Positive and negative scoring has been the name of the game in CX QA for ages, but it isn’t the only option, nor should it be. Adding neutral scoring metrics to your rubric increases insight without stressing your CX team.
Neutral scoring allows both tracking and immediate guided follow through for agents in particular circumstances. This is helpful especially when launching new products, software updates, recalls, pandemics or other catastrophes.
In these circumstances the benefit of being able to track, for example; that all orders were backed up because the Port of Los Angeles was effectively shut down (like it was during the pandemic) allowed for greater granularity in understanding. Customers were angry, there was nothing that could be done by any stakeholder and there should be an asterisk beside that data, made via neutral scoring.
Likewise, for compliance. If you’re wanting to alert an agent of a particular situation, make a disclaimer, or request that a customer should immediately seek medical aid or find a place of safety. Prioritizing safety over scores for thanking the customer for their patience is a must.
What is CSAT.AI’s neutral tracking tool? It’s a setting built into the auto QA scoring system. Define your metric then set it to 0% of agent score. Then add the type of guidance if necessary. That’s all it takes.
The "Algorithmic Fairness" Trend
In 2026, there is a massive push for Ethical AI in the Workplace. Using Neutral Scoring isn't just a "nice to have"; it protects the company from "Algorithmic Bias." If your AI is penalizing agents for things they can't control (like a port shutdown), you're creating a toxic data loop.
Report to reference: Look for "2025/2026 AI Ethics in Workforce Management" trends.
Focus on "Agent Burnout & Mental Health"
The "Great Resignation" evolved into the "Great Retention" of 2026. Companies are hyper-focused on keeping talent. Penalizing an agent for a product recall is a top driver of agent churn.
"Macro-Event Mapping”
Modern CX leaders are now looking for "Clean Data." By using Neutral Scoring as an "Asterisk" (as you mentioned), you are essentially cleaning your training data for future AI models. If you don't use neutral scoring, your AI learns that "Angry Customer = Bad Agent," which is a false correlation.
Do you recommend Neutral Scoring?
Yes, it is very helpful in tracking circumstances – weighing scores properly when things go wrong. It is a game changer in understanding the year-over-year without having to recall particulars.
What are the results from neutral tracking as opposed to setting it to just positive or negative?
Fairness – if you know some departments are going to be hit because of an issue then you don’t want to grade everyone based on metrics that only a few can achieve. If bonuses are based on these metrics it becomes unethical. Ex. agents penalized for bad customer sentiment when a product was recalled for a safety reason.
When to use neutral scoring:
To prioritize safety or compliance above CSAT
- Make sure the customer is safe (more important than empathy or calling them by name)
- Have them call emergency services when necessary
Marking an event outside of company control which impacts sentiment/CSAT
- Local disasters
- Major world events
Marking an event as outside of an agent’s control
- Product Launches
- Recalls
- Extreme categories
In conclusion, think of neutral tracking like controlling for inflation when you’re doing yr-over-yr analysis.
You still want to keep track of events but tying agent performance ratings to occurrences beyond their control is not beneficial. Neutral tracking allows you to separate that which agents have influence on from things they do. When done correctly, it provides a clear picture of actionable items for the stakeholders to effect change.
