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The OCSE model is another useful model for assessing the customer service experi- ence and could be adapted as a checklist for business.

Path to purchase Borrowed from computing terms, path data contains information about a user’s search behaviour, interests and visits. In marketing parlance, the ‘path to purchase’ concept is similar to a non-linear customer journey; the difference is trying to attribute the elements or touch- points which have had an impact on the journey. Was it the email? The pop-up offer on the website? Perhaps dark social (see Key Term) with a message from a friend? If the specific steps can be correctly attributed this means that greater investment can be made where needed.

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Google, as a major seller of online advertising, was an early pioneer of sharing path to purchase data and provides free access to aggregate data, to inform marketers about latest trends and insights.




Online Customer Service Experience (OCSE)

Psychological Factors Functionality

Inter- actions

with service provider

Inter- actions

with other customers

Trust expectations

that a website will act

competently, openly and


Value for

money price level, low price


Context familiarity

re�ects the website’s

capability to make

customers feel


Usability enables online

customers to feel

comfortable using the website

Communi- cation

reduces the risks

associated with


Product presence

is the assessment of

products in virtual

environments to stimulate purchase intentions

Inter- activity

describes the

dialogue between

the website and its users

Social presence

re�ects the customer’s

virtual interaction with other shoppers

Figure 2.4 Online customer service experience (OCSE) conceptual model

Source: Klaus, 2013, p. 447

Digital Tool Google Path to Purchase Google shares its aggregate data to inform marketers about shopping insights, trends and bench- marks. To further explore shopping insights, go to:

• thinkwithgoogle.com/tools

Other academic researchers, Alice Li and P.K. Kannan, created a conceptual frame- work for the path to purchase which combined the customer journey with stages initiated by the firm to influence and direct the purchase (Li and Kannan, 2013). They reviewed the channels connected to online purchases of high-involvement goods such as consumer durables and travel services.

They used a linear model from the channels considered, which were identified through search, so in the example of trying to find a flight, the consumer might search online for flights and they may visit a firm’s own website, such as American Airlines or British Airways, or they may use a flight search engine such as SkyScanner. If the consumer goes backwards and forwards between the different sites, modifying their search terms, to gain the best price, they are leaving a trail of cookies (see Key Term)




for the firms to add them to their online advertising campaigns. Ever noticed that ad following you around when you’ve just looked at a website? It’s all based on your online behaviour and this is the area that Li and Kannan explored further as ‘firm- initiated’ behaviour. In some cases this may have been display ads, like the follow-me marketing. But if a user responded to another channel, such as email, the firm may have subsequently sent a nudge email to encourage the web visitor to return to the website and complete their purchase.

Li and Kannan discuss the concept of ‘spillover effects’, which they explained as the ‘impact of prior visits through a given channel’ (Li and Kannan, 2013, p. 43). As an example, I received an email that said ‘we noticed you left some things in your shop- ping basket’ and I clicked on the email, to return to the website and complete the purchase. The email has an impact on the final step in the path to purchase.

KEY TERM COOKIE A web cookie is a small piece of data that is stored temporarily or for a period of time on your device when you have visited a website.

There are two kinds of cookie: (a) session cookies, which are temporary whilst you are browsing and do not store your data, and (b) persistent cookies, which remember who you are. Persistent cookies remember usernames and passwords, automatically login to websites and recall what is in your shopping basket.

Service blueprinting Understanding customer journeys means understanding the process customers take from identifying a need or desire for an item, to the conclusion and purchase. This considers a single track, the customer view. Service blueprinting is another form of process modelling but considers all the actors involved: the customers, staff, delivery – any people or processes that contribute to the overall customer action.

In ‘Service Blueprinting: A Practical Technique for Service Innovation’ Mary Jo Bitner (the professor who increased the 4Ps to the 7Ps) and her colleagues identified five specific components for a service blueprint (Bitner et al., 2008), which are shown in Table 2.5 with examples.

Table 2.5 Service blueprinting with examples

Service blueprint components Details Examples

1. Physical evidence Tangible elements with which customers come into contact

Website, social media, email

2. Customer actions All actions taken by customers as part of the process

See adverts, read social media posts, order placing




Service blueprint components Details Examples

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