Clients in 2025 are not asking “Do you do QA?” They are asking, “Can you prove coverage? Can your team keep up without slowing us down?” If you cannot answer “yes”, you are not a partner — you are a risk. Clients do not expect perfection. But they want nothing critical to be missed.
This article is developed in consultation with Belitsoft, a custom software development company. Modern software testing is adaptive and integrated, blending in-house strategy with outsourced execution, embedding QA into CI/CD pipelines, and meeting high standards for automation, security, scalability, and compliance. Belitsoft provides quality assurance and software testing services to verify error-free software product operation.
How Clients Choose Partners That Fit
The client’s QA journey does not start with an RFP. It starts with something breaking. A botched release. A bug that hits revenue. A security flaw that shows up in a board meeting. That is the trigger. From there, it is a mix of panic, planning, and politics — all aimed at landing on a testing approach that works before something worse happens.
Step 1: Something Breaks. Then They Define What “Fixed” Looks Like
Clients do not think about testing until the lack of it starts to hurt. Maybe a Sev1 bug got through (a highest-priority defect with a critical impact that needs immediate attention because it carries business risk). Maybe the CEO got a customer escalation forwarded to their inbox. That is when quality becomes a priority — not a technical one, a strategic one.
At this stage, the goal is clarity:
- “We want fewer bugs in prod”.
- “We want to ship weekly without rollback”.
- “We need to pass an audit in 90 days”.
Example: A SaaS startup that is doing weekly hotfixes defines a goal: implement automated testing for all core flows within 30 days and bring production Sev1 bugs to zero by end of quarter.
Step 2: Budgeting and Internal Buy-In
Internal QA leads prep a slide deck. Security throws in breach costs. Product throws in churn metrics. Someone pulls a quote from Gartner. Now it is about making the case that fixing quality is cheaper than not fixing it.
Questions they are answering:
- Is it cheaper to hire QA or outsource?
- What’s the ROI on a tool vs headcount?
- What happens if we don’t do anything?
At enterprise scale, QA is a boardroom topic. One major incident can wipe out the savings from skipping testing for a year.
Step 3: Surveying the Options
Clients now look at execution models:
- In-house. Build or expand a QA team. Full control, slow to ramp.
- Tool-centric. Get software testing tools to empower existing teams.
- Outsourcing. Bring in a vendor for coverage, expertise, or execution.
- Hybrid. In-house strategy + outsourced execution.
Example: A healthtech company realizes building an in-house performance testing lab is too expensive. They keep exploratory testing internal and outsource load testing to a vendor with AWS-based infrastructure.
Step 4: Defining Requirements That Actually Mean Something
This is where smart clients start to differentiate themselves. They say:
- “We need 80% regression automation for React/Go stack, API + mobile”.
- “Testing must integrate with Azure DevOps and Slack”.
- “We require HIPAA-compliant infrastructure and U.S.-based testers”.
What goes into their checklist:
- Test types: functional, performance, security, usability
- Frequency: daily? Release-based? 24/7?
- Volume: number of test cases, environments, devices
- Compliance: HIPAA, SOC2, ISO 27001
- Reporting: dashboards, alerting, audit logs
Example: A D2C e-commerce platform running Black Friday campaigns requires 24/7 support for test execution, real-time Slack alerts, and visual regression testing across 10 device breakpoints.
Step 5: Shortlisting Tools and Vendors
Now they search. Look at review sites. Ask peers. Run RFPs. Check G2, Gartner, Reddit, LinkedIn posts, case studies. They narrow the field to 2–5 serious contenders.
What they do:
- Request demos and proposals
- Evaluate scorecards: tech fit, price, references
- Run PoCs or pilot projects
- Talk to references — and ask the hard questions (how fast do they fix things, how often do they screw up, who shows up when something breaks)
Example: A client gives a vendor one module to test and measures how fast they ramp, how deep their feedback is, and how well they communicate under pressure.
Step 6: Make the Call. Get to Work
Once the choice is made, they move fast. Contract signed. Kickoff scheduled. Access granted. Tools configured.
