Experience management

Carrying out the strategy and proper management of the omnichannel experience

Regarding digital transformation, in one way or another, all organizations have outlined their action plan and a fundamental part of it in order to be able to provide a personalized, individualized service that satisfies the customer experience so that in this way their loyalty improves. In parallel, the same aspiration could be developed for the organization's employees: to the extent that their experience improves, their productivity will improve.

Experience is a subjective concept that depends on each individual's perception. We all have our own experience every time we interact with a tool, go to a space, enjoy a service, or acquire a product. From the sum of those experiences, we shape our own vision of a solution or a company. The fact that it is a subjective concept does not cease to be measurable and it has been so for a long time, but through agencies that conducted studies on the street. Nowadays, this individual experience can be collected from any point where each person is located and can therefore be tracked, measured, compared, and consequently predicted.

When the will to serve the customer is not always the best ally

There are not a few organizations that have taken **customer service** to the extreme, sometimes to the detriment of the general interests of the institution itself. A negative opinion from a customer on a social network can trigger the **butterfly effect** within the organization, if the main objective is the satisfaction of any customer, at any cost. We have experienced situations where a negative experience regarding the delivery of a product to one customer out of thousands (for example) has led to meetings of digital, logistics, marketing, customer service, financial teams, etc. It could be more provocative to say that the customer is not always right, but the effect on organizational management is more concerning.

We want the client to have a good experience (Customer eXperience) and we want to safeguard the reputation of the brand (Brand eXperience). It is an objective that has been extensively studied in academic literature over the past forty years, but, being such a well-established organizational challenge, what do we now have that allows us to improve the traditionally applied approach? On the one hand, new technologies allow us to gather information (Big Data) from any action, no matter how small, that a client carries out directly or through our employees (salespeople, shop assistants, customer service) and through any channel. George Orwell would not have as much impact with 1984 in our days.

We know a client in such detail that, through artificial intelligence, we can build a customer profile by proposing stimuli and analyzing their reaction. We are able to anticipate the behavior of any client if we have enough information: "other clients with a similar purchase history, when faced with this stimulus, have reacted in this way, so there is a high probability that the same stimulus (promotion, coupon, call, discount) will elicit a similar response from the client in question."

If the above already seems like a challenge, what happens when we also question the client? That is, when we combine **artificial intelligence** based on objective data (what has been done), with the information that the client's own experience provides, about their motivation, about why they have done it.

What happens when, in addition to predicting their behavior with predictive analysis based on the profiling we have, the customer themselves provides us with their predisposition to make a new purchase. Here is the real leap in terms of experience. Up to now, we knew that a customer could be more or less loyal based on the amount of orders, their purchase frequency, or loyalty programs, among others.

On the other hand, we could learn how a product, a service, or a brand is perceived in a general way. Now, we are able to combine the experience of a specific transaction, both in digital channels... and in physical channels. We can now declare ourselves faithful to Ortega y Gasset because we have the customer and their circumstances. Returning to the butterfly effect. If we have what the customer has done (a complaint) and their objective context (what they have bought before, what other complaints they or others have made), and subjective (what they expected); the decision-making process on how the customer should be managed and what the experience entails can be made with complete knowledge (and it may end up in the massive meeting we referred to) but with full awareness, because in that case we will know that it involves a structural problem and not just an anecdote.

But how do we gather information about the experience and how do we manage it? What do we do with it?

With great power comes great responsibility. For each client who shares their experience or intention with us, we cannot employ an army of operators capable of interpreting the comments and feeding the profile in our system. Once again, tools are needed to collect customer opinions at every significant touchpoint and instantly analyze their feedback, triggering the consequent actions automatically through "Close-the-loop". Collection, analysis, and action.

Customer experience will continue to be collected through surveys and traditional forms adapted to different devices, but solutions that incorporate advanced text and voice analysis should be considered, so that through sentiment analysis, areas of action and customer predisposition can be identified. By advanced, we mean natural language. For example, if someone gives an opinion in a free text field, they will likely include both positive and negative aspects in the same response: "even though the package arrived late (logistics and negative experience), the product exceeded my expectations (product and positive experience)".

These advanced solutions should also include predictive analysis to determine whether consequent actions should be immediate or not (who the customer is and what they are requesting), and additionally, enrich the specific customer profile.

Similarly, these tools should ensure the experience they aim to measure, meaning that if the customer belongs to a target segment, we cannot overwhelm them with continuous information requests, or if they are willing to respond, we should maximize their feedback in the same survey to capture multiple dimensions.

Finally, the most advanced platforms are those that provide aggregated dashboards that analyze the organization's behavior historically and across multiple areas. This traceability is what allows correlating the actions taken (campaigns, promotions, events, launch of new products or services) with the overall performance of the company and specifically of the different areas being measured. Prediction once again plays a role in this aggregated view, and these solutions become the main tool to aid in strategic decision-making by suggesting actions or areas for improvement in the organization based on the information gathered and the historical data they hold.

Recapitulation and conclusions

All the referred use cases are addressed through the alliance between SAP and SEIDOR, which guarantees an end-to-end solution, based on the market-leading solutions: Qualtrics, SAP Marketing, SAP CDP, and the suite of SAP Analytics Cloud. The SEIDOR team combines the capabilities for the different scenarios covered in this article and with experience in multiple sectors at national and international level.