The ultimate guide to quality assurance
How does quality assurance (QA) differ from quality control? What role does it play in improving your brand’s products and services? Read on to find out how QA can revolutionize your offering.
What is quality assurance?
Quality assurance (QA) is the process of checking whether your services are meeting the standards of quality that you have set. This often includes monitoring and evaluating customer service calls, chats, and other interactions between your employees and your customers.
Quality assurance assessment ensures the day-to-day compliance of your team with legal and company regulations. It also makes sure that your team is offering what you consider to be a “quality” service in a way that’s standardized.
Quality assurance (QA) vs quality control (QC)
Quality assurance is generally focused on how processes are performed, or how service is delivered. It focuses on the prevention of mistakes being made through the creation and evaluation of processes, strategy, and brand policies. Usually, your quality assurance function will have a “checklist” of standards to mark services against.
It’s up to everyone to participate in quality assurance, though having an appointed person or group to monitor the team (customer service team leader or QA team member) helps to maintain standards.
Quality control is focused on the evaluation and management of quality for products. It focuses on correcting issues, such as product defects, and is concerned with carrying out a quality audit and taking corrective action, rather than deciding what checks need to be made. There’s usually a dedicated team for quality control that carries out the fixes needed after testing products. It is more common for businesses that have manufacturing processes and mass production to evaluate.
Your quality system encompasses the management of both quality assurance and quality control.
What is quality management?
Total quality management is the strategic approach to quality assurance. This includes planning as well as evaluation, helping to change QA scores from negative to positive through targeted action.
Though quality assurance methods are vital for a business to provide services that are productive and memorable, quality management takes one step further. It helps you to not only flag potential quality issues, but to take action to ensure that other issues across your business are resolved.
For example, your quality assurance team might spot that calls that end with a recommendation for another product increase the chance that the customer spends more than they originally planned. This might not be a factor that they have been instructed to check to ensure quality, but passing along that extra information to management might help change the way staff is trained for the better.
Ideally, the following approach should be taken to quality management:
- Collect data for analysis
- Analyze your data against your QA criteria
- Make individual suggestions for quality improvement
- Improve your overall criteria and approach by suggesting strategic changes
- Repeat actions that had a positive effect on customer experience
Why is quality assurance important?
Obviously, quality assurance is vital when checking to see if your services, products, and team approach are in line with legal guidelines for your business.
However, quality assurance is also about checking to see if you’re providing a consistently good service. Sticking to your own standards for customer experience is important for meeting customer expectations and setting yourself up for growth.
Calibrating your internal teams to ensure everyone’s offering the same service, no matter the delivery route, is key for success. Developing a reputation for reliability and top-quality service can be a differentiating factor when customers are choosing which business to purchase from.
Quality assurance can also help you to pinpoint opportunities for coaching and for organizational change. This is where quality management comes to the fore. Rather than quality assurance just being a box-ticking exercise, your quality assurance function can flag areas that need better coaching or structure and can highlight factors that are affecting success.
Taking their feedback into account helps you to develop a QA strategy that is effective and evolves over time to improve your offering.
Best practices for quality assurance
Quality assurance might be the last stage of your process, but it’s often where issues in products and services are caught.
Create a specific team for quality assurance
Depending on your business maturity, your customer service team leaders may be carrying out quality assurance checks on your service staff. While this is a good first step, it’s not the most practical way of ensuring you offer a consistent, effective customer experience.
Team biases might become an issue for impartial QA. You need to make sure you’re calibrating one leader’s idea of what quality looks like with everyone else’s. Team leaders already have one job to do, and adding more responsibilities to them is not the most efficient use of their time.
Having a separate QA team means you have a more impartial judge for whether you’re delivering quality or not. With the use of technology, this team doesn’t even have to be extensive. Ensuring you’re consistently offering a great service is made much easier with responsibility passed to a dedicated team.
Develop a robust set of evaluation criteria
If your QA team has a rubric to evaluate against that isn’t particularly clear or could be interpreted in more ways than one, your evaluation process is going to be flawed.
Make sure your team has a consistent understanding of the criteria you evaluate against and be open to suggestions as time goes on to add new criteria for quality improvement based on their experience.
Use technology to improve your processes
While it is possible to carry out quality assurance without the use of more than a spreadsheet, it’s not the most efficient or useful way of proceeding.
Many businesses take a random sampling of customer service calls and chats to evaluate service quality. Given the huge number of calls or chats a business might complete in a week, this can be a significant undertaking, and it doesn’t direct your QA team to the ones that are likely to be informative.
