Blurred Lines Between Analytics and Technology

CRM Analytics and Technology

The Quest

Years ago I became very interested in technology as a frustrated analytics guy. I wanted analytics processes for CRM to run faster. I wanted an analytics system that could keep up with my train of thought and the iterative questions I would ask while mining through data, conducting analysis, and generating insights to inform marketing execution. I did not want constraints on space or performance and throughput simply because data got BIG! As a result I started seeking enabling technologies that could better enable CRM analytics. 

While on this quest, I’ve often been amazed at how differently analytics and technology people think about the work, how they approach it, and the often-strained attempts at collaboration across these two disciplines. And I’ve witnessed epic misses (a.k.a. failures) where analytic and technology capabilities should have come together but could not work in an integrated fashion for the greater good of CRM enablement. These missed opportunities were usually plagued by:

  • Lack of data access for analytics
  • Issues with timeliness and accuracy of data
  • Lack of agility through tools and processes
  • Misalignment around the strategic application of data and analytics resulting in the cross discipline team (tech and analytics) rowing in different directions
  • Little to no discipline around operationalizing where analytics gets embedded in the CRM ecosystem and contributes to marketing at scale

It left me wondering, why can’t technology and analytics be more integrated?

Eureka — The Lines Are Blurring

Thankfully there have been dramatic innovations over the years. Fast-forward to today and it’s exciting to see marketers using new, innovative ways to enable CRM analytics. The lines are blurring between advanced analytics processes and the available technology to enable those processes for CRM. We are seeing technology-enabled analytics solutions emerge that support CRM enablement at scale. Dedicated analytic platforms are emerging that are designed to leverage insights to enable broad scale CRM programs and measurement.

Here are a few examples of technology innovations that are enabling analytics for CRM:

  • Creation of holistic consumer profiles by combining known and anonymous data (direct channels, digital media, and mass media data) into individual event streams that sequence the chronology of consumer interactions — a Holy Grail for analytics profiling enabled by digital tracking and identity management technologies. This is data fuel for things like cross-channel attribution
  • In-database analytics for modeling and scoring processes; enables efficiency gains by eliminating extracts and data movement. Supports automation, making analytics operational, part of the CRM ecosystem, and embedded as opposed to an exercise done in isolation. A great example where database technology is enabling analytics.
  • Handling big data tasks with agility using Hadoop technology. This supports wrestling with massive datasets such as digital display impression and search log files. And leveraging powerful analytics tools within this technology is a reality today (check out what Revolution R Enterprise is doing with Hortonworks sandbox).
  • Flexible visualization capabilities for dynamic and interactive dashboards. Finally, technology exists to allow analytics, non-technical users to configure the user experience for consuming insights (check out Tableau).
  • Model scoring extensions through PMML to enable analytic models to be leveraged in a distributed fashion (check out Zementis as an enabling technology). This opens up integration opportunities. Analytic models can be used for real-time scoring and to contribute to strategic marketing executions like personalization to drive differentiated marketing treatments (e.g., websites).
  • Machine-learning algorithms that can learn from and make predictions on data.

The fact is you can’t do analytics at scale today without technology enablement. The digital evolution and resulting big data phenomena is the reason. And without enabling technologies like the things described above, analytics will not be efficient and timely enough to be relevant to the business.

The Data Scientist

Today’s CRM requires a different kind of analytics enablement to keep up with the speed of business, the change velocity, and the C-suite demands. 

We see the emergence of the modern Data Scientist. An empowered individual who uses these new technologies, leverages analytics know-how, and has the business acumen to apply insights that impact marketing outcomes.  

And clients are demanding this level of support. I recently engaged with a CMO who had reached a point of realizing a big change was necessary around analytics enablement in the organization. This CMO said ...

  • “I need a different kind of analytics”
  • “I need data scientists focused on CRM…not just statisticians”
  • "I need cross-channel insights to enable forward looking media & channel optimization”
  • “I need timely access to insights”
  • “I need my analytics to be integrated with other CRM capabilities”

In Summary

Does the alliance of technology and analytics seem peculiar on the surface? Are analytics and technology strange bedfellows? Not at all ... not anymore! The marriage of technology and analytics actually makes a beautiful union.

Yes indeed, the times are changing. The lines are finally blurring between technology and analytics. It’s a great time to re-imagine the possibilities. The opportunity to leverage data-driven CRM using technology-enabled analytics as a core driver has arrived. This represents a new call to action for us marketers.

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