19December 2021the most powerful enemy: with human habits and previous experience.Data-driven implementation steps:1. Configure and integrate your 1st party data with digital buying environments (Facebook, Google Ads, DSP platform, SMS sender, email sender, telemarketing tool, web CMS, etc.)2. Unify channel grouping in Google Analytics and build rules for proper incoming traffic descriptions (standardized utms, etc.)3. Enrich tracking with impressions and click trackingThere we have to use Google Campaign Manager if we want to have a chance to bind it with Google Analytics traffic. So, it is worth having your own Google Analytics 360, Google Marketing Platform including Display and Video 360, Campaign Manager for traffic all possible to track events.We can use another solution like Adobe, but it will be much more expensive, and we have to decide on one traffic and impressions/click tracking solution.1. If we are using a lot of internal channels like emails, SMS or telemarketing, then it would be great to inform our Google Analytics 360 about contacts like email sent, SMS sent, call done. We can easily do that with Google Measurement protocol and most of SMS / email / telemarketing tools already have webhook functionalities to inform Google about these events (combined with client-ID).2. Build data driven attribution based on Markov chains, consider internal channels events (email, SMS, call). To improve data quality install Google Ads Data Hub which will allow us to consider also non-converting paths. Be aware of some model limitations (can't consider impressions from Facebook, from Affiliate channels, from organic traffic, etc.)We can build it with external agency's help or we can use our own BI department.The place we can merge/link/bind these data is Google Marketing Cloud with their Big Query. It is a very flexible and perspective environment, with proper data structure we will be able to build our own machine learning algorithms for many different purposes, like predicting client's behavior, their willingness to buy or sensitivity for discounts.1. Build media investment cost data storage with daily updates 2. Again easy to write, much harder to implement for many markets (it took me several months and still improving).3. Build and share unified reporting with last click non Summarizing, we did a lot to implement data driven attribution and we finally have constantly reported results with this approach
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