The customer journey is defined as the set of interactions that a person has with a company in the different stages of their relationship: from the moment a user has the need to buy a product or service to the after-sales strategies, including technical support or instructions for use, among others.
The customer journey is also often referred to as the «customer experience map». This means that every interaction will have its own experience. The launch of appropriate offers for a certain potential buyer and the design of unique selling experiences or loyalty programs, are actions that improve the customer journey and, as a consequence, also increase the levels of engagement and satisfaction of those consumers. This is a very sensitive aspect of the business. PwC, the global consultancy, has already detected that 32% of people are capable of leaving a company they love after just one negative experience. This number rises to 92% when there are two or three bad experiences.
Here, where the margin for error seems to have no place, data appears as a key asset to collaborate in the continuous improvement of this customer journey.
Each transaction leaves behind a wealth of useful information that can be essential for assertive decision making: the company knows precisely, for example, what products the customer bought, at what specific time, how long it took in online channels to make the decision, how many questions he asked and what other products or services he had already purchased. Only the increasingly common conversational AI tools are capable of recording entire conversations. The list can be as long as the organization itself decides: the data footprint left by the link between a customer and an organization is gigantic.
On the other hand, there is a second line of information sources that can be used: comments left by customers on social networks, for example, or market research.
At the same time, the company itself can generate feedback elements to analyze how the customer felt about the company, the support received and the product or service purchased. Even deeper questions can be asked, such as why the customer chose the company or its products. In this sense, the range of options is very wide and goes from satisfaction surveys done «in the heat of the moment», at the very moment of purchase to later inquiries, after some time has passed and the initial emotionality has subsided (in these cases, the response rate is lower, but the answers are usually deeper and more complete).
The step to action for a better journey
As is always the case in the world of data, it’s not just about collecting it, it’s about knowing what to do with it, turning it into added value for the organization.
This is where technology once again plays a key role, as it allows us to store data in a way that makes it easily accessible (for example, through a data lake) and extract value from them with big data, analytical tools and artificial intelligence to perform analysis, predict the probability that a customer will buy from us again, estimate the demand for certain products based on the experiences of consumers in their previous journeys or calculate the rate of abandoned carts.
All this learning can also be used to improve the customer journey by designing products and services that are more in line with customer needs, detecting and eliminating inefficiencies in the purchasing process, or optimizing customer-facing resources.
Thus, the virtuous circle is created: a richer experience is generated for each interaction with the client, customer satisfaction and loyalty are increased, and a new batch of data is available to continue to scale to the next level and achieve the ultimate goal: that the journey never ends.