Blog article
When it comes to improving contact center performance metrics, even the smallest of increments can make a significant impact at scale. Process automation has focussed on improvements in quantitative efficiency, driving down average handle times (AHT) and automating simple transactional exchanges to eliminate the need for agent contact. However, for complex interactions, a different approach is required.
Co-browsing has experienced an increase in adoption across industries as varied as financial services, insurance, healthcare, telecommunications and online retail. Average handle time (AHT) is a commonly used metric for performance measurement within contact center environments. However, the nature of an involved, collaborative exchange between agent and customer is such that AHT alone doesn’t work as a metric for success. Using co-browsing to support a customer engagement may not always reduce the initial call duration but it reduces the likelihood of a repeat call, so the total “time to solve” is less. So what metrics does co-browsing impact and how can you calculate a return on your investment in co-browsing technology?
Pre- and post-sales support environments can vary significantly from sector to sector, and by size of organisations. However, some qualitative and quantitative metrics are universal indicators of success; all of which can be improved by co-browsing:
Let’s look at each of these in more detail, starting with some essential support metrics.
AHT is a core metric in customer service operations and measures the average duration of a single engagement. Co-browsing allows agents and customers to see the issue first-hand, allowing for rapid diagnostics and clearer communication, eliminating the back-and-forth that can occur on support calls and driving down the average time to resolution.
FCR is a leading indicator of how effectively your agents deal with customer enquiries. The real-time visibility provided by co-browsing eliminates traditional barriers to communication, delivering better call outcomes. At the same time, call transfer rates are reduced and repeat tickets are prevented.
CSAT is arguably the most important performance metric for contact center operators. High CSAT scores indicate a good customer experience and impact key metrics such as agent satisfaction and net promoter score. Happy customers are more likely to make repeat purchases and have a higher lifetime value to the business.
ASAT is also a critical component of contact center success. An empowered and motivated agent will deliver greater call quality and can transform a potentially challenging interaction into a rewarding one for customers and agents alike. Poor levels of ASAT can impact everything from operational efficiency to bottom-line profitability, as a high agent turnover rate impacts both costs and quality of service.
NPS is a measure of customer loyalty and can be influenced throughout the buying cycle. A product of other contact center metrics, NPS can be significantly improved with co-browsing by raising FCR, CSAT and ASAT.
Co-browsing doesn’t just add value in support situations. In a pre-sales engagement, real-time guidance can provide a personal experience and allow agents to explore opportunities for add-on or complementary sales, helping to raise average order values. It can also help overcome any barriers to purchase that might otherwise lead to shopping cart abandonment. With global cart abandonment rates at 70%, even a small improvement can impact profitability.
Read more about generating revenue opportunities with co-browsing.
The formula for calculating ROI is simple: ROI = (Net Benefits/Total Costs) x 100. However, quantifying the benefits of co-browsing may involve some complicated mathematics when you consider potential revenue increases, cost savings, and increased customer lifetime value. Of course, there are other intangibles such as avoiding poor customer service. Let’s look at one of the metrics we identified earlier and put some numbers behind the theory.
In this scenario, our contact center employs 1,000 agents, supporting 5 million customers that generate 45,000 tickets a day. If the contact center runs at a FCR of 80% there will be 9,000 tickets requiring additional troubleshooting. To make life simpler, we’ll assume these 9,000 tickets are all solved on the second call with an average handle time of 10 minutes, that’s 90,000 minutes, or 200 full-time employees working 7.5-hour days. Just a 5% improvement in FCR would prevent 22,500 minutes of calls. That’s the equivalent of 50 full-time employees who, at $40,000 per annum, would add $2,000,000 to the wage bill. Across all the metrics we identified, these incremental sums would add up to a significant cost benefit.
As a company scales, metrics aligned with operational efficiency become more important. While a team of 100 might not care about shaving 30 seconds from their AHT or increasing their FCR by 5%, the pain behind those inefficiencies becomes apparent at scale. For a company handling 100,000’s of tickets a day, a 30-second reduction in AHT or a 5% increase in FCR can mean many millions in savings.
Capturing pre-deployment metrics to use as a benchmark is key for measuring the impact of co-browsing technologies. These metrics should be isolated by team to ensure measurability for specific workflows and use cases.
While 100% adoption is always the goal, there will always be a healthy mix of early adopters and laggards. Understanding which agents have effectively incorporated co-browsing into their workflows allows for further refinement of the pre-post comparisons for more realistic ROI calculations.
As your team’s adoption of co-browsing matures, there will be use cases and/or tickets where the value associated is much higher. Once these are outlined, you can align your team to use co-browsing when it can make the largest impact. This ultimately leads to an improvement in the metrics above.
As previously mentioned, there will be use cases where co-browsing can provide the most value. To further understand the impact of co-browsing, you should sample feedback from users that links back to the ticket or use case they used co-browsing for. This ensures that co-browsing is positively impacting the quantitative and qualitative metrics that matter most.
Cobrowse delivers a wide range of benefits to the business. It improves customer satisfaction and confidence that their issue is being dealt with by the agent. It also provides greater agent satisfaction as they know they have access to a tool that helps them share in the customer experience and delivers value to every engagement.
Ian Roberts
Director of Care Operations and Technology, Quicken Inc
Co-browsing features prominently in modern contact center service portfolios and it’s easy to see why. Qualitative improvements in CSAT and ASAT are supported by the potential for significant cost savings, and deploying co-browsing across multiple channels, web and mobile, will compound the benefits and help maximize the return on your investment.
If you still don’t know if co-browsing is right for you, look back to some of those key metrics and ask yourself what has negatively impacted performance:
As contact center operations scale, the pain associated with even the smallest inefficiencies can add up. A failure to address the qualitative aspects of more complex engagements will impact performance across many KPIs and affect both CSAT and ASAT.
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