Why has NEOGOV's Insight applicant tracking system seen a 20% drop in new job postings over the past month?

Introduction

NEOGOV's Insight applicant tracking system has experienced a 20% drop in new job postings over the past month, raising concerns about the product's performance and market position. This analysis will systematically investigate potential root causes, generate hypotheses, and propose solutions to address this significant decline in a core metric.

Step 1

Clarifying Questions (3 minutes)

• Considering the timing, I'm wondering if there have been any recent changes to the Insight platform. Have any major updates or feature releases occurred in the past 1-2 months?

Why it matters: Recent changes could directly impact user behavior and job posting activity. Expected answer: Information about recent updates or lack thereof. Impact on approach: If changes occurred, we'd focus on their potential effects; if not, we'd look at other factors.

• Given the specific 20% drop, I'm curious about the baseline. What was the average number of new job postings per month before this decline?

Why it matters: Understanding the scale helps contextualize the impact and guides our investigation's scope. Expected answer: A specific number or range of monthly job postings. Impact on approach: A larger baseline might indicate a more systemic issue, while a smaller one could point to specific client segments or seasonal factors.

• Thinking about user segments, has this decline been uniform across all client types, or are certain segments (e.g., government agencies, educational institutions) more affected?

Why it matters: Segment-specific issues require targeted solutions and may indicate different root causes. Expected answer: Information on affected segments or uniform decline. Impact on approach: Segment-specific declines would lead us to investigate those particular user groups more closely.

• Considering potential data anomalies, has there been any change in how new job postings are tracked or measured in the system?

Why it matters: Ensures we're not chasing a phantom problem due to measurement errors. Expected answer: Confirmation of consistent measurement or details of any changes. Impact on approach: If measurement changes occurred, we'd need to reassess the validity of the 20% drop before proceeding.