Marketing analytics for everyone

[LookerExperts]

This content, written by Dillon Morrison, was initially posted in Looker Blog on Jul 19, 2017. The content is subject to limited support.

It seems like 2017 is the year of marketing. User retention, ROI on ad-spend, customer lifetime value, predictive lead scores, purchase affinity: sophisticated analyses such as these are transforming marketing from a loosely quantifiable “art” to a strictly followed “science”.

But these types of analyses existed long ago - why the sudden increase in significance?

It’s no secret that the volumes of data that today’s companies gather are exploding. These oceans of data provide the opportunity to perform more exact analysis and track behavior all the way down to the individual user level. This means any marketer, from junior program manager to CMO, can easily understand what audience is seeing their ads, what types of ads and keywords attract the most valuable customers, how well each audience cohort converts, and much more.

Just a few years ago, collecting this depth and breadth of data would have been impossibly expensive. Nowadays, thanks to advances in data storage tools, if a company is not collecting and continuously analyzing all this data, it’s considered an outlier and risks falling behind.

Nearly every company that interacts with users or customers online uses the Google Marketing Suite1. Whether it’s an emerging startup sampling with free Google Analytics or a seasoned enterprise leveraging the entire ecosystem of reporting and analysis tools, Google has arguably become the most prolific marketing technology company in the market.

Performing analysis in Google Analytics, AdWords, DoubleClick, or any other marketing tool, provides a strong foundation for deriving insights from the vast quantities of customer data. But the data from each of these sources typically lives in it’s own separate silo - in its individual console or interface (read: another browser tab). To track performance across these tools, users typically download reports and manually reconcile them in Google Sheets or Excel, wait a month, and repeat.

"As a data-driven company, our marketers go deep to find trends and insights that help us take effective actions. As such, the range and sophistication of Looker’s Blocks, including their pre-built dashboards and reports, have the potential to become extremely powerful tools for our team.”
- Andrew Rabinowitz
  Data Ops Engineer, Blue Apron

On top of the restraints of living in a silo, conducting analysis directly in the UI of each data source prevents marketers from seeing raw, user-level data. Typically, all that’s available is daily or weekly aggregated reports, which winds up leaving the possibilities for deep analysis extremely constrained.

What if you want to follow the full event-stream of individual users? Or tie your marketing data to your CRM data to understand ROI on ad-spend? It’s just not possible without exporting the raw data out of the data sources.

Even with the sophistication of Google’s data collection, the dream of tracking performance in real time across all platforms and tools, and taking action on that data, requires a tremendous amount of developer knowledge and data engineering.

That all changed last March at NEXT ‘17, when Google unveiled its Transfer Service offering.

After following a few minutes of instruction in Google’s interface, data from each of Google’s marketing sources, can be piped into BigQuery in near real time. What’s nice about BigQuery - - is that it’s also completely configurable in Google’s interface, meaning anyone can set it up without prior knowledge or experience with databases. It’s all done quickly and easily, in a just a few minutes. Starting up just requires a Google Account.

While Google was developing Transfer Services, our team here at Looker got excited about the potential of what this offering could open up. Transfer Service removes the need to involve a huge engineering team or outsource months of work to move all the separate data into a place where it could be combined. The only step was piecing the puzzle of data together once it was in BigQuery.

That’s where Looker comes into play. As Google finalized Transfer Services, we worked closely with Google’s product team to develop - a pre-built suite of actionable dashboards and analysis - to plug directly into the data after it’s been dropped into BigQuery.

Looker takes all the data from BigQuery, intelligently understands how to link all the sources together, and gives users the ability to run any type of complex analysis or report across each marketing tool, whenever they need. We’ve worked companies such as Hearst Communications, BuzzFeed, and Blue Apron to take their data from raw sources to full data suites in a matter of days.

“Google’s BigQuery Data Transfer Service makes it easy for us to centralize all the data from DoubleClick for Publishers, Google Analytics, and other internal data sources. Looker’s Blocks will allow us to better make sense of that data, with the end goal of building intelligent and predictive products.”
- Esfand Pourmand   SVP of Revenue at Hearst Newspapers

With Transfer Service + Looker, any marketer can jump straight into analysis. No need to deal with disparate APIs, or even involve IT. Even for those companies that already have invested IT time and resources into manual ETL scripts, Transfer Service does the same thing for data engineers that BigQuery did for analysts - it removes the need to monitor and maintain complicated tech plumbing. You can free up those engineers to do more meaningful work for your business.

The argument for DIY structuring of a tech stack typically goes like this: constructing each individual component is helpful due to the higher degrees of control and granularity. In this case, Google is actually providing a better service, since they include all the possible data fields that would be available if the data was pulled manually and/or individually. This widens the breadth and depth of reports available, making it possible to perform complex analysis not typically available in the UI of the data source itself. This is, again, where Looker Blocks® shine.

Blocks not only provide the reports you’re already using in Google, they include additional value-add analysis, not possible without the raw data available through Transfer Services, such as:

• Tracking users across their lifespan of interaction
• Customer lifetime value
• Cross-source user retention
• Flexible user cohorting and segmenting
• Customizable period-over-period reporting
• Single or multi-touch attribution analysis
• Customized sessionization logic

On top of this analysis, users get the full advantage of Looker’s extensive platform. Users can schedule alerts or trigger actions based on time periods or events, change bid prices or keywords from within Looker UI, create custom dashboards and infinitely flexible cutting-and-slicing of all their data. Looker’s flexibility means that data from additional sources such as Facebook Ads, Hubspot, or even proprietary data systems so help business achieve a true 360 degree view of their customers.

Finally, every marketer can easily harness the power of big data in an easy-to-use, centralized interface. 2017 is the year of marketing analytics - make sure you’re equipped to keep up.

Interested in Looker + Google BigQuery Data Transfer Services? and get started in just hours.

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1. Kleiner Perkins Caufield Byers. "2017 Internet Trends Report." Dream Bigger — Kleiner Perkins Caufield Byers. N.p., n.d. Web. 07 June 2017.