Digital Personalization During Face-to-Face Service Encounters

Introduction

Because of my prior experience in customer experience consulting, I chose to focus my master's thesis on a little-studied area of service design and customer experience: how in-person customer-employee interactions may be personalized through technology. My research proposed to explore these questions:

• Can customer data be used to enhance the customer-employee interaction?
• Do customers perceive a need for personalization?
• Is human error actually a desired part of interaction?
• What kinds of customer data and what forms of personalization provide the biggest improvements in customer experience? What kinds of personalization are socially acceptable to employees and customers?
• Are there any negative outcomes that might arise from using data to inform service employee performance?

To do so, I did interviews and scenario speed dating with service providers and customers, then held an online survey to discover additional details on what might make an encounter positive or negative. The results showed that customers and service providers believe that personalization will offer an improved service experience, but that it may be easy to deliver so much personalization that the service seems creepy. Most importantly, the data showed that further research in this area is warranted.

Opportunity Space

Online services like Amazon.com and Netflix monitor users' online interactions in order to personalize recommendations and other service offerings. Users might choose one service provider over another because of personalized content like this, but users usually won't pay more for it.

Many brick-and-mortar service companies such as hotels and retail stores operate loyalty programs that track customer actions and provide discounts as a way of generating loyal patronage. Interestingly, companies rarely if ever use the data collected on individual customers to personalize face-to-face service encounters.

There’s an opportunity for companies to personalize services for customers who are already providing data to the company via the loyalty program and other sources.

Research Process: Exploratory Research

In the beginning, I focused on the air travel industry so that I could easily compare what I learned from my various research methods. The airport setting also struck me as convenient for speaking with interviewees and user research test subjects because the airlines pioneered the use of loyalty programs (i.e. frequent flyer programs) and so the concept of loyalty programs in the airport setting is widely understood. Furthermore, since airports are technologically advanced and already require a high level of disclosure of personal information from all customers, I thought it would create an ideal setting to discuss with test subjects.

I interviewed several airline employees such as flight attendants, gate agents, and corporate marketing experts as well as frequent air travelers. I then made a customer journey map to synthesize what I learned from those interviews:

Insights from exploratory research

• Frequent travelers’ worst experiences were the result of times they lacked access to information, or felt that information was being withheld from them.
• Some of the interviewees’ most positive experiences came from mistakes they'd made that were clearly their own fault, when employees of the airport helped them.
• Customers who have travel rituals they enjoy (e.g., visiting a particular shoe shine station, visiting a specific restaurant) seem to enjoy the travel process more and roll with the punches better. Support for such rituals is virtually non-existent today.

From my exploratory research, five topic areas were developed for ideation:

1. New and relevant service offering: Service agent gives customer information about something new or valuable related to the store or service (e.g., new information relevant to customer’s interests such as new products or information that previously was not relevant to customer, but now is)
2. Error prevention: Service agent helps customer make a better choice such that the customer avoids a costly error.
3. Breakdown validation: Service agent acknowledges that a breakdown occurred recently with this customer, showing the company is sensitive to avoiding this outcome again.
4. Recognizing loyalty: Service agent recognizes that a customer has been loyal to the service.
5. Service orientation: Service agent captures the orientation (social, functional) a customer has to the service and then uses this information in the future to more personalized and appropriate performance.

Design Concepts

The main focus of my design phase was to experiment with the kinds of human-to-human interactions that are possible using a combination of technology and customer data. I used an online survey to explore the boundaries and types of interactions desirable to customers as well as employees.

Testing methodology

Using what I learned in my exploratory research, I designed ten service concepts that show how customer service agents can address each customer’s needs in a highly personalized way. For each service concept, I created a storyboard depicting the service interaction from the customer's point of view as well as the employee's point of view. In all, that makes 20 storyboards. A link to all twenty concepts is here.

I chose to conduct an online survey to evaluate the storyboards for a few reasons. First, I wanted to know if personalizing in-store service encounters based on customer data might increase people’s perception of quality for the service experience, and if so, which of the opportunity areas might represent the lowest hanging fruit. Second, I wanted to gain more insights on the industries and settings where customers value face-to-face personalization. Third, I wanted to understand when this kind of personalization might be experienced as creepy or stalking behavior. Finally, I wanted understand if frontline employees would be open to performing these types of services. Interviews with airline employees indicated that they were not particularly open to providing more personalized services.

The survey presented ten scenarios, one at a time, to each participant. When beginning the survey, we asked participants if they had worked as a customer-facing employee. If they said yes, they received five customer-point-of-view scenarios followed by five employee-point-of-view scenarios. If they said no, then they rated all ten customer-point-of-view scenarios. The scenarios were presented in random order, to eliminate any order effect.

Example storyboard

Sale notification for favorite item (customer's view)

1. Please think of a time when you recently shopped in a store like this. How does the above scenario compare to your own experience? 
     Less desirable  0  1  2  3  4  5  6  More desirable
2. Would this kind of customer service make you want to shop at this store instead of a similar store? 
     yes  maybe  no
3. Why?

Sale notification for favorite item (employee's view)

1. How well do the tools that this salesperson uses help to make them better at their job?
     Not at all  0  1  2  3  4  5  6  A lot better
2. How? Why?
3. How do you customize your service delivery when serving customers in this context?

Results of online test

The survey received 204 usable responses. Of the 204 respondents, 90 indicated they had experience as a frontline employee. Figures 3 and 4 collectively provide an overview of the ratings. In general, responses were positive, with no scenario receiving a mean score of less than 3.3. Collectively, respondents rated all scenarios as an improvement over their current service experiences. All scenarios from the frontline employee’s point of view earned a higher average score than the corresponding customer point of view version. 

Key Design Takeaways

• A service that uses personal data in a way that appeals to an individual customer’s service orientation or that provides utilitarian value won’t be perceived as a privacy violation.
• Customers are grateful for interactions that help them avoid a self-inflicted mistake.
• Customers and employees both would like to have access to more information. The amount of information distributed to individual customers can be determined based on a customer’s prior interactions with the service or company. 
• Customers are bored by quantified-self-type data: for instance, in interactions that provide them with about their past usage (e.g., “This is your 50th visit to Cinema Delux!”).
• Employees may find it useful to have personal information about customers, even if customers find the interactions enabled by that information to be mediocre. Giving employees data to help them feel more competent at serving customers may be beneficial to employee job satisfaction. 
• Data given out of context, even if highly useful to the customer, emphasizes the store’s access to personal customer data (e.g., alerting a customer of a favorite grocery item sale while the customer is shopping in a non-grocery department). Many customers will find this out-of-context data provision intrusive.

[1] “Service orientation” refers to the way different customers prefer different styles of interaction: serious, utilitarian, friendly; receiving lots of attention versus being left alone; etc. Although technology exists to maintain records of individual customers’ service orientation, customization of in-person service delivery using data is virtually non-existent, and is not a major area of study in the marketing and organizational behavior disciplines.

Additional process documentation is at my thesis blog: adfineman.wordpress.com