Complaints Dashboard Manual
After-sales steering: load, processing rate, satisfaction after resolution and churn risk, with analysis by type, root cause, customer and sales rep.
Overview
The Complaints Dashboard is the control desk of the after-sales service. It measures three things: the load (how many complaints come in), the processing capacity (how many are closed) and the quality of the resolution (are customers satisfied afterwards). It covers complaints from customers, sales reps and end consumers.
Purpose
- Track after-sales load and peaks
- Measure the processing rate
- Detect customers at churn risk
- Prioritise recurring root causes
Audience
- After-sales manager — pipeline and lead times
- Sales management — customer retention
- Quality — root causes
Data comes from the customer complaints, sales rep and mobile seller screens. Processing states follow the configured workflow.
Access and navigation
Side menu: Complaints → Complaints dashboard, at the top of the submenu.
Read-only access, subject to the profile's read right.
After-sales scoreboard
The top band combines volume, pipeline state and the satisfaction obtained after processing.
| Indicator | Meaning |
|---|---|
| Total complaints | Volume received over the selected period, all categories combined. |
| Processed complaints | Closed complaints. Processing rate = processed ÷ total × 100. |
| Unprocessed (urgent) | Complaints to be taken over as a priority — the immediate-action indicator. |
| Being processed | Taken over but not yet closed: the current workload. |
| Satisfied / dissatisfied | Satisfaction feedback obtained after processing. |
| Indifferent | Processed without any expressed satisfaction feedback. |
| Complaining customers | Number of distinct customers who filed at least one complaint. |
A dissatisfied customer is flagged as high churn risk. That is not a mere statistic: it calls for a proactive phone call, not a table row.
Filters and scope
The Search dialog works by year and month (not free dates), and lets you restrict the complainant category.
Search
The three Customer / Sales rep / Consumer switches add up: setting all three to YES gives the full after-sales view; keeping only one isolates a population.
Reasoning by year + month makes year-on-year comparison easy: keep the same month window so the comparison stays honest.
Monthly trend
Three series over twelve months: Total, Processed and Unprocessed.
| Item | Detail |
|---|---|
| Equation | Monthly processing rate (%) = processed ÷ total × 100 |
| Reading | Analysis of the monthly after-sales load: complaint peaks and processing capacity. |
| Warning signal | A growing gap between Total and Processed signals a deteriorating response capacity. |
The Busiest month counter points at the peak of the period: tie it to an event (product launch, stockout, carrier change) to turn it into an action.
Overall pipeline state
An instant snapshot of the after-sales pipeline: processed, unprocessed, in progress.
Reading benchmarks offered by the application: a processing rate above 80% reflects good operational capacity; unprocessed should stay below 10%; in progress measures the current workload.
Satisfaction & approximate NPS
After closure, declared satisfaction qualifies the quality of the resolution, not just its speed.
| Indicator | Formula |
|---|---|
| Satisfaction rate | Satisfied ÷ (Satisfied + Dissatisfied + Indifferent) × 100 |
| Approximate NPS | Satisfied rate (%) − Dissatisfied rate (%) |
The approximate NPS is not a strict NPS: a real NPS requires a dedicated 0–10 survey. Use it as an internal trend, not as a figure to publish externally.
Application benchmarks: a satisfaction rate > 70% is excellent, an approximate NPS > +30 is a good signal. Indifferent customers deserve follow-up to recover their engagement.
By type and by root cause
Two complementary angles: the type (problem category) and the root cause — the nature of the issue.
| Analysis | What it reveals |
|---|---|
| By type | Recurring typologies to fix in the processes. A type with many unprocessed items signals a persistent malfunction. |
| By root cause | The underlying cause. A recurring cause with a low resolution rate points at a structural problem: product quality, logistics or customer communication. |
Prioritise fixes on causes with a high unprocessed volume — that is where effort cuts future load the most. Types and causes are configured in Workflow & states.
Responsiveness (live flow)
Four flow counters, independent of the period filter: today, this week, this month, this year.
These indicators exist to spot a peak immediately. A sharp rise over the day or the week calls for a fast reaction; always compare with historical averages to tell an anomaly from noise.
The Current month contribution counter expresses the share of the current month in the yearly total.
By customer, sales rep and consumer
Individual analyses: who complains, who handles it, and with what result.
| Analysis | Reading |
|---|---|
| By customer | Processed complaints, satisfied, dissatisfied and indifferent for each customer. A customer with several unprocessed complaints is at risk of commercial breakdown. |
| By sales rep | Complaints generated on their portfolio and the associated satisfaction — a relationship-quality indicator, not a sanction. |
| By end consumer | Satisfaction after processing on the consumer side (retail sales). |
| By category | Split of complainants between customers, sales reps and consumers. |
A CHURN ALERT flag appears on customers carrying at least one dissatisfaction. Treat it as an action queue, not as a label.
After-sales dashboard by category
The final summary crosses, for each complainant category, the processing rate and the satisfaction rate.
This is the view to keep for a quality committee: at a glance it answers “are we fast?” and “are we good?”, category by category.
A high processing rate with low satisfaction signals a fast but shallow after-sales service — the classic symptom of administrative closures without real resolution.
FAQ & Tips
Satisfaction is empty although complaints are processed?
No satisfaction feedback was entered at closure. Record it systematically: it is the only source of this indicator.
The total does not match what I see in the list?
Check the Customer / Sales rep / Consumer switches in the search dialog: they restrict the scope beyond the period.
Responsiveness indicators ignore my filter?
That is deliberate: today / week / month / year are live flows, computed by date comparison, independently of the selected period.
One root cause dominates all others — is that abnormal?
Not necessarily — but if its resolution rate is low, it is a structural problem. Fix the cause rather than adding after-sales resources.
Tip — weekly after-sales ritual. Open the page on the current month, clear the urgent unprocessed first, then call the churn-alert customers, and finish with a read of the root causes to feed the quality action plan.
