Making the Most of Your Analytics

Released Tuesday, 13th October 2015
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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?

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Episode Details
43m 52s

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