By Daniel Fallmann
As the demands and expectations of customers continue to rise, their tolerance level for poor service is dropping. Offering customers impeccable support in response to requests is a core differentiator, particularly in highly competitive markets. But delivering the best possible customer service is fast becoming a challenge, especially given the steadily escalating number of products and services, along with the surge of hybrid work structures.
The digitalization boom and, most notably, the adoption of new digital communication channels has triggered a change in expectations at the customer level. They’ve come to expect faster and more personalized service, primarily through digital channels. Meeting these demands requires reimagining and redefining both the workflows and the provision of required information.
In particular, the way in which data is managed, processed, and extracted must be adapted to the new circumstances so that it can be processed qualitatively and applied effectively in business processes. As a result, the ability to evaluate and link data intelligently and to make it available holistically now stands as a crucial factor for the success of a business.
Infodemic: A Challenge in Hybrid Workplace Models
State-of-the-art customer service means 24/7 availability, always staying current, and delivering a speedy, friendly, and accurate response to incoming requests.
To satisfy these customer demands consistently, employees need instant access to the correct facts, the latest data, and up-to-the-minute customer information, as well as the most recent valid product, price, and approval lists. If this information is only available in piecemeal form—in multiple documents—then searching for details and essential information just to get specific tasks done is every bit as much of a problem as not having the information at all.
On top of this, the increasing demand and popularity of working from home and on-the-go has given rise to a remote, decentralized workforce in which some of the staff work from home or on the road, while other co-workers hold down the fort in the office. That kind of hybrid work environment can make it difficult to maintain a smooth flow of communication and information, leading to heightened stress levels.
Holistic Views: A Magic Bullet for Customer Service Reps
This boils down to the fact that customer service staff need simple and reliable access to information to gain a comprehensive overview of pertinent data from multiple disparate sources and departments. Use that holistic view of customer data with an analysis of the information from the various sources to identify trends and generate actionable insights to answer specific questions. Applied correctly, this knowledge will enhance the customer experience, drive customer loyalty, and enable companies to utilize their time and resources more efficiently.
Similarly, customer service representatives also need a tangible 360-degree view of the customer and the customer’s activities so that they can respond appropriately.
Instead, companies tend to have several different tools for data storage (business applications, cloud storage, and so on), yet often lack a tool that analyzes and intelligently links all the data stored there.
Four Steps to Prepare Intelligent Information for a Hybrid Work Environment
Step 1: Define the Use Case: To start with, you need to determine “where.” That is, in which department or—even better—in which specific use case your employees need the most support.
One way to approach this is to specifically involve your staff in this process. Ask them questions, analyze their problems, and identify workable solutions. A useful starting point can usually be quickly established this way.
Step 2: Evaluate the Available Systems: The number of innovative technologies and systems is virtually endless. Making the right choice is a daunting task. Different vendors with different approaches—from simple knowledge management systems to AI-supported solutions—all promise a swift solution to the problem.
At this point, it’s about a lot more than just choosing the right application; it’s also about how to implement that application. Many systems are available both on-premises and as cloud services or even as hybrid models. Which option is the right one for your business hinges on several factors. For example:
- The existing data sources, which ones, such as SharePoint Online or Microsoft 365, are available?
- The desired level of data security. Is the data considered sensitive? Is this data allowed to leave your company?
The best practice is when companies choose a system that corresponds to the use case defined beforehand and solves the existing problems efficiently.
Step 3: Conduct a Test Phase with Your Own Data and Experts: When it comes to implementing a suitable system, the proof of concept (PoC) is an important milestone because it helps companies separate the wheat from the chaff. When conducting a PoC, it’s wise to test the solution based on your own data to see if the requirements you’ve identified can be implemented with the solution. At the same time, a PoC using a company’s own data makes it possible to identify problems at an early stage.
Once the system has proved its merits from a technical point of view, the next step is to involve the real experts—the users from the corresponding departments. They understand the processes and can pinpoint potential areas for optimization. Their feedback is instrumental in ensuring a successful roll-out and full acceptance of the solution.
Step 4: Go Live: With the successful conclusion of all tests, the transition to real operation can begin. Ideally at this point, all the settings can be migrated seamlessly from the test setup to the production system. Once the go live phase is successfully underway, roll out the system to other departments or business areas, transforming all processes along the way.
Conclusion
These four steps highlight how simple it is today—thanks to existing solutions—to support your workforce sustainably in their day-to-day work. Customers expect companies to handle their concerns quickly and effectively. High quality and superior performance, backed by targeted big-picture data, are the KPIs that drive a company’s success.
Daniel Fallmann founded Mindbreeze in 2005 at the age of 23 after completing his studies in computer science. With many years of experience in the computer and information technology sector and as the CEO of Mindbreeze, Daniel is a living example of high innovation and quality standards. From the company’s outset, Fallmann, together with his team, laid the foundation for the highly scalable and intelligent Mindbreeze InSpire appliance. His passion for enterprise search and machine learning in a big data environment inspires Mindbreeze employees and Mindbreeze customers alike.