Leveraging Data Warehousing 2017-11-09T09:15:38+00:00

Key to Analytics: Getting your House in Order

At the core of the Invertible technology is the Data Hub.  In its simplest form, The Data Hub is a cloud based data warehouse designed to consolidate multiple data sources into a single repository.   There are many benefits to owning a data warehouse, such as single source of truth, reporting efficiencies, historical tracking; the list goes on.  But to a marketer, the greatest benefit is consumer transparency.

While there is inherent value in data, signficant value is created by constructing disparate data sources into a single view; connected at the most atomic level, the user level.  This connection gives marketers a full view of consumer behaviors across paid, earned, owned media, and offline (CRM), enabling learnings that would not be realized from a single data source. One example demonstrating a data warehouse’s value in this respect is enabling accurate measurement of digital media to offline sales.

Real estate developers, retailers, medical centers, and many others face the common problem connecting digital media to offline sales.  In the absence of a good solution, advertisers optimize to online micro-conversions, which often are not representative of offline purchases.   This myopism leads to media inefficiencies and demand truncation.  However, through an advanced measurement setup and a data warehouse, organizations can resolve this problem.  Organizations can setup pixels to generate user IDs during a user session and pass them to the various data sources, where a data warehouse can then process this data to integrate the web analytics, CRM, and paid data sources at the user level.  Through this implementation, organizations can directly attribute offline sales to media to significantly improve optimization efforts.

One case study shows how a real estate developer became more profitable by optimizing to offline sales.  When comparing paid search keywords from the lens of both online and offline conversions, there were stark differences in profitability.  While one keyword had 48% fewer online conversions, it drove 47% more offline revenues.   As this advertiser shifted optimization to offline sales, budgets started to increase for non-brand keywords.  These early funnel keywords were found to be profitable, and so increasing the budgets led to new demand and revenues growth.  Over time, as this advertiser leveraged its data warehouse to optimize media, total sales increased by +16% YOY, while spending 30% less in media spends.

As demonstrated, data warehouses can increase a marketer’s ability to draw insights and make better marketing decisions.  Traditionally data warehouses have been used for reporting and analysis purposes, but there is opportunity to expand its application.  With the digitization of media channels and proliferation of data science, organizations can mine user behaviors using econometric models to better understand their consumers.  With the growing prevelance of machine learning algorithms and their application in marketing, we can expect to see the next generation of data warehouse integrations to analyze marketing behavior real time, segment customers, and control media efforts through API integrations — also known as Big Data.