apidays Paris 2022 - APIs the next 10 years: Software, Society, Sovereignty, Sustainability
December 14, 15 & 16, 2022
Combining user feedback with API metrics to improve DX
Rainer Loopere, API & App Marketplace Product Lead at Katana
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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
businessneeds 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
Diagnosticmetrics
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 databenefits 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 thedeveloper journey:
Discovery & Evaluation – Website and API Docs activity
Learn – Time to "Hello World"
Build - Time from "Hello World” to an active integration