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Better DX: Combining user ​
feedback with API metrics ​
2023 SERIES OF EVENT
New York
May 16&17
Australia
October 11&12
Singapore
April 12&13
Helsinki & North
June 5&6
Paris
SEPTEMBER
London
November
15&16
June 28-30
SILICON VALLEY
March 14&15
Dubai & Middle East
February 22&23
Rainer Loopere

Katana Co-Head of Product
2014 – 2019

Wise (TransferWise)
2020 – 2022

Katana ​
API 

Product Manager​
2022

Katana API &
App Marketplace
Product Lead
2022

Katana Co-Head
of Product
Agenda
What is Katana
Who uses Katana’s API: how and why
Data analytics architecture
Metrics: from high-level to operational
The data we use for API feature
development
What’s next in API metrics
What is Katana?
Katana is a business software solution that
gives thousands of manufacturers the live
overview they need to make decisions.
By combining live inventory management, real-time
master planning, outsourced production, and a platform
approach with native integrations, Katana is a one-stop-
shop for businesses in need of a leaner, more user-
friendly, manufacturing software solution.
Today's product-based
business​needs a different
type of ERP ​
The era of business suites that deliver
everything is coming to an end
Customers want a 5 ️experience
throughout the entire business workflow​
Katana's journey from
product to ​
platform
Launched open
API
2020 - 2021
Begin onboarding
apps and custom
integrations
2021
Improvements to
developer
experience​
2022
Developed
Katana's App
Partner Program
2022
Launch Katana's
App Marketplace
2023
Who uses Katana's API:​
how and why ​
Katana customers Katana App Partners
Build integration
Sales channels — e-commerce, CRM
Shipping
Accounting
Analytics
And much mor
Automate workflows
Integrate their SaaS solution with ours
Data warehouse
Power BI

Reporting more complex data models
API analytic
Used to define
which integrations
are “active”
Log
Monitoring
Customer Data
Platform
Real-time trends & funnels,
customer activity
Website activity

Product activity

Subscription changes

Intercom, Hubspot
Contextual dat
Name, emai
Subscription data & MRR
User cohorts about active users
API gateway Moesif Segment
Mixpanel
Datadog
Data analytics architecture​
​

Process + tooling we use
Metrics: from high-level to
operational​
Long-term 

business goals
MRR targets
Move upmarket by delivering features that
unlock a new target customer segment​
1
Metrics: from high-level to
operational​

Number of custom integrations on AP
Number of third-party integrations on AP
Conversion rate for customers who use API ​or
3rd party integrations​
​Long-term ​API goals​
2
Metrics: from high-level to
operational​

Number of active custom integrations on API
​Number of third-party integrations on API
​Quarterly OKRs​
3
Metrics: from high-level to
operational​

Weekly active users*: 

made at least one reques
Active integrations who hit the threshol
Monitor changes*/outstanding behaviour 

and offer help if needed
Weekly ​metrics​
4
Metrics: from high-level to
operational​

Total number of request
​Total number of 500
% of error
4xx errors (ensure nothing is broken)
503s to track performance
​Bugs reported by support
​Diagnostic​metrics​
5
Chat bubble on our website, in-app, Developer Portal where
customers can: ​
Get help with finding an integration partner
Discuss API-related questions over a call or chat

Wish tags from support communication
Requests for improvements/missing feature
Examples:
Prioritize which end points we need to open first
Increase rate limits
Data we use to drive API
feature development

Customer requests via Intercom
Data we use to drive API
feature development

Customer calls/interviews
Useful for gaining more detailed insights into pain points and
finding a potential solution.


Examples:
Providing access to deleted data
Designing functionality for our first client library
We can track each endpoint together with headers, query params,
and body. This gives us insight into how each field is used. ​


Examples:
When planning our first library: User-Agent header for
application insight
We wanted to add extend functionality (shortcuts), so we
analyzed patterns of endpoint usage: what endpoints are
requested most often. This helped us identify inefficiently
designed APIs.
Data we use to drive API
feature development

API Usage Metrics
Incidents and bug fixes​​

How we address these at Katana​
Since we can track how each field and endpoint is used, we can
easily get information about who and how many are impacted.


Example:
A case where we fixed a bug and added extra validation to one
field, breaking the integration. We could easily query how many
customers misused the field and got a new error message. ​
How API data​benefits everyone​
API analytics are connected to our company
analytics, ​making it possible to:
Conversion rate, MRR and other business impact analysi
Targeted product update emails based on previous API activit
Input for customer-facing teams to know who is using our API
What’s next?
What is the API about
Could it solve my
problems
Can I trust this API?
Is this of use to me?
Does it look easy to use
Does it look complete
How much does it cost?
Will it meet my needs?
Time to “Hello World
Are the Docs a good
experience
Do I have confidence
Is there a community?
How does it work?
Speed to MV
Is the product a good
experience
How do I get support
Is it value for money?
Can I build a proof of
concept?
How to keep it running
How do I give feedback
How can I contribute
Will the product grow with
me?
Can I use it in production?
Stage
Goals/Needs
Questions
Discover Evaluate Learn Build Scale
Start measuring additional phases of the​developer journey:​
Discovery & Evaluation – Website and API Docs activity
Learn – Time to "Hello World"
Build - Time from "Hello World” to an active integration​
Bringing

manufacturing

to life
Feel free to reach out on LinkedIn: Rainer Loopere

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apidays Paris 2022 - Combining user feedback with API metrics to improve DX, Rainer Loopere, Katana

