A Case Study With Roojoom - Applying AI-Based Customer Journey Orchestration For Customer ServiceAdd bookmark
If I was to ask you which category would you think is most important to consumers when receiving customer service:
- accuracy of information and resolution
- speed and efficiency
- supporting the customer where and when they want
– Which would you say?
Most think speed and efficiency is the most important factor to consumers when receiving customer service. After all, no one likes waiting on hold, being transferred from agent to agent, channel to channel, or wasting time navigating a “frequently asked questions” page that never seems to answer your question.
However, when we asked consumers the above question, accuracy of information and resolution takes the cake at 42% of consumers rating this the number 1 priority of quality customer service, according to CCW Digital research – followed by speed and efficiency at 33%, with the remaining three categories totaling the remaining 25%.
And this makes sense when you think about it. If you were out to dinner, would you rather get poor tasting food immediately after being seated, or quality food and wait longer? Quality food of course.
While speed of service is undoubtedly one of the most important factors in customer experience (particularly in customer support), consumers want a quality product – whether that product is food in a restaurant, or the resolution of a customer service inquiry.
Resolving issues with personal AI engines
In customer service journeys, issue resolution can naturally have many options. However, the prediction of the correct resolution that would solve or answer a customer issue can also change in the course of the journey, depending upon an endless number of factors.
Where many customer service departments go wrong is when these endless number of factors that change the customer journey are not accounted for.
Now, with the emergence of Roojoom’s Personal AI engines with prediction capabilities, customer service departments are starting to enable optimization of resolution time and First-Time-Right rates, tapping into that number one customer service demand consumers are prioritizing - resolution. This applies to both digital self-service channels as well as agent-based channels, where Average Handling Time (AHT) can be significantly reduced. In the process, the solution gives accurate resolutions as efficiently as possible, meeting customers’ top two demands.
Roojoom was designated by Gartner as a 2020 Cool Vendor in AI for Customer Analytics and has AT&T and Comcast as early adopters of its technology.
Roojoom’s AI-based personal journey orchestration is an out-of-the-box solution for intuitive use by marketing and customer service teams, requiring no data-scientist resources from the service provider’s side. This applies to journey orchestration across any vertical and customer type.
Roojoom’s solution is more interesting these days as we’re witnessing massive digital acceleration in customer service, but in order to sustain digital adoption rates, self-service channels must be resolution-capable and not only route customers to the contact center. Digital channels that actually resolve more issues, would make customers call less, Yuval Shemesh, Roojoom’s CEO recently told me.
Roojoom offers an AI-based personal customer journey orchestration platform designed specifically for customer service journeys, marrying 2 disciplines -
- Journey Orchestration - driving customer journeys across channels and sessions from issue to resolution. This discipline is aimed at retrieving data and feeding information into backend systems.
- Customer Service issue resolution - applying information collected to create decision workflows for resolving customer’s issues with the correct resolution.
The result is a comprehensive “resolution capable” solution for service providers which can be deployed in a modular way - for accelerating digital transformation and for enhancing call center teams’ excellence. - Yuval Shemesh, Roojoom CEO.
Getting digital channels go beyond finding the customer’s intent
Unlike in many other customer service solutions, where AI is directed to finding the customer’s intent, Roojoom’s resolution AI fast forwards the journey to reduce resolution times and improve First-Time-Right rates.
The platform drives customer service journeys, continuously from issue to resolution across channels, for ‘troubleshoot & resolve’ technical or commercial issues.
The customer service operations team is self-sufficient in creating and operating customer service journeys applied to both self-service and assisted channels, as the user experience (engagement with a customer or agent) is auto-generated and based on templates. Therefore, it’s coding-free and doesn’t require developers.
According to a recent CCW Digital Market Study, 97% of customer service leaders plan on or have already ramped up AI investments between “slightly” to “extremely” to resolve more issues via self-service – since the pandemic. 94% say the same about using AI to route customers to the right agent. The pandemic has undoubtedly highlighted the exponentially increasing importance of AI - to marketers, customer experience analysts, and customer service leaders. It’s time to take the next step with personal AI engines.
“For example if you consider a telecommunications company and you go to a website, they know who you are when you log in, check your account, or whatever it might be. So it’s using that data to serve you up meaningful content… The company knows you’re an iphone user, showing you iphone accessories, not android accessories. So it’s using that data to serve you better content,” Forbes Communications Council member, and former marketing and CX leader at Verizon, Stacy Sherman told me.
“It’s a combination of the data you have, the data you might need to get, and create personas and journey maps for each individual.”
Roojoom’s Personal AI engines, invoked per customer, drive personal journeys continuously and persistently - from issue to resolution, forming a cohesive single journey, leveraging proactive customer engagements as needed (reaching out to customers that have unresolved issues) and replacing otherwise disjointed customer experiences. For example, a customer using a self-service channel for troubleshooting a technical issue, resulting in having to replace the device, will be followed up by the same personal AI engine, sending self-install instructions upon receiving the alternative device. Only when the issue is resolved, the journey in Roojoom’s system is terminated.
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