In most cases concerning customer experience, one can discern more, and less skewed, insights by pulling them from this now robust and rich dataset. Think about it; when do most people generally provide feedback? Not as often when everything goes the way they feel it should. This has the potential to skew the results negative and will result in spending time putting out fires and addressing only the worst pain points. Which is important, but excellence is in the details. I won't attempt to list all the ways this data could be used to enhance client experiences, but I will give two possibilities: CX Dashboards and Smart Profiles.
Building on our example using Snowflake and the wealth of data combined with its performance capabilities, stacking Alteryx and Tableau into the mix we can create a dashboard that provides immediately actionable insights and performance against targets. What are the average hold times throughout the day and when do they spike? Should you hire because they're always high, or is there something you can do with work schedules? What is the industry average in this instance, and what are customer expectations? If you can't hire more people, how else might one ensure hold times never exceed these expectations (which, depending on the survey is generally between immediate answer and less than one minute)?
I would suggest capping hold times at one minute, effectively hard-coding a better experience, when the caller is prompted to advise whether the number from which they're calling is how they should be called back when it's their turn in line, or enter another. And whatever you do, never automate a message telling someone how important they are while they wait. If this were true, an investment would have been made in some form to address it and people realize this.
One can imagine many and better CX performance indicators that could all be on a single screen, real-time and tied to industry standards, with the ability to drill into any given metric for additional detail. Consider this 'Macro CXBI' to allow leadership to operationalize takeaways and react in real time to immediate threats to the desired experience. At the individual level, 'Micro CXBI', Artificial Intelligence has advanced to the point where it can be used to group data the organization has collected across its channels and across shared and publicly available datasets into Smart User Profiles, requiring minimal, if any, input from the customer. It should be noted here that for some a better user experience is the ability to opt-out for privacy concerns, with messaging on how that will degrade the experience they have interacting with the company.
Going back to the hypothetical cashier asking whether you're still happy with the exact item you bought on their website a month ago, how is this possible without a 'rewards card' or something similar? It could be simple. While it may not be desirable to save credit card information for payment purposes on the general user interface, it could be securely stored in the dataset as an identifier that includes the credit card number and name. When the same card is used again at the physical store, the User Profile appears on the cashier's screen prompting them to ask the question.
Now the challenge of multichannel approaches has become an asset as each is used to collect identifying and purchase history information not collected in the other. Online, users are prompted to provide their email address for tracking purposes. Over the phone the number is automatically associated with payment details - which can be used as a key to blend the data from various sources. Cashiers can be provided an interface to enter additional information from their in-person interaction. Problems, like poor cell coverage at home, can be known and resolved without customer escalation (phone speed data is knowable and trackable over time and geography).
The only limit is our ability to imagine applications.
Salesforce, for one, long ago began enabling and prompting users to do things for purchase anniversaries or birthdays, but the touch here may be a hand-written note. And of course, the cashier has to do something with the screen prompt. However, there are instances where this experience could be automated, such as in the cell signal booster example.
Most importantly, though, is that this Business Intelligence approach to Client or Customer Experience Management provides concrete, specific actions that can be taken to provide the 'Wow!' experience some two-thirds of marketers believe they're already doing. For the most part, they're not. Investing in CX and the BI tools to do it consistently, across all channels, and at scale is how it is done successfully, and the investments will pay dividends in the form of repeat business, referrals and positive reviews, and gained market share. One is either succeeding or failing in this arena. Success may very well be survival.