3 Ways Machine Learning Is Revolutionizing Marketing

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Measuring marketing’s many contributions to revenue growth is becoming more accurate and real-time thanks to analytics and machine learning. Knowing what’s driving more Marketing Qualified Leads (MQLs), Sales Qualified Leads (SQL), how best to optimize marketing campaigns, and improving the precision and profitability of pricing are just a few of the many areas machine learning is revolutionizing marketing.

The best marketers are using machine learning to understand, anticipate and act on the problems their sales prospects are trying to solve faster and with more clarity than any competitor. Having the insight to tailor content while qualifying leads for sales to close quickly is being fueled by machine learning-based apps capable of learning what’s most effective for each prospect and customer. Machine learning is taking contextual content,  marketing automation including cross-channel marketing campaigns and lead scoring, personalization, and sales forecasting to a new level of accuracy and speed.

The strongest marketing departments rely on a robust set of analytics and Key Performance Indicators (KPIs) to measure their progress towards revenue and customer growth goals. With machine learning, marketing departments will be able to deliver even more significant contributions to revenue growth, strengthening customer relationships in the process.

The following are 10 ways machine learning is revolutionizing marketing today and in the future:

    1. 57% of enterprise executives believe the most significant growth benefit of AI and machine learning will be improving customer experiences and support. 44% believe that AI and machine learning will provide the ability to improve on existing products and services. Marketing departments and the Chief Marketing Officers (CMOs) running them are the leaders devising and launching new strategies to deliver excellent customer experiences and are one of the earliest adopters of machine learning. Orchestrating every aspect of attracting, selling and serving customers is being improved by marketers using machine learning apps to more accurately predict outcomes. Source: Artificial Intelligence: What’s Possible for Enterprises In 2017 (PDF, 16 pp., no opt-in), Forrester, by Mike Gualtieri, November 1, 2016. Courtesy of The Stack.

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SOURCE: ARTIFICIAL INTELLIGENCE: WHAT’S POSSIBLE FOR ENTERPRISES IN 2017 (PDF, 16 PP., NO OPT-IN), FORRESTER, BY MIKE GUALTIERI, NOVEMBER 1, 2016. COURTESY OF THE STACK.

  1. 58% of enterprises are tackling the most challenging marketing problems with AI and machine learning first, prioritizing personalized customer care, new product development. These “need to do” marketing areas have the highest complexity and highest benefit. Marketers haven’t been putting as much emphasis on the “must do” areas of high benefit and low complexity according to Capgemini’s analysis. These application areas include Chatbots and virtual assistants, reducing revenue churn, facial recognition and product and services recommendations. Source:  Turning AI into concrete value: the successful implementers’ toolkit, Capgemini Consulting. 2017. (PDF, 28 pp., no opt-in).

SOURCE: TURNING AI INTO CONCRETE VALUE: THE SUCCESSFUL IMPLEMENTERS’ TOOLKIT, CAPGEMINI CONSULTING. 2017. (PDF, 28 PP., NO OPT-IN).

  1. By 2020, real-time personalized advertising across digital platforms and optimized message targeting accuracy, context and precision will accelerate. The combined effect of these marketing technology improvements will increase sales effectiveness in retail and B2C-based channels. Sales Qualified Lead (SQL) lead generation will also increase, potentially reducing sales cycles and increasing win rates. Source: Can Machines be Creative? How Technology is Transforming Marketing Personalization and Relevance, IDC White Paper Sponsored by Gerry Brown, July 2017.

SOURCE: CAN MACHINES BE CREATIVE? HOW TECHNOLOGY IS TRANSFORMING MARKETING PERSONALIZATION AND RELEVANCE, IDC WHITE PAPER SPONSORED BY CRITEO. GERRY BROWN, JULY 2017

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