What clients expect:
- Early proof: automation script delivered in week one, first report in week two
- Clear ownership and communications plan: who to ping, where the dashboards live
- No ramp excuses — vendors should be productive in days, not weeks
If they went the tool route, they expect onboarding docs, support tickets answered within hours, and integration into their CI by the end of week one.
Throughout all of this, clients are managing one thing: the risk.
- Risk of bugs escaping
- Risk of audits failing
- Risk of choosing the wrong partner and having to start over
The path they pick is about who fits. Who’s fast, credible, accountable, and capable of scaling without drama?
Smart clients do not just evaluate tools or vendors. They evaluate consequences.
Software Testing Needs Differ Based on Size
Startups: Move Fast, Try Not to Break Everything
Testing starts as a to-do in someone’s Notion board. Founders do not budget for it, developers pinch-hit it, and it only gets formalized when things start slipping into production that should not. Coverage? Smoke tests at best. CI? Maybe. Budget? None.
But once real users show up — especially angry ones — startups scramble to cover the basics: regression, automation for key flows, and a test suite that does not blow up with every deployment.
What works:
- Open-source tools (Cypress, Playwright) wired into GitHub Actions
- On-demand QA contractors with no ramp time
- Zero ceremony — no test plans, just working coverage
Mid-Size: Scaling Quality Without Creating Bureaucracy
Now there is a QA lead, maybe a team. Bugs cost more now — customers churn, sales deals stall, support tickets pile up. Mid-size teams want automation that runs clean, QA people who understand the product, and help cover blind spots: performance, security, weird devices, and compliance if they are lucky.
What they do:
- Keep core QA in-house to retain domain knowledge
- Use vendors to expand coverage or hit deadlines
- Add tooling: TestRail, Zephyr, BrowserStack, GitHub + Jenkins CI
Enterprises: Process, Politics, and Audit Trails
QA is its own org. It has a budget. It has compliance rules. It has opinions. Testing here means traceability, documentation, and proving that nothing breaks at scale or under scrutiny. This is not a space for “figuring it out as we go”.
What they require:
- ISO, CMMI, SOC2, HIPAA, PCI-DSS, or FDA alignment — or you do not even get in the door
- Integration with enterprise pipelines (Azure DevOps, Zephyr, Jenkins)
- Offshore teams for cost, onshore teams for compliance (HIPAA, ITAR, etc.)
What Real QA Looks Like in 2025
Functional Testing
Still the baseline. Developers own unit tests. QA owns exploratory, system, and regression.
Automation That’s Embedded
Manual-only strategies do not scale. Regression must be automated — stable, repeatable, tied to CI/CD. It does not need to cover everything, but it must:
- Integrate with CI tools (GitHub Actions, Jenkins, GitLab)
- Deliver fast, reliable feedback
- Avoid flaky tests
Test results must be visible — failures, coverage, flakiness metrics.
2025 expectation: intelligent automation. AI-based test generation, test maintenance, or anomaly detection. It does not have to be perfect — but it should exist.
CI/CD and Deployment Alignment
Testing has to move at the pace of code. Daily releases? Then testing happens daily.
- Smoke tests in minutes
- Regression in hours
- Clear path for testing microservices, feature flags, post-deploy checks
Performance Testing
They do not want “pretty fast”. They want guarantees:
- Load: Can it handle 100K users?
- Stress: What breaks under strain?
- Scalability: What is the plan when usage triples?
What they expect:
- Tools: JMeter, Gatling, k6, BlazeMeter
- Infrastructure to simulate spikes (cloud-based, ideally)
- CI triggers with performance budgets — if it fails, block the release
Example: A retail client launching for Black Friday asks for 50K simulated users and diagnostics before go-live. No test = no launch.
Security Testing
If it touches the production, clients want it locked down. No exceptions.
- SAST/DAST scans in CI
- Manual pen tests on a schedule
- Container scanning, dependency audits, MFA enforcement
If you touch health data, expect HIPAA. If you touch credit cards, expect PCI-DSS. If you touch anything at scale, expect someone to ask about SOC2.
