We live in a marketing world where content and data are king, but with the data deluge facing us in the enterprise, how do you make sense of it all and access the insights that truly matter? There is a plethora of customer insights buried deep in your data just waiting to be uncovered by analysts and marketers. That data doesn’t only tell us stories about where those customers have been but helps us understand and predict what they’re likely to do next. The trick is accessing the insights in an efficient way and then making those insights actionable for your organization’s teams.

However, humans alone can’t do all the heavy lifting. It takes people and machines working together. We need the machine’s analytics power to uncover customer insights and the human’s ingenuity to piece together those insights to make better decisions.

The power of the human brain is needed to take all the information, ask questions about it within the context of the business, and use it to create connections with our customers. As machines are getting smarter, we can make better predictive marketing decisions about audience, messaging, creative, media buying, optimization, and more. While data scientists will continue to use and advance the cognitive analytics capabilities of machines, they’ll continue to supplement the findings and decisions with human intelligence and other innately human abilities like storytelling, empathy, emotion, and creativity.

With predictive marketing, we function as the archaeologists of the data discoveries, interpreting the past and present. Predictive marketing combines artificial intelligence and machine learning technologies, analytics forecasting, segmentation, and automation, together with human creativity, reasoning, and decision-making.

Here are some best practices for combining humans and machines to enable marketers to deliver the most personal, relevant experiences possible.

1. Align your business needs with your analytics

Ask yourself what you hope to achieve with the data and how you’ll define success. It’s critical to determine your objectives, goals, and strategies for your analytics and ensure they’re aligned with your enterprise strategy. If your goals aren’t aligned, you won’t drive change or improve your company’s bottom line.

2. Have an end goal in sight

If you can’t envision what you want to do with the insights gained from analytics, AI, and machine learning, you’re likely to fail. Using the data, set a clear path for how to use the information gathered to automate decision-making, engage with customers, or change some process or experience. Ensure you’re connecting the output of your machine learning model to the decision and execution points, such as the technology enabling you to target, personalize, test, optimize, and automate content.

3. Communicate your strategic direction

Get everyone on board, from your executives to your marketing team, so they can build tests to align with key metrics and act to reach business goals. Also, make sure that everyone is aligned when the data suggests a change in strategy.

4. Determine which analyses and decisions to automate

With predictive marketing, you can automate many processes, such as consolidating multiple data sources, personalizing content, segmenting audiences, and delivering content based on the data. When deciding what to automate, think of the machine as handling the smaller, more tedious tasks while you focus on the big strategic decisions and ways to optimize the experiences you’re delivering.

5. Establish a data democracy

Eliminate your organizational information silos, connect your data, and curate who can access the information. Customize data sharing so relevant people can access the insights they need to make more informed decisions. This enables everyone to respond to predictions and insights, and develop and adapt campaigns and experiences as needed. Whether it’s forecasting business outcomes, selling products, or creating content, today’s analytics tools are making it easier than ever for everyone to explore data and promptly act.

6. Encourage creativity and strategic thinking

At all levels of your organization, empower everyone to tell their data-driven stories. Given all the insights coming from big data, it’s easier than ever. Data has the power to spark new ideas and even drive revenue growth.

When a company does predictive marketing right, data follows a journey from initial discovery to great customer experiences. With humans and machines working together, we bridge the gap between the massive amounts of data provided by machines and the uniquely human experience. Using both, marketers can tell more meaningful stories, create more personal experiences, and make deeper human connections.

Suresh Vittal is vice president of platform and products at Adobe Experience Cloud.