Info

Key outcomes Q4

Q4/Q4R

Performance drivers

Awareness efficiency

Q1/Qo

Attraction efficiency

Q2/Q1

Engagement efficiency

Q3/Q2

Conversion efficiency

Q4/Q3

Figure 2.13 A model of the Internet marketing conversion process

Figure 2.14 shows an example of how measuring conversion rates can be used to improve web marketing. Numbers are across a fixed time period of one month. If for a particular market there is a potential audience (market) of 250 000 (Q1), then if online and offline promotion techniques (Chapter 8) achieve 100 000 visitors to the site (Q2), marketers have achieved an impressive conversion rate of 50%. The online marketers are then looking to convert these visitors to action. Before this is achieved, the visitors must be engaged. Data from log files show that many visitors leave when they first visit the home page of a site if they do not find the site acceptable or they are not happy with the experience. The number of visitors engaged (Q3) is 50 000, which is half of all visitors. For the visitors that are engaged, the next step is to convert them to action. This is achieved for 500 visitors (Q 4), giving a conversion rate (Q 4/Q 3) of 1%. If what is calculated (as is most common) is (Q4/Q2), this gives a conversion rate of 0.5%.

Target audience (Q1) Attract (Q2)

Attraction efficiency (Q2/Q1)

Active visitors (Q3) = 50 0

Conversion efficiency (Q4/Q3) = 1%

Site visitors (Q2) Engage (Q3)

Engagement efficiency (Q3/Q2)

Target audience (Q1) Attract (Q2)

Attraction efficiency (Q2/Q1)

Active visitors (Q3) = 50 0

Conversion efficiency (Q4/Q3) = 1%

Site visitors (Q2) Engage (Q3)

Engagement efficiency (Q3/Q2)

= 200 000 surfers = 100 000 site visitors = 50%

= 50 000 active visitors = 50%

= 500 take action

Figure 2.14 An example of a conversion model

In this example, the organisation seems highly efficient in attracting visitors to the site, but less efficient at converting them to action - future marketing improvements could be directed at improving this. Some organisations will measure different conversion rates for different segments and for different goals such as generating new leads, responding to a sales promotion or signing up for a seminar. Analysis by Agrawal et al. (2001) suggests that the strongest sites may have conversion rates from visit to sale for e-commerce sites as high as 12%, as against 2.5% for average sites and 0.4% for poorly performing ones. Clearly, measurement of the conversion rate and taking actions to improve this rate are key e-marketing activities. The marketing communications techniques used to increase these conversion rates are considered further in Chapters 7 and 8.

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