The Hidden Crisis in Your Support Queue
Customer Service Intelligence for a Home Goods Brand
How Sum IQ analyzed 179,442 support tickets across 2 years to uncover a channel migration crisis, Q4 capacity breakdown, and 12 actionable fixes before peak season
Tickets Analyzed
Support Channels
Resolution Rate
of CX Data
Executive Summary
What Sum IQ Uncovered
On the surface, this home goods brand looked healthy: 99% resolution rate, consistent ticket handling, established processes. But when Sum IQ analyzed 179,442 support tickets spanning January 2024 to January 2026, it revealed four critical issues hiding beneath strong top-line metrics:
Channel Migration Crisis
Instagram Comments collapsed 94% (45K to 3K tickets) while Email surged 81%. Customers are migrating away from public channels due to algorithm changes.
Quality Degradation in 2025
Negative sentiment doubled year-over-year (0.05% to 0.10%), with Instagram Comments showing a 4x spike in negativity.
Q4 Capacity Breakdown
Resolution time deteriorated 250% in Q4 2025 vs 2024 (34.2 hrs to 75.8 hrs), indicating serious staffing issues during peak season.
Instagram Strategy Overhaul Required
Comments becoming unusable while DMs remain stable. Immediate channel redirection needed before monitoring effort becomes wasted.
Background
Client & Context
This home goods brand has built a loyal customer base through quality products and responsive customer service. With 52,255 unique customers interacting across 9 support channels over 2 years, they've scaled successfully while maintaining operational excellence.
But growth creates complexity. As their paid media partner, we noticed signs that the CX operation was under strain. Campaign performance was strong, but something felt off in the customer feedback loop.
We used Sum IQ to analyze their complete customer service database: every ticket, every channel, every resolution. What we found demanded immediate action.
Finding #1
Channel Performance Evolution
Sum IQ analyzed ticket distribution across all 9 support channels, revealing dramatic shifts in where customers choose to engage.
Channel Performance Matrix
| Channel | Total Tickets | Resolution Rate | Negative % | YoY Trend |
|---|---|---|---|---|
| 101,991 | 98.8% | 0.0% | +81% | |
| Instagram Comment | 45,989 | 99.8% | 0.1% | -94% |
| Instagram DM | 19,474 | 99.9% | 0.1% | Stable |
| Chat | 6,635 | 99.8% | 0.1% | +170% |
| 1,897 | 99.9% | 1.5% | -28% | |
| Instagram Mention | 2,069 | 100% | 0.2% | Stable |
| Instagram Ad Comment | 673 | 100% | 0.7% | Stable |
| Facebook Messenger | 659 | 99.8% | 0.2% | -63% |
| Facebook Mention | 55 | 96.4% | 0.0% | +145% |
Critical Channel Migration Pattern
Instagram Comments Collapsed
From 27.7K tickets (Q1 2024) to just 0.3K (Q2 2025). Algorithm changes have made public comment monitoring nearly obsolete.
Email Surge
Quarterly volume grew from 7.8K to 18.5K. Customers are actively migrating to direct contact channels.
Facebook Risk
Highest negative sentiment at 1.5%—8x higher than other channels. Quality concerns concentrated here.
The Hidden Message: Customers aren't abandoning the brand—they're abandoning public channels. This migration creates efficiency opportunities but also risks: customers reaching out via email expect faster, more personal responses than social media comment replies.
Finding #2
Seasonal & Temporal Patterns
Sum IQ analyzed temporal patterns to identify peak periods and staffing optimization opportunities.
Top 5 Highest Volume Days
| Date | Tickets | Event Correlation | Day |
|---|---|---|---|
| Feb 16, 2024 | 17,471 | Likely product launch/viral content | Friday |
| Apr 25, 2024 | 6,096 | Major campaign/promotion | Thursday |
| Feb 15, 2024 | 4,470 | Pre-launch buzz | Thursday |
| Feb 17, 2024 | 3,385 | Weekend overflow | Saturday |
| Apr 26, 2024 | 2,926 | Campaign continuation | Friday |
Weekly Distribution
Peak Days
Thursday & Friday
42% of all tickets (34.7K + 40.4K)
Lowest Volume
Saturday & Sunday
18.4K + 18.9K tickets
Sentiment Concern
Tuesday
Highest negative sentiment (0.14%)
Staffing Insight
Thu-Fri need maximum coverage; Tue needs quality monitoring
Q4 Holiday Season Impact
| Metric | Q4 2024 | Q4 2025 | Change |
|---|---|---|---|
| Tickets | 19,983 | 22,061 | +10% |
| Negative Sentiment | 0.07% | 0.12% | +71% worse |
| Resolution Time | 34.2 hrs | 75.8 hrs | +250% slower |
Q4 2025 shows severe capacity strain. The team handled 10% more volume but took 2.5x longer with significantly worse customer sentiment.
Finding #3
Ticket Category Analysis
Sum IQ broke down tickets by category to identify where CX effort is concentrated and where problems emerge.
