Digital transformation. Yup, I said it. It's over-hyped, but it's also real and powerful. While our customer-obsessed world is being liquefied from physical assets into virtual assets, and analog processes into digital processes - the world is turning into data. Into bits and bytes...
As this trends evolves, the role of analytics is not changing. Simply put, it is to derive insight from data. But what is changing in light of digital transformation is the importance of data and analytics. It now has an expanded and strategic role. Quite frankly, i's a requirement.
Many brands are finding themselves in unfamiliar territory. Generally speaking, analytical software feels like it is becoming commoditized. The technology landscape has shifted to cloud companies with seemingly unlimited resources and appetite. The building blocks of technology are changing quickly. Innovation cycles are now measured in weeks and months, not years.
Brands operating in unfamiliar territory can benefit from having an internal compass. A built in GPS, if you will. As an analytics technology company, SAS has this. It is called:
The Principles of Analytics
It informs our approach to data, analytics, and martech. They manifest in our Customer Intelligence 360 software offerings. Their fingerprints are everywhere. Let's walk through the four principles.
Data without analytics is value not yet realized. Today, more diverse consumer data is generated and available to all of us. The first principle is about bringing the right analytical technology to the right place at the right time, whether it is on-premises, public, or private cloud. Thus, this principle manifests itself in pushing both autonomous and customized analytical assets aggressively into our capabilities that support micro-moments of opportunity during a customer journey. Integrating analytics with cloud storage and computing, while architecting our hybrid software solutions to support cloud-native and on-prem environments. And an increased emphasis on data quality, privacy, and security.
We have always paid attention to the quality, robustness, and performance of algorithms. It's no surprise that we love math. But the value of analytics is not in the features and functions of the algorithms. Not anymore. The value for the marketing team is in solving data-driven business problems.
Everybody has algorithms in 2020. But operationalizing analytics is not a commodity. Everybody has challenges in bringing analytics to life. Data science teams are no longer measured by the number of models or algorithms they build. They are measured by the business value they generate. Analytics needs to be enterprise-grade:
The integration of the end-to-end analytical life cycle with no-code, low-code, and high-code interfaces supporting both SAS and open source languages addressing different roles with unique needs.
How does this second principle manifest itself within Customer Intelligence 360? Here are two topics with applied use cases to dive into:
If data analytics plays a strategic role in digital transformation, then brands will not benefit from the impact of this modernization effort unless analysis can scale beyond data science teams. Lower tiers of the analytic skill pyramid need to be enabled because they in turn have more domain knowledge. The democratization of analytics is an element of the larger trend within the democratization of technology.
This principle unfolds itself within SAS through technology for visualization, augmented analytics, automation of data management and machine learning, and autonomous AI supporting the marketer's daily tasks and processes. Examples of Customer Intelligence 360 applications inspired by this premise include:
Don't care to read more text? Check out a live demo recording highlighting use cases of this principle coming to life.
Let's transition to the final principle.
At SAS, we see everything through the perspective of data and analytics. Within Customer Intelligence 360, if it does not boil down to one of the following areas of customer engagement:
Then the question is outside of our competency. As an example, we are in the customer intelligence space to improve marketing through analytics and optimization, not to run email campaigns. However, we run email campaigns improved and informed by analytics and optimization.
Lastly, we cannot rest on our laurels and assume analytics in general is a differentiator. Access to analytics is no longer unique. Getting value from analytics is. An analytical platform is not a difference-maker, but analytical solutions for improving customer personalization and targeting is.
Conclusion
Allow me to close with a summary of the design principles for SAS Customer Intelligence 360, where the technology is intended to resemble the anatomy of the human brain. There are two distinct hemispheres.
The left hemisphere is associated with analytical, logical, and fact-oriented thinking. The right side is associated with creative, intuitive, and visual thinking. This translates to the following factors:
Together the intent is to better understand and manage customer activity, regardless of channel, in alignment with a brand’s goals and objectives. At the end of the day, both the analytical-minded and the creative-minded need to be in lockstep with one another. This is how the whole-brain approach of SAS Customer Intelligence 360 works.
To learn more about how the SAS platform can be applied to other marketing and customer-centric use cases, please check out additional posts here.
This article was inspired by SAS COO & CTO Oliver Schabenberger.
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