Technology that can help you evaluate all the data you collect and pick out the statistically relevant calls, chats, and more can not only speed up your QA process but improve it.
Using an experience data platform that includes conversation analytics can automatically evaluate calls and intelligently source them for you. Rather than just scoring the calls that your QA team evaluates, it can score all your calls, chats, social interactions, and more against your quality criteria. With a sophisticated platform, this is made possible using AI and natural language understanding to judge emotion, intent, and effort.
Instead of your team wasting time on irrelevant data, technology can pick out the most useful logs for QA to evaluate, and find pertinent trends by scoring all calls automatically. This saves your QA team time – and helps you to focus more on quality management.
Integrate quality assurance insights into your strategy
Quality assurance is often seen as being a box-ticking exercise, but it can be so much more when you view this process through the lens of strategic management.
When your QA team flags that there is an issue with how a call was handled, this typically affects only that customer service agent’s score on their performance. However, QA team members are uniquely able to get a view on where coaching opportunities might benefit the whole team – and this can become part of your overall strategy.
It’s not only your customer service team that can benefit from insights gathered during your QA process. Your product teams, sales teams and more can see more clearly if there’s a gap between your customer experience and your brand’s expectations.
Quality assurance use cases
Flagging issues and changing strategy to be more quality management focused
Let’s say your company has just implemented a new payment system. Your customer service team might notice an uptick in complaints calls specifying the new system as a problem. This might not automatically be flagged further up in the business, as your customer service team always resolves these complaints.
Your QA team – if instructed – can not only evaluate if your team’s calls are up to standard, but also evaluate if negative interactions are due to this particular issue. They can then flag this to relevant teams, and changing the approach to payments becomes part of your overall strategy.
This may already be something that your QA team does informally, but making strategic suggestions part of their role can help you to create greater cohesion between your teams and ultimately, a better customer experience.
Updating your approach to customer service based on data
In this example, your QA team is evaluating customer interactions with Agent A and Agent B.
Agent A’s calls take longer than advised. She takes time to make small talk with the customer. In your evaluation, you can see that Agent A’s ratings for customer service are higher. There are fewer repeat calls from the customers that interact with Agent A.
Instead of penalizing Agent A for taking longer than advised, your QA team suggests that it is more cost-effective to take more time on the original customer service call than to have repeat calls. As a result, you implement a new strategy for your agents that asks them to take time to make small talk to your customers.
Agent B has been instructed that it is acceptable to put customers on hold. Of his own volition, he informs the customer of the estimated time that the call will be held before he puts them on hold. His ratings for customer service are higher than his peers, though they all put customers on hold when appropriate.
Your QA team sees the benefit of managing customer expectations and implements coaching on expectation-setting for all customer service team members.
What makes a quality assurance program effective?
The best way to judge the quality of your service is to use intelligent sampling. Depending on business maturity, companies might be using:
- Manual sampling: Your QA team picks logs at random to evaluate customer service, team members. There are no criteria for this sampling other than it is a random selection. Only the samples selected are scored against your quality requirements.
- Automated sampling: Your QA team has “guardrails” in place to select their sample. For example, perhaps you automatically disregard calls under or over a certain time frame. Only the logs that are sampled are scored against your quality requirements..
- Intelligent sampling: An experience management platform or similar automatically scores all logs received against your chosen criteria. Using AI and natural language understanding, it determines which samples are statistically significant and delivers them to your QA team for evaluation.
A dedicated QA team
As mentioned, a dedicated QA team can help to avoid:
- Biased evaluations carried out by team members that have a stake in the score
- Responsibility overload for customer service leaders
- Missing opportunities for coaching and systemic change
- Repeat problems not being flagged for resolution
Using sophisticated quality management systems
Using technology such as an experience management platform offers the following benefits to your QA process:
- Intelligent sampling
- Removal of bias when sampling
- Full evaluation at speed of all the data you collect against your QA criteria
- Reduces instances of human error
- Ability to overlay different types of data in one location for a better understanding of the full customer experience picture
- Ability to identify patterns and trends in customer data
A quality management focused strategy
Rather than having a static approach to customer experience, a great quality assurance program has strategic thinking built-in. Your QA team should be enabled to flag points of interest outside of the criteria they’ve been asked to evaluate.
By focusing on building a data-driven quality strategy rather than box-ticking, your quality assurance becomes a key part of your business strategy.
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