Category Performance Matrix
| Category | Volume | Avg Resolution | Negative % |
|---|---|---|---|
| General | 116,419 (65%) | 0.3 days | 0.05% |
| Returns | 34,594 (19%) | 4.7 days | 0.14% |
| Order Status | 15,605 (9%) | 2.3 days | 0.11% |
| Shipping | 5,494 (3%) | 2.4 days | 0.05% |
| Warranty | 3,105 (2%) | 6.1 days | 0.06% |
| Sizing | 2,959 (2%) | 1.6 days | 0.30% |
Returns: The Longest Journey
Nearly 5 days to resolve a return request. This isn't just an efficiency issue—it's a customer experience failure during an already emotional touchpoint. Returns also show 2.8x higher negative sentiment than general inquiries.
Order Status: Self-Service Opportunity
15,605 tickets asking "where is my order?" That's 9% of all CX volume for information that should be automated. Each ticket costs time and money that could be eliminated with better tracking communication.
Sizing: The Upstream Problem
Sizing questions show 6x higher negative sentiment than average. This signals a content problem, not a CX problem. Customers are frustrated before they even buy because product pages don't answer their questions.
Action Plan
Strategic Recommendations
Based on Sum IQ's findings, we developed a phased action plan across CX, Marketing, Ops, and Product teams:
Customer Support / CX
- | Audit Instagram Comments workflow—confirm if monitoring is still worth the effort
- | Update IG bio, highlights, and auto-replies to push customers to DMs or email
- | Create Q4 escalation playbook (when queues exceed X hrs, what happens?)
- | Flag Returns + Order Status tickets for priority handling
Marketing / Social
- | Reduce reliance on public IG comments for customer interaction
- | Test pinned comments + story highlights that redirect to support channels
- | Coordinate with CX on expected campaign spikes (no more surprise surges)
Operations
- | Build Q4 capacity model using 2025 resolution-time data
- | Define minimum staffing thresholds for peak days (Thu/Fri)
CX + Ops
- | Launch self-serve order status (tracking links, macros, help center surfacing)
- | Add returns-specific macros + flows to reduce back-and-forth
- | Introduce sentiment tagging for early detection (before complaints escalate)
Marketing + CX
- | Audit sizing content (PDPs, FAQs, UGC) to reduce pre-purchase confusion
- | Identify top 5 sizing-related objections from tickets and fix upstream
Leadership
- | Set a Q4 resolution-time SLA (hard line the team plans against)
- | Align incentives around quality, not just resolution rate
CX / Automation
- | Pilot AI-assisted ticket triage for Order Status, Returns, and General FAQs
- | Auto-route high-risk sentiment tickets to senior agents
Product / Marketing
- | Rework return messaging to set clearer expectations and reduce emotional friction
- | Test proactive post-purchase emails answering "Where is my order?" and "How do returns work?"
Data / Ops
- | Build a weekly CX health scorecard: Volume, Resolution time, Negative sentiment, Channel mix
Leadership
- | Formally shift CX strategy toward owned, private channels
- | Decide whether IG comments are monitored lightly or deprioritized entirely
CX + Marketing
- | Treat CX data as a product-feedback loop: sizing, shipping expectations, return friction
- | Use ticket insights to guide creative, PDP copy, and ads
Framework
Why This Analysis Matters
Resolution rate isn't the whole story
99% resolution sounds healthy until you realize tickets are taking 3 days longer to close and sentiment is deteriorating. Sum IQ surfaces the metrics that matter—not just the ones that look good in reports.
Channel shifts reveal customer preferences
The 94% collapse in Instagram Comments isn't a failure—it's customers telling you where they want to engage. Smart brands follow this signal rather than fighting algorithm changes. This intelligence directly informs paid media strategy.
CX data predicts paid media friction
Sizing questions with 6x negative sentiment signal a content gap on product pages. Fix the upstream problem, and you don't just reduce support tickets—you improve conversion rates. See how we applied similar analysis for Bomber Eyewear.
"The brand's systems are resolving tickets well—but channel shifts and Q4 pressure are quietly eroding customer experience. These issues need resolution before peak season, not during it."
Common Questions
Customer Service Intelligence FAQs
How is this different from regular support analytics?
Standard dashboards show resolution rates and ticket counts. Sum IQ analyzes patterns across time, channels, and categories simultaneously—revealing compound issues like "Q4 capacity + channel migration + sentiment degradation" that individual metrics miss. Compare this to our Sozy Apparel buyer persona analysis.
What data does Sum IQ need for CX analysis?
An export from your helpdesk (Gorgias, Zendesk, Freshdesk, etc.) with ticket timestamps, channels, categories, and resolution status. Richer analysis includes sentiment tagging and customer identifiers for repeat contact patterns.
How can this inform paid media strategy?
CX data reveals friction points that affect conversion: sizing confusion, shipping anxiety, return hesitation. When we fix these upstream through better creative and landing page content, both conversion rates and customer satisfaction improve simultaneously.
How do I get started with Sum IQ?
Sum IQ is available to Sum Digital paid media clients as part of our partnership. Book a call to discuss how customer intelligence can inform your growth strategy.
Ready to See What's Hiding in Your Support Data?
Sum IQ can analyze your customer service tickets to reveal channel shifts, capacity risks, and upstream product issues you didn't know existed.