Diana Smith of Segment tells us how to get the most out of our analytics tools. In the pursuit of trying to be data-driven, we have been conditioned to track everything. Diana tells us why this can be dangerous if we want to draw useful insights from our data.
Here's what to listen for:
- 00:49 - What specifically are we talking about when we are talking about analytics in this context?
- 01:55 - What is the difference between user path and funnel tracking?
- 03:10 - Are there tools similar to Kissmetrics Path Report tool?
- 03:57 - If I’ve got my own database, why should I be using some sort of other analytics tool when I could just easily track events that happen on my database as it is?
- 05:43 - What events should I be tracking?
- 07:22 - When I set up what these events are, does it matter how I name them?
- 08:19 - What is the best naming convention?
- 09:14 - Why should I start only with just tracking a few events?
- 10:53 - What kind of info should I be putting in these properties?
- 13:16 - How do you connect and keep track of the who the referrer is? How does that work?
- 14:45 - How important are user demographics for data and tracking?
- 19:59 - How should I make use of the data that I’m collecting?
- 23:25 - Do you recommend that people create a bunch of accounts on these different sites and then choose one? How do you deal with the paradox of choice?
- 24:57 - What types of other analytics tools are out there?
- 26:33 - How do you decide which of these tools to use? What sort of questions should I be asking around “which one is right for me”?
- 31:54 - Are there any can-not-ignore metrics?
- 33:03 - How do I actually try and make a connection between the action that I’ve taken and the results that I’m seeing?
- 34:34 - Do you recommend waiting and focusing on qualitative things over quantitative?
- 36:42 - Is there a number you should be looking for in terms of when things should be statistically significant?
- 37:19 - In terms of doing the qualitative work that you talk about, and maybe trying to use quantitative data to make it match up with the qualitative data, or at least help … are there any specific strategies that you recommend for going out and getting that qualitative data?
- 38:51 - Let’s say that I am collecting enough data at this point. Even though I have a baseline for myself and my company, how do I know whether or not that’s a good baseline?
Who's On This Episode
We don't know anything about the creators of this episode yet. You can add them yourself so they can be credited for this and other podcasts.
This episode hasn't been reviewed yet. You can add a review to show others what you thought.
Mentioned In These Lists
There are no lists that include "Making the Most of Your Analytics". You can add this episode to a new or existing list.