CX refers to customer experience – how a customer experiences the buying process. It is important to note here that there is a difference between the buying process and the selling process. The selling process is provider-centric; it concentrates on what the provider is selling and how it is selling it. The buying process, on the other hand, concentrates on what makes a customer buy. Thus, it focuses on what the customer wants and how he or she wants to purchase and obtain it. And that brings us to CX – Customer Experience.
Retail stores and supermarkets have long known that Customer Experience is the key to attracting and retaining customers. Offline, stores that offer a welcoming and pleasant customer experience, with friendly staff, well laid-out goods, an unhurried browsing experience, etc., can gain more customers and retain more of those customers than stores that want customers to simply buy, pay and leave. There are exceptions to this, of course – stores that have goods / services that no other can offer can easily, force customers to enter, buy, pay and leave. Such customers have usually decided what they want to buy and do so immediately upon entering the store.
Online, the customer experience is all about the customer being able to find goods easily, compare one brand against the other, and then make a choice, pay and leave.
Whether offline or online, Predictive Analytics is the key to making the customer experience great; so great that it influences the customer to revisit and buy again. Often, it is the key to influencing the customer to even search within the store for something that is unlikely to be found in that store, just with the expectation of being guided to the appropriate store! And this can be a golden opportunity for the store to sell something the customer hadn’t even considered buying.
However, it is in the realm of online selling that Predictive Analysis really takes its place in the sun. Companies have realized that most customers today far prefer to shop online than offline, because of the ease of operation, ease of payment and often, free delivery, that makes it easy to buy items that do not require personal interaction.
In fact, Predictive Analytics can make the online shopping experience virtually an offline shopping experience, by incorporating virtual shopping assistants who can guide customers through selecting and buying goods online. Imagine the equivalent of a Siri or Alexa popping up on a screen, predicting goods the customer may need and accessories to those goods. The day is not far off when a virtual shopping assistant, empowered by a customer’s search history and social media posts, is able to anticipate what that customer is seeking and guide him / her to the appropriate section. Let’s presume a man has recently gotten engaged and logs onto a shopping site. The site has already scanned that male’s social media and knows he will probably be looking for anything from a wedding suit to a flat on rent or for sale. Predictive Analytics can scan all his interactions and predict what are the most likely items / services that man seeks. It then becomes a matter of pleasantly offering that item or service and a complementary service.
For example, if Predictive Analytics predicts that a newly married couple will be looking for a flat, it can then offer flats on rent, lease or outright purchase – and additional goods and services – all in one offering. This will make the Customer Experience pleasant and the customer is very likely to visit that site again to order additional goods and / or services. That’s not the end of the power of Predictive Analytics. Predictive Analytics can analyze how a customer interacts with the login process of a site – for example, does he / she typically fumble a login, requiring a username + password reset – or is he / she able to login with no problem? If a customer typically forgets a username + password combination, the site can offer an alternative login at the outset, instead of requiring the user to first try the traditional process, give up and then request an alternative login process. This makes the login process smooth and encourages the customer to revisit the site. The power of Predictive Analytics doesn’t end at the login process, though. It can be used to present the customer with the items / services most likely to be needed by that customer, based on the whole background data analysis of past purchase behavior, social media posts / interactions and the economic, social, political and physical environment. Thus, the customer gets what he / she wants in the least number of clicks, pays with the least number of hurdles – OTP (One Time Password) is often seen as a hurdle in payment – and receives the shipment in the least number of days. That is the power of Predictive Analytics in Customer Experience