Aug 14 2020 30 mins 1
Arjun grew his customer data wrangling techniques while crafting Segment Tracking Plans to transform product lines at IBM as a Growth Product Manager. Tune in to this episode to hear how to succeed with automation by increasing data literacy and focusing curiosities.
This is Segment’s Data Council series, where members share stories about using Segment to work with customer data within Enterprise companies. To make sure you don’t miss an episode, subscribe on iTunes, Spotify, or your favorite podcast player. You can also read a lightly edited transcript of the conversation below.
Takeaways
- Just because you can automate something doesn't mean you should.
- Everything that you're tracking should be tied to a KPI, a metric, or some specific use case.
- Use governance on your architecture to be both proactive and reactive.
Audio highlights
- “You could have the greatest data in the world and it could follow a very clean and specific taxonomy, but if nobody understands it and there's no record of it anywhere, it's meaningless and worthless.”
- “Automation can be great once you have a more mature process and you have a better idea of what it is you're trying to achieve. But automating for the sake of automating can also be more trouble than it's worth because writing something into stone when it's a first draft is just a bad idea.”
Links
- Blog: What does it take to achieve good data at enterprise scale?
- Guide: What is a Tracking Plan?
- Analytics Academy: Making the Most of Your Customer Data
- Catalog: Amplitude, Braze, Intercom, Segment Functions, Segment Protocols, WalkMe
- Case Study: How IBM standardizes data across its cloud platform with Segment
- Video: Digital distribution 2.0: How Anheuser-Busch InBev delivers beer all over the world
- Video: Protocols Course | Segment University