Example: A healthtech client requires automated scanning in CI, manual security review every quarter, and proof of HIPAA compliance before any testing begins.
Expectations include:
- Isolated and locked-down test environments
- Sanitized or permissioned test data only
- Encryption and compliance for cloud tools (ISO 27001, SOC2)
- NDAs, background checks, audit logs
Usability, Accessibility, UX
Does it just work? Or does it work well for everyone?
- Manual usability testing with real users
- UI checks across devices (BrowserStack or scripted tools)
- Accessibility compliance: ADA, WCAG, keyboard nav, screen readers
Clients also expect A/B test changes. Harvard study: startups using A/B testing scale faster. Clients read it. They expect it.
Compliance and Regulatory
If there is an auditor, there is a test plan.
- Traceability from requirement to test result
- Audit-ready documentation
- Geographic constraints (for example, ITAR = U.S. citizens only)
Example: Defense software vendor requires QA team onshore, U.S.-citizen only, and full validation protocols in place before passing any release to staging.
In-House, Outsourced, and Hybrid Testing: Control, Coverage, and Fit
For clients, this is not a philosophical debate — it is about control, coverage, speed, and cost. Testing has to get done. The question is who owns what, and when.
In-House: Maximum Control and Context
You get full control. QA works side-by-side with devs. Same sprint board. Same Slack. No lag. You define the process. You own the tooling. You do not wait for updates or escalate through vendor PMs. Great for teams that move fast and need tight iteration loops.
Your team knows your product. Context-aware testing. Deep domain logic. Product fit is tighter. Internal QA is who product taps when a bug is patched and needs to be verified right now in staging.
In regulated industries (finance, defense, health), it is often mandatory. Everything stays inside the firewall. Lower IP leakage risk. Sensitive modules — health data, encryption keys, AI under patent review — stay internal.
But niche skills? You will need to train or hire. Security, performance, AI-based testing — expensive to grow organically. Staying current with trends = another overhead item. Scaling up? Slow. Hiring takes weeks. Downsizing? Expensive. Between releases, you pay for idle capacity.
Outsourced: Speed, Scale, and Specialist Access
You are managing a service, not a team. Vendors bring breadth. They have seen what breaks across industries and stacks. They catch what your team is blind to — because they are detached enough to test like users.
Need a performance engineer for 3 weeks? A HIPAA security tester? They have one. They often bring in new tools, approaches, frameworks you have not thought about yet.
Pay-as-you-go. Ramp up for a release, ramp down after. Vendors carry bench capacity. Offshore rates save 50–70% vs. U.S. salaries. It is faster and cheaper.
But unless scoped properly, do not expect instant response. Escalation paths and working hours must be clear.
You will need NDAs, VPNs, ISO 27001, SOC2 — and you’d better verify them. Smart vendors partition data and access cleanly.
What Smart Clients Outsource
- Regression Execution and Repetition Work: bandwidth relief for internal QA
- Test Automation Implementation: get the suite built
- Performance Testing: infrastructure, load simulation, diagnostics
- Security Testing: pen tests, SAST/DAST scans, independence for audit
- Localization and Usability Testing: native testers, unbiased feedback
- Burst Capacity for Deadlines: scale 5x before launch, scale down after
- Legacy Maintenance: low-volume systems no one wants to own in-house
The Hybrid Reality: Where Most Clients Land
Most clients do both.
- In-house owns strategy, sensitive flows, and long-term knowledge
- Vendors handle the heavy lift: regression, load, device testing, specialized audits
- Some use blended models: a few vendor staff on-site, rest offshore
Example: Enterprise client keeps 5 QA leads on-site, 20 testers offshore. All reporting flows through the internal QA manager. Regression, load, and UI testing run offshore at 70% lower cost.
Key to making it work:
- Shared test repos and bug trackers (Jira, TestRail)
- Regular syncs: joint daily standups, weekly reviews
- Defined roles: who owns what
- Knowledge transfer: internal QA shadows vendor work early on
- Consistency: same QA lead, same processes sprint to sprint
2025 Expectations: Trends, Experiments, and Emerging Standards
Client expectations are evolving fast — not because of hype, but because delivery models are changing underneath them.
