Level Zero Solvable
Definition
Level Zero Solvable: The Self-Service CX Metric
Level zero solvable (LZS) is the share of customer issues a user could have resolved on their own, through a knowledge base, FAQ, chatbot, or account portal, before contacting a live agent. LZS is the deflection ceiling of your customer experience, and it tells support leaders how much ticket volume is theoretically avoidable with better self-help.
The metric grew out of tiered support models, where “level zero” refers to the pre-agent layer: everything a customer solves without human intervention. A high LZS score means your help content is doing the heavy lifting; a low score means agents are answering questions the website should already answer.
Most contact centers treat LZS as a diagnostic. It is not a KPI you chase for its own sake, but a signal that reveals where your knowledge base, product UX, or in-app messaging is failing to guide the customer.
Key takeaways
- LZS measures the percentage of contacts that could have been self-served.
- It is calculated through internal testing, ticket sampling, or post-contact surveys.
- A rising LZS score means your knowledge base is beating your call center on cost per resolution.
- LZS complements — not replaces — first-contact resolution and CSAT.
How it works
Level zero solvable is calculated by sampling closed tickets or contacts and asking a simple question: could this issue have been resolved by the customer using existing self-service resources? Analysts tag each contact as solvable or unsolvable, then divide the solvable count by total contacts.
According to Altura Communication Solutions, LZS provides three critical pieces of information — the ceiling of possible deflection, the quality gap in current self-help content, and the priority order for knowledge-base investment. A Harvard Business Review analysis reported that 81% of customers now try to resolve matters themselves before reaching a live representative, which is why the deflection ceiling matters.
The formula is straightforward:
| Input | Description |
|---|---|
| Sampled contacts | A representative slice of tickets or calls over a defined period (usually 30–90 days) |
| Solvable tags | Contacts flagged as answerable via existing FAQs, KB articles, or automated flows |
| LZS score | (Solvable contacts ÷ total contacts) × 100 |
A 2023 industry benchmark places typical LZS scores between 20% and 45% for mid-market SaaS support teams, meaning roughly a third of live-agent conversations were technically avoidable.
Examples
LZS shows up in three familiar shapes across the BPO sector: retail e-commerce, SaaS, and telco support. Each uses the score to redirect budget from headcount to self-service assets.
- E-commerce returns: A US apparel brand sampled 2,000 chat contacts in early 2024 and found 38% asked about return windows already published on the product page. The team rewrote the returns FAQ and cut agent contacts by 22% in the next quarter.
- SaaS onboarding: A Manila-based call center supporting a European fintech logged an LZS score of 41% on tier-1 tickets. Password resets, invoice downloads, and 2FA setup dominated — all documented but hard to find. A search-optimized help center dropped the score to 27% within six months.
- Telco billing: An Australian carrier ran LZS analysis in 2023 and found 30% of billing calls were “where do I find my invoice.” An in-app banner solved most of them within eight weeks.
- Insurance claims: A regional insurer used LZS scoring to justify a chatbot investment, showing that 33% of claim-status calls could be answered by a status lookup tool.
Related terms
LZS sits inside a wider vocabulary of customer service metrics. These are the terms that typically appear alongside it in a support scorecard or outsourcing RFP.
- First contact resolution, the share of issues closed in a single interaction, LZS’s operational cousin.
- Average handle time, the mean duration of a single contact, often falls as LZS rises.
- Customer satisfaction (CSAT), the sentiment score that self-service quality directly influences.
- Knowledge process outsourcing, a delivery model where analytics teams often own LZS scoring.
- Chatbot, the automation layer that converts theoretical LZS into actual deflection.
- Customer service, the parent discipline LZS reports into.
- Agents, the customer service personnel whose workload LZS is designed to reduce.
FAQ
What does LZS stand for?
LZS stands for level zero solvable. The “zero” refers to the pre-agent tier of support, everything a customer resolves without a human on the other end.
How is level zero solvable calculated?
Sample a batch of closed tickets, flag each one as solvable or unsolvable using existing self-help content, and divide solvable contacts by total contacts. Most teams run this quarterly on a 200–500 ticket sample.
Is a higher LZS score better?
Yes and no. A high score means self-service could handle more volume, but it also flags that customers are still calling instead of self-serving. The goal is to close that gap by improving discoverability.
Who owns LZS in an outsourced support setup?
Usually the client’s CX operations lead, with the BPO providing raw ticket data and sampling support. In mature partnerships, the BPO’s analytics team scores tickets directly.
How does LZS differ from first contact resolution?
FCR measures how efficiently agents close issues once contacted. LZS measures whether the contact should have happened at all. The two together give a full picture of support efficiency.
Explore vetted customer service partners in the Outsource Accelerator directory to benchmark LZS scoring inside your own operation.
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