Compared to typical legacy software firms, SaaS organizations require a fundamentally different customer support model. Their customers use their technology on a daily basis, and for their support staff to deliver efficient, individualized assistance, they require real-time access to operational customer product data.
In order to improve contemporary SaaS customer care, there are four key differentiators. In order to comprehend this, we must first respond to a frequently asked question that rings throughout the industry: What is the difference between on-prem support and SaaS support? We must know the benefits and drawbacks of the cloud.
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Why is SaaS Customer Support Important for Companies?
Many businesses have switched to the cloud because it offers less complexity and reduced total cost of ownership, among other benefits. Since the cloud provider owns the implementation and the technology is hosted on their servers, problems should theoretically be fixed more quickly. Additionally, because the technology provider owns and maintains the system, they have access to all the log files and clickstreams, which helps them understand how people use it and be aware of any problems that may arise. On how to improve workers’ output and methods of operation with cloud computing organizations, there are many diverse viewpoints. Support and engineering regularly communicate and work together; however, with on-prem, there is a more siloed approach, making it more challenging for these two groups to display.
Additionally, the cloud’s emphasis on product-led growth makes it possible for more support interactions to determine what new features are required.
One significant finding from the Technology & Services Industry Association’s (TSIA) 2021 Support Services Benchmark is that cloud users have half as many deployment and configuration problems. There is greater uniformity in the application of cloud technologies, and you don’t need a large implementation crew on site. However, every customer is impacted when there is an outage.
Different Issues in On-Premise and Cloud Support
The number of product releases in the cloud versus on-premises is, as we all know are far higher. Moving to the cloud has both positives and cons, with many cons being in a “can be handled” stage. The four prerequisites for contemporary SaaS customer support follow from this.
Cloud enterprises require a reliable escalation procedure
The fact that assistance is managed as a cost center necessitates improved efficiency and coordination. The largest issue is locating pertinent information. To help frontline workers make better decisions, data needs to be contextualized and connected across sources.
Through perceived value, we can move from being a cost center to a growth driver. Imagine you are utilizing a platform that continuously correlates data, learns and develops as the business expands, and improves the optimization of your current investment. It will be viewed as a growth driver in that situation. It alters the conversation for a support leader around how to benefit the organization. A platform for intelligent support operations makes sense for this reason.
Additionally, you need to spot recurring problems, and visibility is essential for this. Why can’t the same strategy be applied to support as well? DevOps and engineering have many automation technologies that streamline operations.
SaaS support agents must recognize faults with products promptly
In a cloud context, SaaS support agents must swiftly and precisely identify product faults using product data logs and usage statistics. Support has to be able to see everything that is happening in the cloud. However, in practice, it doesn’t operate that way because accessing information requires support to go through DevOps, a CloudOps team, or the Engineering team, which takes a lot of time.
The TSIA Support Services Benchmark shows that Priority 1 tickets typically take five days to resolve. It seems reasonable that resolution time can be shortened by determining where the consumer is experiencing the problem. According to the same survey, Priority 2 tickets may take up to eleven days to be resolved. There must be a more effective approach as well as a contextual and real-time correlation engine.
The other issue is that support often uses Salesforce, while development typically uses Jira or Slack, and the two are not connected. According to the TSIA’s report, 75% of cloud organizations operate support as a cost center, which implies they may not have the necessary employees, technology funding, or tools.
Cloud enterprises need to be proactive in resolving client complaints
According to the TSIA study, there is a strong correlation between contract renewal rate, support, and customer happiness. To make money, cloud service providers rely on renewals. In a SaaS environment, your support experience cannot be distinct from your product experience. Companies’ understanding of data is crucial for product-led growth. Why can’t support teams use the same data when it happens on the sales and marketing side?
Support should also have access to the engineering and DevOps data. Support can now be seen as both a cost center and a source of competitive advantage. But automation is required here. A successful customer experience and revenue growth depend on unified customer insight and AI-driven operations.
SaaS support agents require a deeper level of product expertise.
Technologies are developing so quickly. As a result, it can be difficult for support agents to comprehend the tools, how users interact with them, and what is new this week. Product signals must be used to supplement knowledge. The average client in our customer base uses 12 to 15 tools in their support environment. The environment contains the content of the resolution, the user journey, and the backend logs pertaining to the error locations. The information is isolated, though.
How can we equip the agents with current product insights in addition to providing them with knowledge? A contemporary support solution can correlate data from the customer journey in real-time. Therefore, you no longer need to inquire about the customer’s usage of the goods.
If a mistake happens, you can correlate it with the log files and alerts at a level of infrastructure to help the agent rapidly pinpoint the problem. Is it an error? Is this a bug, or has something similar happened before? The agent benefits from this advice. Instead of copying and pasting content between tools, clients should be better engaged in discussion.
Conclusion
In order to improve contemporary SaaS customer care, there are four key differentiators. This article deals with all those four must-haves for modern SaaS customer support that you need to know in 2023. To know more about these, connect with SaaSworthy.
