Data Insights Agent use cases

Transcript

Hi, this is Michelle. Join me to learn about the efficiencies and use cases enabled by the Data Insights agent in Customer Journey Analytics. Meet Taylor, a marketing analyst who constantly faces delays, chasing answers from data analysts. His role demands quick insights, but he’s often stuck waiting, highlighting a common challenge for marketers and business users alike. His first challenge is the heavy reliance on analysts for deep strategic analysis to understand customer interactions and uncover hidden patterns in company data. Secondly, assessing campaign performance is slowed by a lack of real-time access, leaving him dependent on weekly dashboards from analysts. This hinders timely decision-making, and it results in bottlenecks and inefficiencies. Meet Sarah, the data analyst complementing Taylor’s story. Like many organizations, she navigates a ticketing system to handle data requests. Less fluent in understanding the data than her teammates, Sarah relies on her analyst team, waiting for responses in a continuous cycle that delays insights for Taylor and other marketers. Taylor’s daily routine involves a challenging interaction with Sarah to shape marketing strategies. He seeks cross-channel insights into customer experiences, positive or negative, to refine campaigns relying on Sarah to analyze data. After reviewing her insights, Taylor often needs further slicing or what-if scenarios, prompting more wait time. He also tracks campaign and asset performance in weekly dashboards, while facing constant stakeholder demands for business performance data, all of which amplify delays. Taylor’s challenges translate into missed business opportunities. His sole reliance on Sarah leads to suboptimal customer experiences and delayed marketing decisions due to inefficient real-time data. This lag in performance insights hinders proactive marketing, leaving him reactive and falling behind. The process is inefficient and time-consuming for both Taylor and Sarah. Taylor needs a smarter solution, and the Data Insights agent delivers. He streamlines his process, cutting wait times to a fraction, allowing natural language queries that generate visualizations and iterative analyses in analysis workspace. Let’s dive into key use cases, starting with marketing strategy development. Marketers need a holistic view of customer behavior and business performance trends, like market share, but rely heavily on data analysts, causing constant back and forth. With the Data Insights agent, marketers can ask questions like, what was online and in-store revenue this week, and quickly craft strategies without prolonged analyst interactions. Next, consider campaign and asset management. After crafting a marketing strategy, marketers launch campaigns and assets across digital platforms, needing real-time performance insights to adjust strategies, audiences, or content for better ROI. Traditionally, this relies on analysts, but the Data Insights agent empowers marketers with instant access, visualizing performance data within seconds through natural language queries. Finally, business performance reporting is a universal challenge. Marketers face demands from leadership and stakeholders to understand business performance. Instead of struggling through delays, they can use the Data Insights agent to ask questions and receive instant answers, empowering them with timely insights. With the Data Insights agent, Taylor can create, analyze, and fine-tune visualizations effortlessly. Meanwhile, Sarah gains more time for strategic deep data analysis, which is her true expertise. This creates a win-win scenario, empowering both marketers and analysts within the organization. Thank you for watching.