Design a Differentiated Online Experience: Insights from eBay China and Taobao


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Every year, I travel from Shanghai to Singapore several times and choose between Singapore Airlines and several Chinese airlines. Although I prefer Singapore Airlines, the premium price is a barrier. Recently when planning a Singapore trip, I found a cheaper and better way to book a flight on Singapore Airlines: via the web site. Not only was the price lower than the Chinese airlines, but also I could choose my seat and tailor my meals. Systems drive behavior. I changed my flight-booking habit from traditional (via phone or at a sales office) to an online touch-point.

Whether for the sake of corporate cost control or customers’ convenience, nowadays we are all facing this trend. We are directed—or incented to shift—to online touch-points. Making your customers “feel good” during their online experiences is—and will continue to be—one of the primary concerns of business executives, especially as more transactions take place online. The challenge of the online channel is similar to that of retail and call center touch-points: how to deliver a differentiated experience, given severe competition and limited resources. Complying with the quality level set by renowned standards organizations or achieving high customer satisfaction scores are proving more and more irrelevant in delivering a differentiated experience.

Online Customer Experience Survey in Mainland China

Nobel prize-winning psychologist Daniel Kahneman discovered that people remember only two things during an experience, how they feel at the peak (either best or worst point in the process) and how they feel at the end.

When satisfying the most important needs of your customers and highlighting your brand values at the positive peaks, this “branded” experience deposited in each customer’s effective memory drives positive behaviors, such as repeat purchasing, brand loyalty and good word-of-mouth.

On the other hand, when the most important needs of customers and your brand values are reflected in the negative peaks, this “un-branded” experience deposited in each customer’s effective memory drives negative behaviors, such as reduced purchasing, churn and bad word-of-mouth. Thus, it is not only important but also necessary, to identify the peaks (both positive and negative), to locate customers’ most important needs and to identify your brand values before you try to manage and enhance customer experience.

Consider two e-commerce sites that stood out in Global CEM and the Web Analytics Association’s recent online survey: retailer Taobao and auction site eBay China.

For the survey, Online Customer Experience in Mainland China, we received 2,015 valid responses and categorized the entire online experience into the 22 sub-processes in the chart below, assessing respondents’ emotional feelings and mapping the emotion curves of surveyed web sites to derive the drivers of positive and negative online experiences.

S1 Loading speed S12 Product quality
S2 Visual design S13 Online enquiry
S3 Site navigation S14 Purchasing history
S4 Effective links S15 Customized web page
S5 Search functionality S16 Customized promotion info
S6 Product category S17 Payment option
S7 Product display S18 Freight costs calculation
S8 Product info S19 Delivery option
S9 Product review S20 Order confirmation
S10 Product variety S21 Goods return policy
S11 Product price S22 Complaint system

Unlike most conventional satisfaction surveys, this research adopted a natural time sequence from the beginning to the end of the entire online experience. It was experience-centric instead of focused on process and efficiency.

EBay China versus Taobao

Taobao and eBay China dominate the e-commerce market and represent the ends of the spectrum—Taobao rated high among sites people “mostly loved” and eBay China rated high among those people “mostly hated.”

Figure 1 shows the emotion curves that match the emotional feelings at the 22 sub-processes of the entire online experience between Taobao’s “love” curve and eBay China’s “hate” curve. (Note that we compare only the “love” curve of Taobao and “hate” curve of eBay China for this illustration.

Figure 1 Emotion Curves of Taobao (love) and eBay China (hate)

Based on the “love” emotion curve of Taobao and “hate” emotion curve of eBay China, we should be able to identify their positive peak (the sub-process that drives the “love” emotion the most) and negative peak (the sub-process that drives the “hate” emotion the most), taking into consideration the “weighting” factor. Figure 2 shows the survey respondents’ weighting of the 22 sub-processes.

Of the four highest-ranked sub-processes on the Taobao “love” curve, only product variety and payment option can be regarded as both important to respondents and satisfactory sub-processes. On the other hand, at the “hate” curve of eBay China, product quality, online enquiry, return policy and complaint system are important and yet perform poorly in terms of satisfaction.

Figure 2 Importance of 22 Online Customer Experience Sub-processes

To determine whether the sub-processes are effective (memorable) positive and negative peaks, you have to refer to the “love” and “hate” drivers (Figures 3 and 4). Consumers may love and hate for different reasons. For example, when we asked the survey respondents why they “loved” any e-commerce web site, more than half cited convenience (29 percent) and product variety (26 percent), but when we asked them why they “hated” any site, only one-fifth cited convenience (8 percent) and product variety (12 percent). Here product price (18 percent) and web site design (18 percent) determined the negative emotion. Different decisive factors dictate why consumers stay loyal or stay away.

Figure 3 “Love” Drivers for E-commerce Web Sites


Figure 4 “Hate” Drivers for E-commerce Web Sites

Using the ratings and weightings of all the sub-processes during the online experience and countering them with the love and hate drivers, we identified the most relevant and important sub-processes during the entire experience: those that drive customers to “mostly love” and “mostly hate” Taobao and eBay China.

However, neither of these two e-commerce web sites is delivering experiences that satisfy the most important needs of Chinese online consumers. They are both hitting the wrong peaks, and neither allocates adequate resources to address the right peaks. There is still room for improvement. The e-commerce battle in mainland China has just begun, and it’s too early to name the winner. I would not be surprised if eBay China turns around—if it can hit the right peaks.

Once you have measured these sub-processes, you can start to manage and enhance your customers’ online experiences. Ensure that brand values are reflected at positive, and not at negative, peaks. Align strategies (brand, product, price) if needed and relocate resources to more relevant and important sub-processes. This measurement system helps managers deliver differentiated (branded) experiences, navigate the strategic direction and prioritize resource allocation.

As more and more businesses, like the airlines I patronize, move to the online channel, it’s more important that they think these through and get a good measure of the customer’s experience online.


  1. I was wondering the possibility of designing a differential online experience for an African market like Nigeria, where data is not properly kept and accesible. I would really appreciate it if I can be given an insight into this. Thank You.

  2. Tope

    It’s a small world, we’ve attendees from two different Nigeria companies attended our CEM Certificate Program last week.

    No matter which country you’re located, there are some common elements such as deciding your target customers, identifying their most critical needs and your brand values, before you’re able to design your own branded and effective online experience.

    As a starter, I’d recommend you to download the free experience-centric VOC research reports in our portal on online experience (we’ve also call center, in-store and B2B experience reports). Data should not be the concern as they will be generated after the X-VOC research.

    Let me know more specific if you’ve further questions.



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