☰ Sidebar
Voting period for this idea type has passed

SXSW Interactive 2014

Metrics That Matter: Transcending User Data Silos

The recent proliferation of Big Data has had good, bad and ugly effects with respect to customer analytics. The good news: data is everywhere, meaning we know more about users than ever before and moreover, that we can access that data faster than ever. So what’s the problem, then? With big data have come even bigger silos, which frequently lead to a very ugly outcome: ignorant marketers.
Let's talk about an email I received from AMEX last month - subject line, “Cassie, check out our updated mobile app.” Despite the fact I have the iOS app (and have had it for years), I got prompts for both the iOS and Android apps. And when I went to download the "updated" app for iOS, there was nothing there for the taking - because I had already downloaded the update. Womp-womp.
All marketers talk about 1:1, relevancy, etc., but the truth is, beyond sparing men of bikini wax offers, few actually deliver. This talk will focus on actionable methods for understanding the 360-degree customer.

Share this idea

Takeaways

  1. Tracking parameters such as join dates and acquisition sources are truly the epitome of amateur hour when it comes to customer analytics. What type of information should you be collecting and aggregating about your customers as well as about your broader business ecosystem to drive truly game-changing insights?
  2. What are "situational" business metrics and how do they differ from the traditional approaches of more straightforward customer- and product-level analysis? Why are data relationships and ratios the foundation for understanding the 360-degree customer?
  3. What sort of "single" platforms exist to help marketers synthesize and digest customer behavior from a multitude of disparate sources in a meaningful way (e.g. tie purchase propensities to email behavior, site behavior, app activity, viral coefficients and so on)?
  4. How has the proliferation of Big Data helped traditional customer segmentation models (e.g. RFM/recency-frequency-monetization) to evolve? As we think about the multi-channel customer, where is segmentation headed?
  5. As marketers continue to know more and more about their end customers, it's tempting to use that information for profit however humanly possible. Where and when should marketers draw a line between Big Data and Big Brother?

Speakers

  • Cassie Lancellotti-Young, VP Client Optimization & Analytics, Sailthru

Organizer

Cassie Lancellotti-Young, VP Client Optimization & Analytics, Sailthru

Meta Information:

  • Tags: analytics, marketing
  • Event: Interactive
  • Format: Solo
  • Track: Entrepreneurialism and Business
  • Level: Intermediate
Show me another idea

Add Comments

comments powered by Disqus

SXSW reserves the right to restrict access to or availability of comments related to PanelPicker proposals that it considers objectionable.