collecting data, now the largest bottleneck is our ability to understand the data and make informed decisions based on it.” Chartio has made quite an investment in making data analysis more intuitive with their visual SQL interface. One advantage of visualizing the querying process vs learning code is that it leaves the less technical user unrestrained with the business questions they have. This gives the product manager more time to incorporate the data points that will help tell their performance story. 

Andrea Sipos from Prezi shared her product management story building a Chartio dashboard. Working in a “data-required” culture, Andrea found it easy to create a dashboard in Chartio and begin sharing charts with her stakeholders. She applauds the ease of self-service she has with the tool versus having to be dependent on another team for the data.

The key to success moving forward is a broader understanding of data. Being a great product manager will require analyzing data and communicating trends and insights.  Chartio lets you build out these metrics without writing a single line of SQL. Start using Chartio to combine metrics on dashboards to provide right insights to the whole company.

Meet the Author

Allen Hillery

Allen Hillery

Allen Hillery serves as part time faculty at Columbia University’s Applied Analytics program. He has spent the greater part of his career being an ambassador for business teams and championing the voice of the customer. Allen is very passionate about data literacy and curates an article series that focuses on the importance of creating data narratives and spotlighting notable figures on how their use of storytelling made major impacts on society.

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