For this type of question, I will follow GAME method and funnel method.

Goals :

1. To use the google sheets among people or team
2. To save the edits and sheet
3. To edit the sheet concurrently
4. To access the saved sheet again
5. User retention

I would insist that revenue is not the goal when it comes to google sheets cause there is a strong competitor from Microsoft. So, from sheet, revenue might not be the primary and foremost goal.

Actions :

1. How often do they sign in in order to create google sheet accounts
2. How often do people use it in read mode that they downloaded some .xsl formal
3. Frequency of create button on sheets
4. Frequency of Save button
5. How many people are concurrently working and saving the sheet?
6. Can they comment on the edits people make?
7. frequency of downloads
8. frequency of sharing

Metrics : honestly not good at this

1. Calculate Daily Active users
2. Number of sheets created per day – trade off – they might delete it
3. How much time are they spending on average ? 20-30min

Guys, help me out in defining metrics

When evaluating the success of Google Sheets, it’s crucial to consider the various touch points users encounter and their user flow while accessing the product. The user journey of a general user accessing and using Google Sheets typically involves the following steps:

Awareness -> Discovery -> Sign-up/Sign-in -> Introduction -> Creating/Importing a Sheet -> Data Input/Manipulation -> Collaborations & Integrations -> Sharing -> Re-iteration -> Exporting

To ensure a comprehensive assessment of Google Sheets’ success, it’s essential to consider the user flow and incorporate it into the key metrics. Here are the key metrics that I would use to measure the success of Google Sheets, aligning them with the user flow:

1. User Growth: Tracking the number of new users signing up for Google Sheets at the entry point indicates the product’s ability to attract and onboard new users effectively -> New Sign-ups
2. Active Users: Monitoring the number of users who regularly access and engage with Google Sheets demonstrates the product’s popularity and ongoing usage -> Monthly/Daily/Weekly Active Users (MAU/DAU/WAU)
3. Retention Rate: Assessing the percentage of users who continue using Google Sheets over time, from onboarding to regular usage, reflects the product’s ability to retain its user base and deliver long-term value -> Percentage of Users Retained
4. Session Duration: Analyzing the average time users spend actively using Google Sheets during a single session at the interaction stage reflects user engagement and the product’s ability to provide a seamless and valuable experience -> Average Time Per Session
5. Feature Adoption: Tracking the percentage of users who utilize specific features within Google Sheets at the feature interaction stage indicates the effectiveness of new functionalities and updates and the user engagement/value created by them -> Number of Clicks per Feature
6. Collaboration Metrics: Evaluating collaboration metrics, such as the number of shared sheets, concurrent editing instances, and collaboration frequency during the collaboration stage, reveals the product’s effectiveness in facilitating teamwork and collaborative workflows -> Average number of Collaborators per Sheet
7. Revenue Generation: Assessing the impact of Google Sheets on revenue generation throughout the user flow, considering potential revenue sources like premium plans, enterprise subscriptions, or any other monetization strategies implemented within the product, demonstrates its financial success -> Percentage Revenue Share per Month

By considering these metrics aligned with the user flow, we can better understand, track, and improve Google Sheets’ success. This approach enables us to identify strengths, areas for improvement, and opportunities for enhancing the user experience at each stage of the user journey.

Great question! Let’s start by defining the goals of Google Sheets. After that, we will come up with a couple of metrics that support these goals. Finally, we will choose from these metrics to determine what our key metrics are.

At a high-level, I view Google Sheets as a tool to empower students and professionals to organize data collboratively as part of the larger Google Drive ecosystem.

For metrics, we can start with the top-line metrics:

• DAUs: Daily Active Users gives us a sense of how the product is performing overall. Are people coming to Google Sheets?
• Market Share: Comparing the # of users within Google Sheets compared to other competitors like Excel may give us a sense of product superiority over the rest of the market.

Then, we can begin to get more granular with our metrics. I think a good place to start would be engagement.

