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Customer Experience (CX) Series

Part 2 –The Future of CX – Analytics, AI, and more

November 29, 2018

Steve Ronan 
Smija Simon

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In our previous edition, we defined customer experience and took you through how to design your company’s customer experience. In this edition we explore technology trends which touch customer experience.

Starting off with a quick recap, Customer Experience is the sum of customer acquisition and customer development & retention activities.

Technology and customer experience

If we take a look at the general customer journey example below, it is evident that technology is intrinsic even to a straightforward experience. How a company uses data gathered during all the customer’s interaction and leverages that data for analysis, then drive business decisions can help increase the precision of strategy and execution.

Customer analytics
Customer analytics is about the analysis of customer information and behavior to drive decision making across many aspects of business, ranging from marketing strategies, site location(s), segmentation, service channels, and even product development.

Often customer data sources exist within businesses in multiple systems. For example, a customer’s profile is captured in a CRM system, while order history sits in the ERP, and these may not be connected to the contact center systems which houses all the customer service history. The challenge is to identify ways to connect the various sources of internal customer data, publicly available Social data, and relevant Big Data sets to generate insights that help optimize customer experience and overall operations. Some examples:

  • Customer satisfaction: imagine your shipping department had the ability to inform customers of a potential delay in their orders due to inclement weather conditions – a customer is more likely to understand why their package is going to be 2 days late if they receive a proactive notification and still have high chance of a positive customer experience even if the promised delivery window is exceeded
  • Operations improvement: suppose an analysis on Returns data reveals that “incorrect size” as the main reason for returns on a handful of SKUs, this could be an indicator for the manufacturing teams to re-examine their process controls where a particular size is not being produced to specification and can help lower the cost of quality, and improve customer satisfaction
  • Predictive analytics: this is about current and historical data to make predictions about future events. One example that stands out is how banks are leveraging patterns learnt from customer interactions and customizing ATM interfaces to suggest actions based on past use. For example if your regular interaction at an ATM has been an $80 withdrawal, your landing page pre-populates that for you as an option without you having multiple keystrokes to navigate to that option.

Incorporating BI and Analytics into your Customer Experience design can create the ability to move from a reactive use of data to a more proactive use of it, and not just improve your Customer Experience, but overall business performance too. 

Multi- and Omni-channel enablement
Customers have multiple touchpoints with a business through their lifecycle. A customer may start off with researching your product/ service through an online channel, then move onto a direct channel such as a physical location to make a purchase and switch back to online for support. Being able to connect all the dots between channels and build a complete profile of the customer allows you to create a more meaningful experience for the customer. In this digital age, customers are becoming more demanding on companies to seamlessly interact whether it starts on social media then pick up the conversation by phone without having to take any steps back in the customer experience.

The Healthcare industry provides some examples of service industry omni-channel capabilities – for example being able to reserve a spot in line while you’re on your way to the urgent care, and when you walk in, the intake staff member already has the correct patient record lined up.

The retail industry has some of the more tangible examples of how multi-channel and omni-channel can be used – browsing an app for a product, adding items to your cart on the app, picking up the session on a web browser, ordering online and picking up in-store. All these conveniences are driven by app or website features with connections into the POS, ERP and CRM databases in the backend to orchestrate and present a unified view of data points to a customer.

Omni-channel enablement is about creating as seamless an experience as possible regardless of which channel a customer starts and finishes their journey. Achieving this usually relies on selecting and implementing the right systems and tools to enable the desired customer experience.

AI, bots and Robotic Process Automation (RPA) in CX
One of the growing uses of AI, bots and RPA (Robotic Process Automation) in CX is within the area of customer support. Chat bots are being used more and more on websites. These bots are trained using machine learning and AI tools and help automate responses to some frequently asked questions. When the bot is no longer is able to help, the enquiry is seamlessly transferred to a support agent. RPA applications on the other hand, tend to be more suited to repeatable tasks with structured data. For example, repetitive data entry or screen navigation in back office processing tasks could be candidates for RPA.

With so much potential for innovative applications of technology in CX, one can safely say that the future of CX is an exciting one.

Citrin Cooperman is uniquely positioned to advise and execute projects that will dramatically improve the customer experience and drive bottom-line impact. If you want to assess how your customer experience can be improved, reach out to us today!