We certainly don’t need another example of how the nature of customer service has changed in the past 10 years, though an article I recently read hinted at its future: A startup is offering paper-thin sensors to install in the flooring of physical stores. By monitoring each footstep, these sensors can now track where customers stand or walk, how long they waited, and where sales occurred. Analysis of this data then suggests an improved customer experience through revised staffing, floor layout or better placement of products and coupon offers.

This unique approach underscores how digitization is at the core of a customer service revolution, and how the speed, complexity and volume of the customer data companies collect (which now includes footsteps!) are forcing significant changes in every business. That’s why we see a mandate for what I call customer-centric CIOs.

Track Every Data Point

A customer-centric CIO is a leader whose entire IT department is geared toward, and measured against, the customer experience. Doesn’t every CIO do that? Every CIO likely keeps close tabs on endpoint metrics that show how fast and available an application is delivered to an end user. 

But as Gartner suggests in a report titled “Innovation Insight for Digital Experience Monitoring” (DEM), simply tracking the end user experience is insufficient. Organizations must now go a level deeper and also track every data point that might contribute to the user experience.

This has implications for any business that uses technology as leverage for greater success — meaning it applies to all businesses. Here’s a look at five guidelines that can help re-orient your IT organization along this path.

1. Break IT Out of its Silo

It all starts with a culture shift. If your IT team is sequestered and only occasionally interacts with other departments, particularly marketing, that’s a sign that you need to break the organizational siloing that’s in place. While your company’s chief marketing officer and other department heads don’t necessarily want to get too deep in the technical weeds, they should be made aware of new IT initiatives and their immediate impact on the organization’s customers.

For example, will a new software-as-a-service update hinder sales team in the field? Will the new mobile app for human resources have the speed and availability needed to help employees enhance their productivity? Will marketing know — before dollars are spent — whether the enhanced website feature it requested will work well for customers in practice? If you’re not asking questions like those, and more, your first step is to align IT’s communication with the business divisions it serves so customer experience considerations are a factor in all technology initiatives.

2. Blend Real End User Data With Simulated Data

Tracking the experience of actual end users, whether they are customers or internal employees, is a vital function of any IT team. Too often, this data has conflicted with the simulated user, or synthetic, data that teams also gather. This debate must end, because the approaches are actually quite complementary.

Learning Opportunities

Real-user data shows you the actual path of an end user. For example, did customers get what they needed? Did they buy? Did they abandon the process? Synthetic data provides a baseline of performance understanding by using digital robots to simulate the speed, availability and reachability of services even when no one is accessing them.

This makes you better able to predict, and prevent, potential problems before real customers are inconvenienced. It also enables you to test applications in the preproduction phase without using real end users. Finally, synthetic data and real-user data, when analyzed together, can validate each other’s findings. For example, real user data may show that people are abandoning your landing page and analysis of the synthetic data may explain why: The page loads too slowly.

3. Take Responsibility for the Entire Delivery Chain

Instead of just monitoring how well systems perform, IT needs to take responsibility for the entire application delivery chain. This is the core tenet of the Gartner DEM report, and one that IT managers will resist the most, given the complexity and ever-growing volume of data involved.

Organizations historically utilized a process called application performance monitoring (APM). By mainly focusing on how an application performs, however, you’re missing all that went into it. Gartner’s Digital Experience Monitoring model asks IT to look at the entire application delivery chain: every cloud service, every data stream, every API, the domain name servers and all externally sourced elements affecting the application your customers use. Complicated, yes. Sometimes overwhelming, sure. But the result will be applications that are fast and readily available, and that provide intelligence that helps IT avoid problems when portions of the internet break.

4. Get Closer to Each Customer

IT needs to understand what every end user is experiencing. While that seems obvious, it’s a difficult challenge for IT teams because the performance of any internet-driven application degrades the farther the end user is located from the data center. If you’re tracking an end user from within your firewall on the East Coast, you have no idea what other users on the West Coast are experiencing. Even if you’re tracking from several regional monitoring points, you’re still blind to exactly what’s happening in some areas of the country. For businesses with an international reach, understanding the experiences of all users is particularly important.

As your end users become more far-flung geographically, you should expand the number of monitoring points appropriately so you’re capturing the most realistic views possible across various end user locations. As more people depend on mobile devices using cellular networks, the inconsistencies and gaps in service must also be factored into your plans. This will include tracking from backbone nodes located in data centers, as well as from 3G and 4G networks.

5. Reduce Mean Time to Detect and Identify Problems

IT teams already flooded with data will have to contend with much more as they put these guidelines in place. It will seem overwhelming at first, but eventually with proper analysis and dashboarding, the data will start to make sense. At this point, you’ll need to focus on shortening the time between detecting a problem, identifying it and understanding its impact on the end user. Eventually your new set of metrics will be more directly linked to business results, which is exactly where you want to be.

According to a Walker Information report titled “Customers 2020: A Progress Report,” customer experience will soon be the key brand differentiator, surpassing even price and product. CIOs seeking actionable data within their enormous data flows can use this as a reminder that while metrics can provide information about back-end systems, they lose relevance unless they offer insight into the true impact on end users.

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