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Transforming your business in the Age of Assistance

Technology has a history of making organizations adapt. Marketers are continuously sharpening their skill sets—from the early days of the web to the proliferation of mobile, and now with AI and machine learning. With the current pace of digital innovation, companies large and small are constantly rethinking the ways they operate.

Now more than ever, importance is being placed on precision in marketing—reaching the right user in the right moment with the right message. But this level of precision can’t be accomplished by humans alone. Machine learning technology is enabling smarter marketing by allowing marketers to drive customer intimacy at scale. Now, marketers can learn what customers want and react to their changing preferences in real time. It’s new technologies and analytics techniques that are making this possible.

For instance, companies are starting to use machine learning to understand the next best action (NBA) to take with a customer. A few years ago, a call c

Data-driven businesses that use machine learning to serve menter agent was encouraged to upsell customers based on their previous purchases. NBAs take this to the next level: if the system predicts that a customer is at risk of churning, the agent will focus on mitigation rather than selling to drive higher customer satisfaction and lifetime value.ore relevant experiences for their customers are better positioned to take share away from their competitors.

Data-driven businesses that use machine learning to serve more relevant experiences for their customers are better positioned to take share away from their competitors.

How do leading organizations use data as a competitive advantage?

Successful organizations start with a business objective that’s supported with a robust data strategy. We’re seeing some of the best organizations groom data science teams who can apply big data, including machine learning, to business problems. In fact, Bain research shows that leading companies are 3.2X more likely to have the right analytics talent embedded in marketing.

Advancements in technology usually mean new mindsets and skill sets. How are companies planning for this?

We’re seeing successful companies assess how technology will redefine current roles and the skill sets their teams will need to drive future growth. The most effective organizations are comprised of small, nimble teams that are agile in their approach. They combine the cross-functional talents and expertise that they need to win in today’s competitive environment, taking ownership to make things happen quickly.

The role of the marketer is also starting to evolve. How are you seeing machine learning technology transform the work that marketers do?

As consumers navigate across multiple channels, platforms, and media, they’re leaving behind millions of signals about their intent, context, and identity. The problems marketers aim to solve and the data they are dealing with are complex. Machine learning is an effective approach to process all of that complexity at scale and surface the insights that matter to marketers.

Machine learning is an effective way to process complex data and surface insights that matter.

Most often we see incremental adoption of artificial intelligence and machine learning for high-value use cases. For example, there are a number of startups (Kuaizi Tech, that use AI and machine learning to select the best image or video to maximize click-through rates in a campaign, and drive higher return on ad spend and customer intimacy. These companies benefit from machine learning because the technology frees up marketing from debating which creative is best so they can launch more campaigns faster, or reinvest in new areas of marketing.


Matt Lawson

Vice President, Ads Marketing at Google

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