Diagnostic analysis is a type of advanced analytics used to explore data and determine the root cause of a phenomenon or event. Unlike descriptive analytics, which simply tells you what happened, diagnostic analytics seeks to understand why it happened.
Based on the provided reference, here are specific examples illustrating diagnostic analysis in practice:
- Identifying why sales decreased during a specific time period. This involves drilling down into sales data and related factors (like marketing spend, competitor actions, economic indicators, website traffic, or inventory levels) for that period to uncover the underlying reasons for the decline. Was it a failed marketing campaign? A new competitor? A seasonal dip? Diagnostic analysis helps pinpoint the exact cause.
- Identifying why website traffic decreased after a website redesign. Following a significant change like a redesign, diagnostic analysis would involve examining traffic sources, user behavior flows, technical performance, SEO rankings, and user feedback to understand what specifically led to the drop in visitors. Was there a broken link? Did the site load slower? Did the design confuse users?
These examples showcase how diagnostic analysis moves beyond observing a trend (like decreased sales or traffic) to investigating the data to find the specific factors that contributed to that outcome. This understanding is crucial for taking effective corrective action and making better-informed decisions moving forward.