  • 1. Better DX: Combining user ​ feedback with API metrics ​
  • 2. 2023 SERIES OF EVENT New York May 16&17 Australia October 11&12 Singapore April 12&13 Helsinki & North June 5&6 Paris SEPTEMBER London November 15&16 June 28-30 SILICON VALLEY March 14&15 Dubai & Middle East February 22&23
  • 3. Rainer Loopere Katana Co-Head of Product 2014 – 2019 Wise (TransferWise) 2020 – 2022 Katana ​ API 
 Product Manager​ 2022 Katana API & App Marketplace Product Lead 2022 Katana Co-Head of Product
  • 4. Agenda What is Katana Who uses Katana’s API: how and why Data analytics architecture Metrics: from high-level to operational The data we use for API feature development What’s next in API metrics
  • 5. What is Katana? Katana is a business software solution that gives thousands of manufacturers the live overview they need to make decisions. By combining live inventory management, real-time master planning, outsourced production, and a platform approach with native integrations, Katana is a one-stop- shop for businesses in need of a leaner, more user- friendly, manufacturing software solution.
  • 6. Today's product-based business​needs a different type of ERP ​ The era of business suites that deliver everything is coming to an end Customers want a 5 ️experience throughout the entire business workflow​
  • 7. Katana's journey from product to ​ platform Launched open API 2020 - 2021 Begin onboarding apps and custom integrations 2021 Improvements to developer experience​ 2022 Developed Katana's App Partner Program 2022 Launch Katana's App Marketplace 2023
  • 8. Who uses Katana's API:​ how and why ​ Katana customers Katana App Partners Build integration Sales channels — e-commerce, CRM Shipping Accounting Analytics And much mor Automate workflows Integrate their SaaS solution with ours
  • 9. Data warehouse Power BI Reporting more complex data models API analytic Used to define which integrations are “active” Log Monitoring Customer Data Platform Real-time trends & funnels, customer activity Website activity Product activity Subscription changes Intercom, Hubspot Contextual dat Name, emai Subscription data & MRR User cohorts about active users API gateway Moesif Segment Mixpanel Datadog Data analytics architecture​ ​ Process + tooling we use
  • 10. Metrics: from high-level to operational​ Long-term 
 business goals MRR targets Move upmarket by delivering features that unlock a new target customer segment​ 1
  • 11. Metrics: from high-level to operational​ Number of custom integrations on AP Number of third-party integrations on AP Conversion rate for customers who use API ​or 3rd party integrations​ ​Long-term ​API goals​ 2
  • 12. Metrics: from high-level to operational​ Number of active custom integrations on API ​Number of third-party integrations on API ​Quarterly OKRs​ 3
  • 13. Metrics: from high-level to operational​ Weekly active users*: 
 made at least one reques Active integrations who hit the threshol Monitor changes*/outstanding behaviour 
 and offer help if needed Weekly ​metrics​ 4
  • 14. Metrics: from high-level to operational​ Total number of request ​Total number of 500 % of error 4xx errors (ensure nothing is broken) 503s to track performance ​Bugs reported by support ​Diagnostic​metrics​ 5
  • 15. Chat bubble on our website, in-app, Developer Portal where customers can: ​ Get help with finding an integration partner Discuss API-related questions over a call or chat Wish tags from support communication Requests for improvements/missing feature Examples: Prioritize which end points we need to open first Increase rate limits Data we use to drive API feature development Customer requests via Intercom
  • 16. Data we use to drive API feature development Customer calls/interviews Useful for gaining more detailed insights into pain points and finding a potential solution. Examples: Providing access to deleted data Designing functionality for our first client library
  • 17. We can track each endpoint together with headers, query params, and body. This gives us insight into how each field is used. ​ Examples: When planning our first library: User-Agent header for application insight We wanted to add extend functionality (shortcuts), so we analyzed patterns of endpoint usage: what endpoints are requested most often. This helped us identify inefficiently designed APIs. Data we use to drive API feature development API Usage Metrics
  • 18. Incidents and bug fixes​​ How we address these at Katana​ Since we can track how each field and endpoint is used, we can easily get information about who and how many are impacted. Example: A case where we fixed a bug and added extra validation to one field, breaking the integration. We could easily query how many customers misused the field and got a new error message. ​
  • 19. How API data​benefits everyone​ API analytics are connected to our company analytics, ​making it possible to: Conversion rate, MRR and other business impact analysi Targeted product update emails based on previous API activit Input for customer-facing teams to know who is using our API
  • 20. What’s next? What is the API about Could it solve my problems Can I trust this API? Is this of use to me? Does it look easy to use Does it look complete How much does it cost? Will it meet my needs? Time to “Hello World Are the Docs a good experience Do I have confidence Is there a community? How does it work? Speed to MV Is the product a good experience How do I get support Is it value for money? Can I build a proof of concept? How to keep it running How do I give feedback How can I contribute Will the product grow with me? Can I use it in production? Stage Goals/Needs Questions Discover Evaluate Learn Build Scale Start measuring additional phases of the​developer journey:​ Discovery & Evaluation – Website and API Docs activity Learn – Time to "Hello World" Build - Time from "Hello World” to an active integration​
  • 21. Bringing manufacturing to life Feel free to reach out on LinkedIn: Rainer Loopere