Emerging Practices: Learning Without Committing
Clients watch early adopters. Not to copy — to test ideas in parallel.
- Netflix uses chaos engineering — failure injection in prod — to validate real-time resilience.
- Salesforce runs automated performance checks every release.
- ML-based prioritization and coverage suggestions are already in production use at multiple large organizations.
Clients are looking for practices that help them move faster with fewer surprises.
AI Is No Longer a Talking Point — It’s Part of the Stack
AI is not replacing testers — but it is changing what modern testing looks like. Clients now expect practical usage, not theory:
- Generative models assist in test case creation and script generation
- ML-based tools identify high-risk modules based on change history and defect clustering
- AI-powered test selection reduces regression scope intelligently
- Self-healing tests adapt to UI changes, reducing script flakiness
Clients want vendors to walk them through how these tools are integrated into real workflows. Many providers now offer services like custom generative model development and integration of AI into existing systems to enhance automation and predictive capabilities in software testing.
According to statistics, 85% of organizations now view AI/ML as a core part of QA strategy. If you are not integrating it somewhere, you are behind.
QAOps: Where QA Meets Delivery Infrastructure
Testing that lives outside CI/CD is no longer viable. QA now touches everything from infrastructure automation to observability.
- Containers (Docker, Kubernetes) are used to spin up disposable test environments
- Shift-right testing includes synthetic transactions in prod and user session tracing
- QA participates in pipeline health, alerting, and root cause triage
Clients expect vendors to integrate. If a QA partner cannot plug into Jenkins, GitHub Actions, or GitLab CI, they are a bottleneck. The same goes for log analysis and monitoring tools like Datadog or New Relic. If a vendor cannot help debug staging failures, they are not built for 2025.
Data Privacy and Test Data Engineering Go Hand in Hand
Realistic test data is now non-negotiable — but so is privacy compliance. Clients are not just asking if test data is sanitized. They are asking about the tooling, workflows, and access policies behind it.
- Synthetic data generation replaces production clones
- Test databases are subsetted and anonymized
- GDPR, CCPA, HIPAA compliance affects how data is moved and stored
Clients may expect vendors to handle test data lifecycle management entirely — or operate inside strict access boundaries with audit trails. There is no room for informal processes.
Device Testing Expands Beyond Web and Mobile
As IoT continues to grow, software testing moves beyond the browser.
Clients expect:
- Device lab access or simulators for physical products
- Network reliability tests under poor conditions (intermittent, latency, offline recovery)
- Compatibility checks across smart TVs, wearables, Bluetooth devices, embedded systems
Clients building on smart appliances or vehicles do not want “best-case” scenarios in clean lab setups. They want vendors who have tested edge-case environments — and have the scars to show it.
Security Testing Is No Longer a Separate Function
DevSecOps isn’t a buzzword. Security is baked into the QA cycle now.
What is expected:
- Static analysis (SonarQube, Checkmarx) in CI
- Dependency scanning (Snyk, Dependabot)
- Manual pen testing coordinated with QA regression
- Compliance baked in: SOC2, PCI-DSS, ISO 27001
Clients will ask how vendors handle secrets, encrypted test environments, audit trails, and access controls. If a vendor cannot show real compliance artifacts, they are not even making the shortlist.
Procurement Behavior Is Adjusting to Delivery Models
Clients now evaluate testing partners more like product teams:
- Fixed-scope, long-term deals are being replaced by short cycles with renewals
- Outcome-based pricing is emerging — tied to escape rate, defect density, and delivery velocity
- RFPs include live trial periods, scenario-based walkthroughs, and stakeholder workshops
Clients want to validate working relationships before contracts are signed. If a vendor cannot work inside the client’s stack during a test phase, it is over.
Caroline is doing her graduation in IT from the University of South California but keens to work as a freelance blogger. She loves to write on the latest information about IoT, technology, and business. She has innovative ideas and shares her experience with her readers.