• Ratings: We could use an internal tool within sheets to have users quickly rate their experience with the tool. Maybe, it’s from 1 to 5 stars. We could see trends of this over time in terms of how users are enjoying the software, and even implement qualitative feedback as well.
• % of sheets downloaded: Normally, downloading a Google sheets indicates completeness. It means you’re saving it or sending it to somebody. So, we may be able to look at what % of people are able to “complete” their work by downloading it through Google Sheets. The caveat to this metric is that work can be completed without being downloaded or oftentimes continually added to (ex: if you have a live sheet that is being continually updated)
• Average number of people shared with: Google creates collaborative tools, so one way to measure the success of that particular idea is to track how often the sheet is being shared with another editor.

We can also look at retention.

• % WAUs: It may be helpful to find the % of users who are using Sheets every week. It indicates that Sheets are a core part of their work.
• Churn rate: it also may be helpful to find users who have used Google Sheets in the past, but no longer do for what ever reason.

Now, I’m going to prioritize the metrics that I believe are more important.

• Market Share
• % of sheets downloaded
• % WAUs

Happy to elaborate on why I chose these and did not choose the others.

What do we want to measure? Engagement

• Lets define the breadth of the funnel
  • The total number of users landing in Google sheets will be the breadth of the funnel
• Lets now define the depth of the funnel – Depth defines the user journey
  • # of users who search for an existing sheet or the # of users who create a new sheet
  • # of users who updated data
  • # of users who shared or # of users who downloaded data
• Lets now add a factor of frequency
  • # of sessions for each user
• # of sessions with at least one of the following actions is considered as an Active Session
  • Share event
  • Update event
  • Download event

|--------Number of logged in Users landed in Gsheets---------|

Lets now derive the metrics with the help of above mentioned data

1. The Enegagement can be derived from the Unique users with # of active sessions > 3 per day
   1. This can be derived by grouping the active sessions by User id.
   2. 3 can also be swapped with the avg # of sessions per user
   3. This will give us the # of users who use the product above average usage
2. Usability of the product can be derived from the avg time taken for each active session

Google’s Mission : Google intends to organize the world’s information and make it universally accessible and useful

Google Sheets (Product goal) : With Sheets as a product, Google intends to provide a collaborative and efficient platform to the end users to be able to process and share data and other information.

It aligns with the company mission of organizing and disseminating information. As a product, Google sheet appears to be in growth stage of the lifecycle and hence, user engagement is an important goal that I shall like to focus upon

Top-Level/North Star Metric : As a company, Google is more focused upon no. of searches being made by the end user indicating the engagement levels. Similarly, for Google Sheets, the North Star, according to me shall be – No. of active sessions/per user on a single sheet

Secondary Metrics : I’ll break down the secondary metrics into in-product and business metrics

• In-Product Metrics
  • Let us visualize the user journey for Google Sheets, first. 1. User sign-up/sign-in 2. User opens an existing sheet or creates a new one 3. Edits are made to the sheet 4. Sheet is shared with other users 5. Sheet is downloaded/exported 6. Process is re-iterated

Given the user journey, some of the secondary engagement metrics are as follows – # of sign-up/sign-ins – DAU/WAU/MAU – Average session time – # of features/functions used per session – # of collaborators/sheet – # of parallel edits on a single sheet – # of downloads/sheet

• Business Metrics
  • Here are some important business metrics to track
    • # of users retained since onboarding/signup
    • # of users churned post onboarding
    • # of new sheets created vs deleted

Guardrail Metrics :

• It is important to take into consideration the following precautionary metrics to validate the success
  • # of inactive collaborators
    • It shall point out at the dis-engagement amongst users even post having the opportunity to work upon a sheet
  • # of sheets created/user
    • It shall validate the non-biased usage of sheets amongst one particular cohort of users

I will first start with listing down the GOALS of Google Sheets as a product

GOALS:

1. Enable better collaboration amongst employees in an organisation
2. Make edits parallel
3. Share with co-workers so that the team can work seamlessly
4. Increase user engagement, activity and make more users aware about the functionality and usefulness of Google Sheets

Next, i will try and list the broader ACTIONS a user might take

ACTIONS:

1. Create a new Google Sheet
2. Share with co-workers
3. Make edits in an existing sheet
4. View an existing sheet
5. Comment in an existing sheet

Now, with the goals and actions in mind we can list down the metrics that can be tracked for the success of Google Sheets

METRICS:

1. Average number of new sheets created per user each day
2. Average number of co-workers / participants added for sharing
3. Average number of time spent working on sheets per user