Data cleansing (or cleaning), is used to refer to the process of detecting and correcting inaccurate, corrupt or unusable data. It is an essential step before any data analysis project, since every step after it assumes the data is “clean” or, in other words, trustworthy and accurate.
In Part 1, we were introduced to the main data types and what you need to look out for in your dataset before you set out to clean it. Here, we will be taking a look at the actual cleaning steps required to get your data ready for service.
The outsourcing industry is notoriously confusing and we’ve all heard horror stories about what can happen if you choose the wrong vendor. We compiled a list of six questions you should absolutely ask each outsourcing vendor that you consider to help determine if they will provide a quality service.
An effective customer service strategy is a cornerstone for building lasting customer relationships, driving customer loyalty, and enhancing overall brand reputation.
It is a ton of work to rip out an existing BPO partner and replace it with another, but it's often the right move. Read our guide on the five best ways to structure the move.
That first interaction with a barista can set the tone for the rest of your day. Walking into my local coffee shop and realizing my usual barista, the one who knows all my quirks isn’t on shift is definitely a nightmare.
Discover how customer support triage brings order to the chaos—so your team can respond faster and smarter while focusing on what really matters.
While experiences of this global pandemic vary between (and even within) industries, we can all find grounding in the number of powerful lessons we are being exposed to.
Being a customer is a pretty universal experience. So if we all do it, why are we so often disappointed by the customer experience we receive?
Any kind of company can use the principles of observation and shared responsibility to create the kind of customer experience that other businesses envy and that will keep your clients coming back for more.
