If You Care About CX, You Should Care About Your Technology Road Map

by | Sep 20, 2019 | Cloud Software

Modern organizations are flooded with data from a variety of sources, as they collect billions of gigabytes of information each year. But often, the average contact center or CX executive doesn’t even have access to it. I would love to paint a rosy picture of executives having complete visibility into the entire customer journey, with dynamic graphs and word clouds on organizational victories across CX performance, but that just wouldn’t be the case.

The reality is that we are all on a journey of understanding how to measure, and then create actionable change based on those measurements. Customer experience is on the top of almost every executive’s list of things they know they have to prioritize. We have learned that seamless experiences drive optimal CX changes, but in order to reach the effortless you have to include technology.

If you’re in the same boat, you’d better be asking your CIO/CTO exactly what your tech roadmap looks like over the next two years. I say two years because, at the rate of change, anything planned beyond that is likely to significantly shift.

Since I am a contact center guy, let’s get back to talking about the roadmap as it applies to CX and contact centers.

Today, some of the leading call center executives are capitalizing on this deluge of data as a foundation to improve the individual customer experiences.

Imagine owning a theme park and knowing everything about each new guest — it would be impossible to organize the park’s layout — from rides, to food, to carnival games — in a way that was personalized to every single individual. 

But modern call centers don’t have that problem. That’s because call center technology has made it easier to scale and personalize experiences with contextualized data, improved organizational productivity and increased budgets for CX technology. These leading-edge call centers are already investing in RPA and AI technologies that are currently generating incremental improvements across the customer experience.

Exponential improvements to machine learning, natural language processing and artificial intelligence (just to name a few) are pushing the boundaries of how effectively businesses can serve their clientele. 

But before organizations can seamlessly connect their customer experience to cutting-edge technologies, leaders must first do a few things: 


Improving customer experience correlates to increased revenue. That’s because customers expect fast and intuitive engagements at every touchpoint, and they’re willing to exchange their business for effortless experiences. 

Your organization must take a holistic view of the customer journey, determine current journey gaps and decide where new technology might help fill the void. Reducing customer friction will be a rising tide across all of your brand interactions. 

But identifying the right class of technology, or the right vendor to supply it, is never that simple as every shiny new technology promises the world while you burn through cash hoping they deliver. 

To mitigate that reality, leaders must make an honest assessment of their biggest CX obstacles — and then ask a few key questions:

  • Do our customers expect us to have this technology?
  • Do our competitors capitalize on technology we don’t have?
  • How do our customers interact with our brand? Which channels? What are our KPIs per channel? What are the CSATs, NPS and customer effort scores per channel?
  • Would adding technology improve our organizational outcomes? Our customer experience? Both?

To help answer these questions, organizations can look to their collected data to help make sense of the customer journey. 

But before you can see the forest through the trees, you must: 


If you want a clear path to better customer experiences and improved tech ROI, organizations need to pin down the signal from the noise across their unstructured and non-normalized data. 

First, you must understand the difference between structured and unstructured data. In short, structured data is the easy-to-discern customer information you typically find in a relational database, like your CRM — things like age, gender, address, etc. 

Unstructured data, meanwhile, is the harder-to-quantify information your consumers volunteer across brand experiences, such as customer emails, recorded customer service calls, or survey responses to open-ended questions. Unstructured data might tell you that a customer is interested in purchasing a replacement part or that they wish to speak directly to a company employee. 

The better your technology captures and contextualizes this data, the better you’ll be at anticipating consumer needs and servicing your customers. 


Once you’ve captured your data, your team of data scientists has the chore of normalizing it so it can be useful. For example, let’s say you outsource half your service calls to a BPO partner that is providing the omnichannel platform. Meanwhile, you supply the CRM/system of record. It’s great that you are capturing data directly from the agent in your own system, but what about the communications data?

Each system in the market calculates different criteria in a different way. So how are you bringing that data back in to your data warehouse – if you are at all? If you are, are you normalizing the data before it gets stored for the Business Intelligence team to analyze? 

Thorough analysis of data across your customer experience gives you a comprehensive look at how customers interact with your brand. It also will reveal areas of improvement or technology issues you can resolve.


Clean and concise data can tell you a lot about your consumers. Proper data mining will show you how customers engage with your brand. 

So why is that important?

By knowing preferences and common consumer behaviors, contact centers can make educated judgments on the technology and features that customers will prefer and embrace in the future. 

For instance, while direct calls remain a huge swath of consumer interactions,the landscape has evolved over the last 30 years with more cloud applications, IVR features and self-service tools influencing CX. 

Features like visual IVR, bots of all kinds and AI-driven knowledge base tools are just a few you’ve probably dealt with. (And let’s not forget your mobile strategy for CX!)

Consumer preferences will always be changing, and will always dictate the customer experience roadmap. More data at your fingertips allows your leaders to be proactive with their technology roadmap.


Both EX (employee experience) and AX (agent experience) are growing considerations call centers need to manage as the competitive landscape intensifies. This is a common talking point in discussions with other industry professionals, and the general consensus is that EX/AX is driving better customer outcomes – and healthier bottom lines.

For example, RPA tools can create and automate remedial tasks that in turn offer significant savings to the customer. There are AI tools for agent assistance, which consistently increase agent satisfaction while helping improve a host of customer-facing metrics. 


If you care one bit about your customer experience, now’s the time to start planning and driving your technology roadmap. In order to meet the modern customer expectations, you have to deploy technology in many forms. 

You’re not the only one facing this challenge. Roughly 70% of contact center agent licenses are still connected to premise-based systems – systems that simply aren’t capable of quickly adopting new technologies as they emerge. At the pace things are changing that number will decrease, but you need to know where your tech roadmap is headed – sooner rather than later. 

The call center leaders that will succeed across customer experience will be the ones that identify the right people, processes and technologies to deploy, and the tech often comes down to picking the right vendors for your organization.


With so many technology options to choose from, Cloud Call Center Search can work with your experienced agents and managers to select the right cloud software technology and vendor partner to drive amazing results — fast! Work with an agent-focused partner that understands your industry and can identify the right vendors to produce the most impactful results. 

Fred StaceyFred Stacey has been in the contact center industry for over 20 years.  He started first as an agent on the phones and moved on to the operations side, starting and recovering failing call centers.  During that time, he worked in leadership capacities surrounding technology acquisitions and center build-outs, including ongoing call center management and selection of future leadership.  Prior to joining Corey Kotlarz to start Cloud Call Center Search, Fred worked over the past 16 years in executive-level roles in contact center telephony and debt collections software companies.  He has managed every aspect of a software company from running operations in Europe, the Middle East and Asia-Pacific to cofounding and participating as the COO in startups. Fred specializes in contact center and debt collections software, selection, business operations and strategy.