You’re the PM for Google Cloud storage. How would you measure success?
Google
Dropbox- Malcolm Sequeira
Clarification:
We are talking only about cloud storage and not any of the following which doesn’t come under the classification of cloud storage. Specifically not the following
Google drive
Firebase
Compute storage
Filestore
Product Description:
Use-cases are for storing objects in cloud for many of the following not restricted to
Standard – Hosting static websites, storing data which is accessed frequently from your compute engines
Nearline – Highly durable but access(RW) is less frequent (once a month )
Coldline – Less than once a month. Like once a quarter- highly durable
Archive –Â Once a year. Highest durable, SLA
Cloud storage by itself (remember that we are not talking about Google drive etc.) serves primarily two of the multiple use cases
- Can be used solely as a standalone storage mechanism without an active project/application
- As a part of a cloud application
The difference between both are
- If using as a part of cloud application, the customer is tying their application to Google’s cloud eco system and will use other services offered
- Will use more storage as application increases the demand for storage and also the demand on network transfer and storage also increases
- If solely used for storage, it will be periodic transfer of data from on-premise data to cloud storage. Mostly a hybrid cloud model
Another point to consider is that all cloud storage offerings offer a free tier and only after you cross the storage limit you will start to get charged.
Competitive Analysis
Currently the market leader in cloud storage and computing is AWS with Google Cloud a distant 3rd and Microsoft taking the second spot
In terms of competitor’s strength
- AWS – First to the market, massive lead, plethora of storage options by granularity (IOPS, throughput) for different use cases
- Microsoft – Hybrid cloud strategy, works best for all office applications used across the world
- Google Cloud – Specialized applications in terms of ML/AI engines, data sets that can be used for training models etc.
Market Analysis
- Multi cloud deployments are still not easy and generally one vendor solutions reduces complexity
- Hybrid cloud deployments are the form for normal applications
User/Organization analysis
- Startups – # of Employees < 10, going to launch the product and get the demand hopefully
- Small & Mid sized companies
- Large companies
Product Lifecycle
- Even though Google cloud storage was launched first amongst the Google cloud products, its adoption is heavily dependent on the applications moving to Cloud platform
- Even though it’s an old product, based on my understanding of the market and competition I would like to focus on acquiring new customers
Google Cloud’s Mission and Goals
- Mission is to help organizations around the world to help in digital transformation by providing the best possible infrastructure
Metrics for measuring success
- I am going to focus on the acquisition and engagement/adoption of the cloud storage as the ultimate goal. Not going into the segments/verticals acquisition/adoption
| S No. | Criteria | Funnel | Metric Explanation | Implementation Difficulty and Notes | Impact | Priority |
| 1 | Users | Acquisition | # of New users signing up for the free trial | Easy – Helps in measuring the conversion later and also what can be done better | High | P1 |
| 2 | Acquisition | # of New users entering their credit card details | Easy – Shows that the user is serious about using the service | High | P1 | |
| 3 | Adoption/Engagement | # of New users actively logging on daily/weekly | Easy – If the application requires maintenance it will show a high number. Can be misleading as well because of dependency on application | Medium | Â P2 | |
| 4 | Adoption/Engagement | # of New users creating project(applications) & buckets associated with the applications | Easy | High | P1 | |
| 5 | Adoption/Engagement | # of New users using other GCP services, compute engine etc. | Easy – Good metric to track in the long run | Medium | P3 | |
| 6 | Adoption/Engagement | The traction/visibility of the new user’s application i.e. Number of website requests, sessions etc. – this directly ties to revenue metrics as network traffic increases | Easy – The billing is done automatically | Medium | P4 | |
| 7 | Adoption/Engagement | # of new users transitioning from free tier to paid tier | Easy | High | P1 | |
| 8 | Adoption/Engagement | Rate of storage use increase by user | Easy – Helps in promotions, targeting users | Medium | P4 | |
| 9 | Storage | Adoption/Engagement | #Â of new users turning on lifecycle management, tier management notifications etc. | Easy – Shows adoption and also in future they plan to use storage more extensively | Medium | P3 |
| 10 | Adoption/Engagement | # of new users using archival solutions for their cloud data or on-premise data | Medium – Long term adoption | Medium | P4 | |
| 11 | Adoption/Engagement | # of new users requesting access to archival data | Easy | Easy | P4 | |
There are a bunch of other services that can also be used to measure success like number of IAM roles/users etc. but focusing only on storage here.
The reason I have marked most of the implementation notes as easy – GCP already has dashboard to show all these data and easy to get.
I would like to focus on (1), (2), (4), (7), (3) for measuring success in Phase (1) and after a period of 6 months focus on (5), (6), (9), (11) along with the previous list.