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Matthias Bettag - Challenges for each the multi-channel, multi-device and multi-platform measurement

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Don't miss the next year of Marketing Festival Brno - http://www.marketingfestival.cz …

Don't miss the next year of Marketing Festival Brno - http://www.marketingfestival.cz

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  • 1. Multi-Channel, Multi-Device, Multi-Platform Measurement Marketing Festival Brno 2013 Matthias Bettag, Digital Analytics Consultant, Berlin @MatthiasBettag
  • 2. About me Job: • Self employed Digital Analytics Consultant and Certified Web Analyst™ Representation: • Country Manager Germany of the Digital Analytics Association (DAA) • Country Manager Germany for Mind Your Privacy (Spain) Conferences: • Co-Owner of the Discussion Conference DA Hub (ex XChange Europe) June 2-4, 2014 in Berlin • Co-Chair of eMetrics Germany , November 4-5, 2014 in Berlin • Vice Chair of the I-COM Conference, March 31-April 3, 2014 in Sevilla Education: Tutor of the „Award of Achievement in Digital Analytics” online course of the University of British Columbia
  • 3. Multi-Channel Measurement • Examples for different Channels: – – – – – – – – – – – – Search Engine Advertising (SEA) Organic Search Display&Banner Advertising Email Video Mobile Ads Social Media Ads + Links Portals Other Paid Links Radio/TV Ads Print Ads …
  • 4. Multi-Channel Measurement • Channel measurement is visit based – Customer journey across different channels? • Channels are traffic drivers – Quantity vs Quality?
  • 5. Multi-Channel Measurement Goals • CTR – CPC – CPM – CPP – PPO – ROI – – – – – • • • Awareness? Traffic? Purchases? Cost reduction (per order)? Overall RoI? CTR/CPC/CPM  Ad-Server CPP/PPO/ROI  Website Level of Segmentation is rather technical: – – – – – – – – Keywords Campaigns Referrers Time/Date Revenue Purchases, conversions Products, Landingpages …
  • 6. Measuring Goals per Channel • Campaign Tracking – Ensure ALL campaign links have the necessary parameters attached to the URL (after the „?“) – Campaign Tracking Link Example: Different variables, separator: & www.domain.com/page?cid=123&ref=abc&date=DMY&kw=xy www.domain.com/page?cid=123|ref=abc|date=DMY|kw=xy Landingpage Campaign ID Referrer Date from/to Many other parameters are possible (Banner sizes, types, ..) Challenge 1: Consistency and accuracy across all campaigns Challenge 2: Report configuration can become complex Keyword (set) One variable with different attributes
  • 7. So, this gives me superpower?
  • 8. Moving beyond „simple“ campaign traffic analysis • Define (real business relevant) KPIs across all platforms • Define how your KPIs apply to each platform • Categorize campaigns by their goals • Establish a common understanding across all stakeholders • Start thinking about customer analytics
  • 9. Solving Multi-Channel Measurement • Customer Segmentation: – Personas / Target Audiences? – Identifiable by their online behavior? – Create visit segments (use cases) – Create visitor segments (user behavior)
  • 10. Let the Barcelona Food Market explain Segmentation.. Amount – Turnaround – Conv.Rate Occasional buyer Bulk buyer for restaurants Amount – Turnaround – Conv.Rate Amount – Turnaround Regular buyer for own household – Conv.Rate MS-Aida tourist on a shore leave.. Amount – Turnaround – Conv.Rate Buying lemons Buying onions Buying tomatos Buying pears
  • 11. Multi-Device Measurement • A user is using multiple devices on a customer journey: – – – – – – – Desktop PC (e.g. at work) Laptop Smartphone Tablet Playstation, Xbox, etc. Smart TV … Source: www.broadwayworld.com/bwwgeeks/article/Users-Weighed-Down-byMultiple-Gadgets-and-Mobile-Devices-New-Sophos-Survey-Reveals-20130314 CAGR = Compound Annual Growth Rate M2M = Machine to Machine Communication
  • 12. Solving Multi-Device Measurement • Perfect solution: Use a mandatory login. • Even better: Providing Hardware and Platforms! – Google, Apple, Microsoft, Amazon, .. • „Closed communities“ (only platforms) are in advantage – Facebook, Ebay, large portals, .. • Really hard to measure users across devices otherwise
