About Lukas Oldenburg

Lukas Oldenburg is a Digital Analytics Specialist with 12 years of experience in the field and works as a freelancer in Switzerland and Germany.

Before deciding to start his own business, he was the Head of Analytics & BI at siroop, an ecommerce online startup in Zurich, Switzerland, founded by Swisscom (Swiss Telecom) and the large Swiss retailer coop. Earlier, Lukas was a Senior Consultant for Digital Analytics at Unic, one of the largest Swiss-based E-Business specialists.

From 2006 to 2012, Lukas worked as an editor-in-chief and webmaster for e-fellows.net, the German career network, online scholarship and recruiting company owned by McKinsey & Co. and DIE ZEIT.

He has planned and rolled out several complex data setups, using mostly Tealium, Google Tag Manager, and Adobe DTM as the Tag Management System and Adobe Analytics, Google Analytics and Webtrends as the Analytics tools. His experience goes beyond Web Analytics and Tag Management however, having been the driving force behind several Business Intelligence initiatives as well.

Lukas originally hails from the Black Forest in South West Germany and graduated in Cultural Sciences from the European University Viadrina in “the other” Frankfurt on the German-Polish border. He loves languages, speaking seven. In his freetime, he plays the piano and follows NBA basketball.

Find Lukas on Twitter, Google+ or LinkedIn. Read Lukas’ Latest Articles.

Testing Tealium Universal Data Hub: How We Used Visitor Stitching and Salesforce Connectors

June 12, 2018 by Lukas Oldenburg Leave a Comment

Image of spiderweb with title text Tealium’s “Universal Data Hub” (UDH) claims to be a central place for acting on real-time customer behaviour data. The promise: Get customer data into the “Hub” from anywhere, enrich it via rules, have it stitched and join it with data from other sources, and then send it server-side to wherever you need it, via connectors or APIs.

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Testing Tealium’s Dynamic Data Layer Management (Product Data into Google and Adobe, Part II)

November 14, 2017 by Lukas Oldenburg Leave a Comment

Part 2 of “Get more Product Data into Google or Adobe Analytics“

The more product data, the more work for developers, the heavier your Data Layer. Tealium’s “Dynamic Data Layer Management” promises to ban at least the developer part forever. The idea is to enrich your Data Layer in real time with data (like “best-price” labels) that is hosted somewhere outside on a CDN. It has huge potential and is something you cannot do with a other Tag Management Systems. But does DDLM live up to its promise? We tested it.

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Get more Product Data into Google or Adobe Analytics, Part I: Classifications vs. Dimension Widening

October 31, 2017 by Lukas Oldenburg Leave a Comment

In an E-Commerce company, work revolves around product data. That does not only apply to search filters, bidding strategies and on- and offsite advertisement, but also to data analysis. Do our best-price products really convert better than the rest? Which price ranges are we selling the most in our wine section?

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localStorage vs. Cookies for Analytics Implementations: What You Should Know

September 26, 2017 by Lukas Oldenburg 2 Comments

localStorage has long established itself as a wonderfully comfortable way to store data in the user’s browser. Many tracking implementations depend on it.

But it is not the best solution for all cases, as 7-8% of users block it (on our site at least).

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Marketing Cost per Channel is Harder Than You Think (Google and Adobe Analytics)

February 14, 2017 by Lukas Oldenburg Leave a Comment

Image of ocean channel with title text The “Marketing Channel” is the main entry point for any analysis on digital campaign performance in today’s Web Analytics world. But how good is a channel if you can only see how much money it earned you, but not how much you spent on it?

Both Google and Adobe Analytics do not make it easy here.

While there is no way to get the cost per channel into Google Analytics apart from the context of the Multi-Channel Funnel Reports,, Adobe offers a somewhat hidden trick. And you can go full circle: Cost->Revenue->Refunds = the real ROAS.

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