Trader Corporation’s online sites, mobile applications and print publications comprise Canada’s largest automotive marketplace. Trader’s online properties - autoTRADER.ca, autoHebdo.net and Autos.ca - are the leading online automotive marketplace and advertising platforms in Canada.
Tag Management with Google AnalyticsWith pages dynamically generated based on search requirements, user submitted ads and more, Trader Corp was torn between purchasing, installing, and maintaining an expensive solution or missing out on large chunks of data. Our Google Analytics audit revealed a solution: a custom tag-management system that enabled new ways to analyze their data while incorporating a familiar interface.
The ChallengeTag management is a serious issue for companies with large, dynamic sites. Trader Corporation, whose sites are founded around complex page structures (customizable by data such as car colors, years, models, and more) wanted to understand how user search patterns, advertising viewership, and willingness to buy are linked.
Given their various advertising methods and the extent of both their search and site options, Trader had hundreds of thousands of URLs. So many, in fact, that the cost of paid analytics solutions would be enormous, but that free solutions such as Google Analytics - their chosen platform - would be unable to analyze due to the sheer amount of data.
Instead of seeking out vendors of expensive tag management solutions and complex analytics suites that require significant investment of time, resources and budget, they approached Cardinal Path.
The SolutionWe worked with Trader Corp to create a customized tag management solution for Google Analytics using a system of virtual pageviews. Our web analytics team set out to create a customized “virtual page structure” which classified pages by categories such as ad details, advanced search and keyword search, and grouped them into sets - the loading of which would trigger a custom pageview recorded to Google Analytics with all the detailed classifications necessary for clean analysis.
The ResultsTrader received a completely new way to think about their data, with analysis options far beyond what would be available using a standard pageview model. Using this revised analysis model, Trader was able to see more than just ad conversions from a page.
They gained knowledge about their users, including the impact of photos, videos, keywords and number of viewed ads – all without sacrificing accuracy, depth of detail, or platform familiarity. Not only was Trader Corp able to avoid the time and financial investments in unnecessary technology, they were able to collect and surface actionable data, enabling a new depth of insight and analysis.