Data-driven marketing is when marketing teams create their own strategies based on big data analysis which helps them to offer insights into customer preferences and broader trends that impact a marketing campaign’s success. The teams collect data through applications or various websites. When all this information is passed and analyzed, they can see which creative assets drove more engagements, which channels got the highest ROI. Based on these findings, organizations can boast their campaigns to ensure the best customer experiences and the greatest return on marketing investment, and also improve conversion factors, because the targeted messaging enabled by data-driven marketing is more likely to catch the attention of users. Companies that works on precision marketing in these ways can drive significant customer acquisition during periods of explosive change. However, capturing this opportunity will require brands to update their modeling—from pulling in new sorts of data to retraining algorithms—to keep pace with changing needs and expectations and anticipate shifts in customer behavior. The major issue observed while using this technology is the rapid, large-scale shift to remote working.

Data-driven marketing works best in agile settings, where teams can test and iterate in sprints. But with nearly two-thirds of employees working from home, marketing leaders have found it difficult to create an effective cadence. Marketers are using artificial intelligence (AI) to monitor digital campaigns and interrogate responses at a detailed level, to learn more about what works and what doesn’t but for which segments, and at what times, and over which channels—and then based on those observations they adjust their strategies. Deriving those specific insights using standard analytics might take the average organization days. But if they start using AI-enabled monitoring, they can do this in minutes, sometimes seconds.