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MeasureCamp - Returns Management System Hacks
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MeasureCamp - Returns Management System Hacks

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A MeasureCamp presentation I didn't get time to cover which explains how we used some Google Analytics hacks to analyse e-commerce Returns Management System trends.

A MeasureCamp presentation I didn't get time to cover which explains how we used some Google Analytics hacks to analyse e-commerce Returns Management System trends.

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  • 1. Returns Management System hacking Matt Clarke, @techpadSunday, 17 February 13
  • 2. The problem... • We promised customers we’d handle their return in 7-10 days. • We suspected that sometimes returns didn’t get handled within this time, but our existing RMS couldn’t tell us. • When returns handling was slow, call volume went up, so did email queries. This annoyed customer services and customers.Sunday, 17 February 13
  • 3. Step 1: Track emails • Before we started on a major rebuild of the RMS, we added event tracking to the form used to categorise customer service emails from the site. • We do a similar thing with complaints analysis (there’s a post on that on my blog).Sunday, 17 February 13
  • 4. Step 2: Monitor emails • I built a dashboard to provide an overview of emails received. • I used the API to report on increases in returns emails/proportion, which might indicate a failure to meet customer promise.Sunday, 17 February 13
  • 5. Step 3: Dig deeper • I spent three months writing an MSc project to further investigate the problem, and proposed a solution to tackle it. • The proposed solution used GA, among other things...Sunday, 17 February 13
  • 6. Step 4: Re-build the RMS • We rebuilt the RMS to tackle the issues the business was facing, as well as those that impacted customers. • We added a metrics system so we could record which returns were pending, due today, late etc, and help staff prioritise and hit KPIs.Sunday, 17 February 13
  • 7. Step 5: Plan event tracking • I made a spreadsheet of events. There were lots... • Why GA? Using GA would mean I could analyse and report on the data much more easily than I could if I had to write SQL queries to pull the data out of the RMS.Sunday, 17 February 13
  • 8. Step 6: Sent events in PHP-GA • There were too many events to send using the client-side code, so I used PHP-GA, which allows you to bypass the token bucket algorithm. • Primary keys in the events allow related events to be re-joined in the API.Sunday, 17 February 13
  • 9. Step 7: Set up reporting • The default Google Analytics dashboards were too limited to be of use for this problem. • So, we’re using Google Drive and the Google Analytics Core Reporting API “magic script” to create detailed reports.Sunday, 17 February 13
  • 10. We can now answer these questions on returns • What percentage of returns are handled on-time? • What is the average time to handle returns of different types - replacement, exchange, refund? • How many returns are unscheduled arrivals? • What are the return rates for different items, and why are they being returned? • What proportion of faulty goods are non-faulty? • How much working capital is tied up in returns?Sunday, 17 February 13