The Rise of the Analytical CMO - DataScienceCentral.com

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In the post-Covid era, organizations are recalibrating their marketing strategies to make better use of data and analytics to stay ahead of the competition. Increasingly, it is the Chief Marketing Officer (CMO) who has to take the lead to drive digital adoption and become the organization€™s digital evangelist. Data is everywhere and the CMO is increasingly expected to use multiple sources of data analysis and marketing intelligence for growth and revenue.

Customer buyer journeys changed significantly during the pandemic: Buyers prefer to undertake a self-education journey, learning about the product rather than engaging with a salesperson right from the start. This puts the onus on marketers to provide prospective customers with the right content at the right time via the right channel.

Also, as the Wall Street Journal reports, ad spend has shifted to digital with Google, Facebook and Amazon getting half of all US ad spend. Additional research by the Interactive Advertising Bureau and PwC indicates digital advertising grew by 12% year-over-year. With a surge of customer data available, CMOs had to respond to changes in the market in hours and minutes, not in days or weeks. To succeed in this dynamic environment, CMOs have made the shift to becoming more analytical. They now have a multidisciplinary toolbox of skills €” including experiential, creative, and analytical, to gain insights to shape data-driven marketing, and business strategy. Data is a vital part of driving growth marketing.

Every organization wants data-driven marketing and marketing leaders are faced with a flood of new customer data and insights that they are expected to use to shape their strategy. To see how this plays out in real life, take a look at wheelchair accessibility company Braunability: They were previously dealing with siloed data that was not easy to share and did not generate meaningful intelligence. With the help of the right BI solution, they were able to integrate sales, marketing, and logistics information to plan their promotions and new campaigns and evolve their marketing program. As marketing (in every industry) continues to change, becoming increasingly data-driven and with tighter and tighter margins, every CMO will be looking to up level their organization with the right actionable intelligence, delivered to the right users at the right place and time. Choosing a powerful analytics platform that can connect to disparate data sources and infuse insights into user workflows will be an important way companies separate themselves from their competitors and ultimately improve their marketing performance.

Traditionally, the CMO had a creative mandate to think about how best to connect with customers. Decisions were mostly gut-driven and based on historical data. Today€™s CMO must combine their creative thinking with marketing intelligence that reveals not only which ads convert best, but also customer triggers, unmet needs, and affinities which can unlock new opportunities.

A McKinsey survey of over 200 CMOs and senior marketing executives revealed that marketers who combine data and creative thinking drive more growth than those who don€™t. The top-performing marketers consistently integrated four or more insights on average into the process of improving customer experience instead of the traditional approach of using analytics as a distinct and separate process.

Infuse intelligence from multiple sources into workflows to drive data adoption

Customer data resides everywhere, but it may not be in the most obvious of places. Chatbots, social media, voice search €” these new sources of textual data contain valuable but untapped insights. The use of artificial intelligence in marketing, specifically natural language processing, can convert this rich textual data into valuable customer insights. When done right, it can give CMOs a significant competitive advantage: According to the Sisense-commissioned IDC Internal Analytics Survey 2020, 78% business leaders are already using AI in their BI tools, and the rest plan to start using it in the near future; 38% users are looking for a solution that offers natural language queries. Savvy CMOs who are already using artificial intelligence in marketing use it to track granular details of their customers and campaigns to optimize in real-time.

Analytics from this wide array of sources can be the CMO€™s best friend when it comes to things like measuring ROI on marketing spend and other important KPIs. Building an analytics-driven team and culture is vital to that mission but going back to the IT team for insights repeatedly wastes time.

The solution: Infuse analytics into workflows. This bridges the gap for marketing teams by providing self-service, shareability, and real-time updated data right where and when users need it, without leaving their usual tasks to hunt for intelligence. According to the IDC survey, 61% of business leaders say incorporating analytics into their existing workflows is one of their biggest objectives while choosing third party solutions.

Bring customer insights to the C-suite to influence strategy

Challenges provide tremendous opportunities to grow. As organizations face fast-changing customer expectations due to Covid, it is the right time for CMOs to evolve their role. They can bring their analytics-driven customer insights to the boardroom to prove marketing€™s measurable and strategic importance and help influence strategy.

To achieve this, a strong foundation of analytics is essential. With the right analytics solution, infused seamlessly into workflows, marketing leaders can develop an analytics-driven culture that leads to optimized campaigns and improved KPIs and ultimately impacts revenues. An agile analytics infrastructure is key to evolving your business.

Ashley Kramer is a senior executive with over 15 years of experience scaling hypergrowth companies including Tableau, Alteryx, Amazon, Oracle, and NASA. She has a strong track record of transforming product and marketing organizations and effectively defining and delivering the end-to-end product strategy and vision. Ashley is passionate about data, analytics, AI, and machine learning.