In this first of a two-part series, Farzad Aref, Founder and CEO of Farlinium, joins Matt Egol of JourneySpark Consulting to discuss how to create a continuous improvement cycle that leverages insights to drive ROI for your CX. This conversation is the first in a series focused on leveraging insights at every touchpoint to enhance customer experience and improve business outcomes, and it focuses on the "what." Watch the second part, focusing on the "how," here.
Throughout the conversation, Farzad and Matt delve into the significance of capturing and analyzing customer feedback from various channels and technologies, emphasizing the power of unstructured data and natural language understanding. They share their experiences working with Qualtrics' XM Discover platform and discuss the evolution of customer experience measurement and analysis. By watching this video, CX professionals will gain valuable insights into creating a continuous improvement cycle and utilizing data effectively to maximize return on investment for customer experience initiatives. We hope you find it helps you to stay ahead in the dynamic world of CX.
Matt Egol: I'm excited to be here today with Farzad for the first in our video series on embedding insights into a continuous and proven cycle at every touchpoint. , Farzad a good friend and business partner from Farlinium, where we're working with Qualtrics to help companies drive more value from their investments in customer experience.
Thanks so much for joining Farzad
Farzad Aref: Thank you so much for having me, Matt. Looking forward to our conversations.
Matt Egol: So just to get the ball rolling. Farzad, why is embedding insights into a scalable continuous improvement cycle so important to realize value from your investments and customer experience.
Farzad Aref: That's a really good question, Matt. I think that's really important because first and foremost, we're living in a world right now where, through a lot of transformations, customers have a lot of options in both how they're doing business with customers and also what they're expecting, and in those expectations. I think that it's extremely important that when they run into either an issue or a pain point, they're gonna be sharing that feedback with companies through a lot of different channels and technologies have really evolved over the course of recent years where you're able to actually tap into all of those conversations no matter what the channel.
And be able to extract not just what the frictions are or suggestions, but also what the feelings are , and knowing that and being able to actually drive improvement and insight from it, I think really can bring sort of the expectations that not only customers have, but the business results and benefits that you can get from it as well.
Matt Egol: I think that's a really good point about getting beyond the technology itself. And focusing on the business value that you're looking to create across all the different touchpoints. And you talked about, you know, the, the growing sense of data unstructured data. Do you wanna elaborate a little bit about what are some of the most fertile areas to leverage this data to build insight?
Farzad Aref: Yeah, so we've been doing a lot of work for years now with Qualtrics, specifically their XM Discover platform, and it's been amazing to see. So with XM Discover, you're able to essentially bring in any sort of conversation or feedback from your customers and apply very advanced natural language understanding and AI to it.
To not just understand and extract what these sentiments are, but really to uncover what is the effort you're putting on your customers and what are the areas where those efforts are being experienced? What are the emotions that they're invoking? And that creates really a good opportunity for you to do a closed loop process, whether it's inner or outer.
As we think about that and, and look at companies, right, and, those channels, that customers that are talking to them first and foremost, a lot of that is unstructured and qualitative, right? So it's gonna come through feedback and conversation, not necessarily just a dropdown or a a what we call a .define or structured attribute.
Second of all, from a volume perspective, as everyone knows, digital is huge these days, right? And with the adoption of digital now, you have a lot of information that are coming either through the social channel. It could be coming through customer service from a digital channel or a more traditional channel like phone conversations.
So imagine if you're able to tap into your mind all of that information, you're able to get really good aggregated insights and compound it on. What are those main points that are sort of coming together from analyzing all of these different channels?
Matt Egol: I think that one of the exciting things from the work we've been doing together is the ability to take learnings about what worked in the earlier days of the call centers and social media to mind this unstructured data and now leverage it a more integrated way where you're leveraging this data as you were just talking about, for continuous improvement cycle. So instead of just having your annual listening or your relationship, listen, Or periodic pulse surveys around specific transactional moments, you're able to drive a continuous improvement cycle where there's always fresh insights, mining the data to drive the right set of use cases that you're working on.
How do you see this evolving? You know, what do companies need to focus on to get this recipe right of continuous improvement using all these data together?
Farzad Aref: Yeah. From what, what we've observed over the years, like the initial approach was. Some combination of running a post interaction survey, right, to kind of understand essentially the CSAT or customer satisfaction of that interaction. And that usually is paired with some level of quality management where you know, their, their the quality Analysts are essentially randomly selecting a handful, five calls per representative or agent who's cor it now with technology, right? These recordings are, are available. They're very easily transcribable so that you can run tech and speak analytics on it.
And, and the next evolution we saw in that is then when customers started to kind of expand their ability to analyze this information. And we're starting to focus on just traditional scores of what is the customer sentiment score. As we look at the calls, what is the agent's score? And I think that the more advanced and more mature customers that we work with, they're actually focusing on modeling the.
Outcome. At the end of the day, when we're analyzing these interactions, are we addressing the issue correctly the first time around so we're not getting repeat calls? Are we doing that in a way that is providing a positive customer experience? Right? Where we're not putting a lot of effort on our customers, we're educating them on self-service options that they might have and proactively trying to fix those issues. And lastly, like what's really interesting is actually some companies are starting to tap into that from a sales opportunity perspective, right? So while they have the customer on the interaction side, can they actually educate them on other service offerings that they think is relevant as it's you know, personalizable to that customer.
And that's the area that I think we're gonna see the biggest innovation in is less about traditional measurement, but how do you actually take that information and provide real-time opportunities that will both elevate the customer experience as well as again, create a positive contribution to your goal from a business perspective