Data Is Eating The Enterprise

Many enterprise CIOs struggle to keep up with the unprecedented rapid growth of data, most of which is unstructured. In addition, they are being asked to leverage this data to unlock and provide true value to the business, both internally and externally.

Modern CMOs already understand the value of rapidly interpreting the constant deluge of data into actionable insights, and if CIOs want to avoid the transition of power to the CMO, they will start taking a proactive approach to managing and leveraging their multitude of data sources, learn to effectively collaborate with the CMO with technology and data strategy, and rapidly take advantage of the incredible advantages of AI and machine learning to support marketing initiatives.

Customer Data Sources

One of the main challenges that CIOs face is the disparate data “silos” that exist within every enterprise. Many attempts to consolidate these into a “data lake” unfortunately have resulted in a “data swamp,” since the effort was approached tactically instead of strategically by leveraging a data analytics platform.

The modern enterprise has a vast amount of unstructured data from customer behavior and actions. In addition to this internal customer data challenge, many enterprises also have external data, from both customer and third party sources, which often presents a significant challenge in areas such as cross-channel identification. Regardless of the source, in order to provide true value back to that customer this data needs to be analyzed and leveraged. One way to think of this is being able to target your individual users with personalized options. The ability to provide this takes “consumerization of IT” to the next level.

CIO<->CMO Collaboration

CIOs and CMOs need to band together and collaborate on technology and data strategy. The end goal should be driving revenue for the business, instead of an internal power struggle. I’ve spoken quite a bit in the past on this, including this interview.

The relationship between the two leaders should be simple, direct and transparent. CIOs should first work to deeply understand the strategic initiatives of marketing, and then recommend and implement the correct set of technical solutions that enable the CMO and team to fully leverage their various data sources. CMOs need to continue to communicate on how the solutions are working, and also keep the CIO updated on any new requirements. One way of thinking about this is to adopt the “culture of DevOps” where the core tenets are: Collaboration, Automation, Measurement, and Sharing (CAMS).

Rise Of The Machines

With the number of disparate data sources increasing at a rapid pace due to the deployment of sensors and the overall IoT movement, marketing data science and analytics teams simply can’t keep up with the continuous processes of identification, unification, cleansing, and enriching. Advances in machine learning and artificial intelligence are driving innovative solutions that allow for rapid integration of all data sources, self-service analysis, and detailed visualization. Platforms that allow for adaptive integrations and flexible insights will be the ones that will be most attractive to both CIOs and CMOs. Data sources need to be continuously augmented and enriched, instead of the legacy process of performing this only once, using platforms that are enabled by AI and machine learning models.

That’s where ZyloTech, formerly DataXylo, an MIT spin off, and a MIT CIO Symposium 2016 most innovative startup showcase finalist comes in. MIT spin off, ZyloTech is an award-winning AI-powered customer analytics platform designed to help enterprise Retain and monetize their most precious asset — their existing customers.

The ZyloTech platform uses machine learning to solve data quality issues and analyze all customer data continuously and in near real time for superior insights in support of omni-channel marketing operations. In a marketing world where improvements are measured by small percentage points, ZyloTech clients have frequently reported a 4–6X lift in customer retention and monetization efforts.

Originally published at on April 4, 2017.