  • 13. Methods for Customer Analytics Two examples: 1) Drawbrid.ge uses massive amount of (3rd party) cookies and e.g. matches devices by time and location  calculated approximity, but obviously working well enough 2) Lytics.io – System starts low and learns over time by connecting dots and pieces together, e.g. by: • Cookie backmatching • Campaigns with unique userIDs, then tracking visitors and tying identities together • Matching-Algorithms inside a system • CallToAction via Twitter results to connects a social profile to a web profile • Similar with Mobile App to Web Without such sophisticated systems: • Providing a personalized user experience helps to bridge cross device usage seamlessly (provide a strong benefit for a log-in) • Generally, a good visit-/visitor segmentation is already helpful to optimize per platform/device
  • 14. Multi-Platform Measurement • • • • • Own Website(s) Mobile Websites Mobile Apps App Stores Social Media Platforms • • • • External Portals (e.g. Aggregators, Communities) Gaming Platforms Widgets embedded in third party websites …
  • 15. Better Multi-Platform Measurement • What purpose does each platform have? – Lead generation, Traffic driver, Research and information, Mobile/local services, Purchases, Rating, none really.. (but the competitor is there, too), … ? • How does a platform contribute to a business goal? • Assign appropriate business KPIs (per segment) to the different platforms
  • 16. Measure the user experience, not each silo by ist own • Track one user experience into one reporting suite: If a website includes different platforms (e.g. general global structure and local content in frames) track visits and visitors across the platforms without duplication • You‘ll probably need to customize the main JS-file and have to inherit VisitorIDs across platforms • Debug, Debug, Debug!
  • 17. More silos: Using 3rd Party Trackers? • Think of moving from 3rd party tracking to 1st party tracking – And be prepared to lose ~90% of data tracked by 3rd party tools with the upcoming EU privacy regulation Your 3rd Party Trackers
  • 18. Sky-Level: Ready for strategical #CRO? • Understanding your conversions across all these “multi-multis” is hard! • An attribution model helps to: – – – – Understand the different touchpoints of a user journey Understand a touchpoint‘s impact on the user behavior Understand how touchpoints influence Optimize marketing spends • Consider a Tag Management Systems (TMS)..
  • 19. TMS: Solving Data Inaccuracy • Data inaccuracy caused by: – – – –  Users deleting cookies Users on multiple devices Missing offline campaign tagging „Dark social“ TMS benefits: Multi-channel management at a glance  Double tracking to end system and TMS  Rule engine to configure firing rules in very detail 
  • 20. TMS: Solving Data Duplication • Data duplication caused by: – Channels measured in silos – Problem: Multiple affiliates/channels claim for the same conversions  TMS benefits:  Data-deduplication and allocation of actions per touchpoint  Clear picture of conversions by channels at a glance
  • 21. TMS: Solving Insufficent Control • Insufficient control caused by: – No access to source code – Results in long cycles for updates/changes/adaptations • TMS benefits: – Direct configuration of tags via the TMS – Rule engine helps to customize firing rules per tracker individually – Provides individual level of control to the different stakeholders
  • 22. TMS: Managing Privacy Processes • Users need detailed explanation about all Trackers and the purpose of data collection • Avoiding unwanted data • TMS benefits: – Managing User Consent – Control of Datastreams Source: British Telecom
  • 23. TMS: Solving Lack of Processes • Lack of processes caused by: – Missing Hub&Spokes model – Friction between Marketing, Analytics and IT causes delays  TMS benefits:    A Data Layer model enforces a tagging documentation and by this transparency for all stakeholders Each stakeholder can focus on the respective area of responsibility and act independentely Much quicker reaction time for any changes/updates
  • 24. Too complex? In fact, that‘s so 1977.. Screenshot from “James Bond 007 - The Spy Who Loved Me” (1977)
  • 25. Summary • Segment your audience and their intentions • Map KPIs to business goals • Rely on your own data! – .. and make sure you‘re allowed to use it.. • Try hard to understand your customer‘s decision making behaviors • Tools help, but governance is on you!
  • 26. Thank You! Matthias Bettag Digital Analytics Consultant DAA Country Manager Germany MindYourPrivacy Country Manager Germany matthiasbettag@gmail.com @MatthiasBettag de.linkedin.com/in/mbettag/