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Harnessing volumes of data for marketing analytics for Chief Marketing Officers (CMOs) can provide actionable insights that help drive highly targeted marketing campaigns. And when we are talking about data, we also mean technology. In order to get the customer facing technology in place with the backend data analysis and AI insights coming together, the CMO and the CIO are forming partnerships. They both share goals to improve profit and working together they can manage costs, technology and expectations.

First, know your customer journey

To help inform smart marketing tech investments, CMOs should gain a comprehensive understanding of the customer journey from initial awareness to purchase, through to an ongoing relationship between the customer and the brand. Consider such questions as:

  • Where can technology improve the efficiency of marketing operations?
  • Where can you automate the buying journey to deliver a better customer experience?
  • Where can you deliver customized offers to increase revenue?

While your organization may capture transactional data from every point in the buying journey, it’s time to think more broadly. For more valuable insights, you’ll want an integrated marketing tech solution that synthesizes structured and unstructured data from many sources into a single view of the entire customer lifecycle. In this way, you’ll be better equipped to understand how customers interact with your company across all channels (e.g., email, phone, print, social media, etc.), and which channels may be more profitable.

With full visibility into the customer lifecycle, CMOs can identify numerous ways to segment customers to deliver the right offers at the right time. They can also more effectively partner with other lines of business on strategies to improve customer experience at every touch point. And CIOs will have visibility across those other groups to help create synergy within the company.

Think like a CIO

Once you understand your customer journey and have pinpointed opportunities to segment customers for targeted marketing, you can assess where marketing technology can make a bigger impact, such as driving lead generation or increasing revenue. That’s where the CMO really starts thinking like a CIO. And some companies that recognize this importance have created a new C-level role: the Chief Marketing Technologist.

Collaborate with your IT partners to choose technology that will complement your strategy, rather than creating a strategy to suit your technology. For example, suppose you’re trying to increase engagement using video content–what’s the best channel for that strategy? Here are a few key considerations:

  • Plan for a comprehensive view by choosing technology that can aggregate and analyze structured and unstructured data from many different sources (e.g., transactions, registration data, call center transcripts, social media, surveys, etc.), and deliver insights in a single, integrated view.
  • Leverage existing IT environments and look for opportunities on how they can complement any new marketing analytics technology to optimize data collection from all points in the customer journey. Consider ways to integrate multiple systems to form one, more complete customer record.
  • Create an implementation roadmap that prioritizes the technologies that can improve marketing operations or make you more competitive. Work with the CIO and IT team to develop timelines that work for everyone involved.

The big data advantage

Data is a powerful resource, and data science and AI predictive analytics provide the keys to unlock actionable insights that can drive measurable ROI in your marketing efforts. It’s a competitive advantage that CMOs can’t afford to be without. Today’s CMO can create a valuable bridge between marketing and IT if they develop the right CI relationships. Both groups can benefit from skills and knowledge to provide effective input into technology decisions. Their deep understanding of the buyer journey can help teams assess the technology needs for critical stages in the customer lifecycle.

Johnson Controls is using AI to reduce churn and identify over $100M a year of protectable revenue


Johnson Controls had no usable data sets, no data science team or data engineers.

How could they rapidly build a global data team with new AI/ML capabilities to improve business outcomes on a major scale?

Is your company struggling with how to implement predictive analytics?

Last updated: February 06, 2024
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