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7. The Customer Experience<br />

proportion of which are made with the 9.46 million Oyster cards that are <strong>in</strong> regular<br />

use) are captured by TfL’s ticket<strong>in</strong>g and other automated systems, provid<strong>in</strong>g a huge<br />

amount of <strong>in</strong>formation – ‘big data’ – about how people travel around the Capital.<br />

TfL is actively analys<strong>in</strong>g and improv<strong>in</strong>g its capability to apply big data to provide<br />

better transport: we can measure and anticipate the impact of changes to our<br />

services, as well as the effects of alterations to <strong>London</strong>’s landscape such as new<br />

hous<strong>in</strong>g, offices and shopp<strong>in</strong>g developments. Of course, to protect customers’<br />

private <strong>in</strong>formation, TfL removes all personal details from the data that we analyse:<br />

but while the <strong>in</strong>formation used is anonymised, the benefits are <strong>in</strong>creas<strong>in</strong>gly<br />

personalised.<br />

As part of our work to manage ris<strong>in</strong>g travel demand, we are us<strong>in</strong>g big data to<br />

develop programmes that encourage customers to explore alternative travel<br />

options. This is particularly useful dur<strong>in</strong>g peak times when the transport system is<br />

close to capacity. With the <strong>in</strong>formation our customers provide, their needs can be<br />

‘segmented’. This means that we can email them with travel <strong>in</strong>formation updates<br />

that match their travel patterns and typical choice of transport service. TfL is also<br />

us<strong>in</strong>g big data to send automatic refunds to customers when there has been a<br />

material delay to their journey.<br />

7.8 Customer perception and satisfaction of the wider transport<br />

experience<br />

Previous <strong>Travel</strong> <strong>in</strong> <strong>London</strong> reports have detailed a wide range of improvements to<br />

aspects of the customer experience, and the overall impact of these on selected<br />

customer perception/satisfaction <strong>in</strong>dicators related to the wider transport<br />

environment <strong>in</strong> <strong>London</strong> that have been tracked as part of the formal MTS strategic<br />

outcome <strong>in</strong>dicator set.<br />

Results are presented <strong>in</strong> terms of mean scores out of 100 (these are not percentage<br />

scores), based on a response rank<strong>in</strong>g system from zero (lowest satisfaction) to 10<br />

(highest satisfaction). TfL <strong>in</strong>terprets these scores <strong>in</strong> a semi-subjective way, based on<br />

experience (this albeit open to different <strong>in</strong>terpretation by different people). Figure<br />

7.10 shows the available time series for these <strong>in</strong>dicators – note that not all<br />

<strong>in</strong>dicators are available on a consistent basis for the entire review period, and that<br />

TfL’s subjective assessment of the scores is represented by the bar to the right of<br />

the graphic.<br />

Perception of journey experience<br />

This <strong>in</strong>dicator looks at how <strong>London</strong> residents perceive their journeys overall. It<br />

complements mode-specific scores reported above and recognises the complex<br />

<strong>in</strong>teraction between modes that is typical of travel <strong>in</strong> <strong>London</strong>.<br />

The average satisfaction rat<strong>in</strong>g for travel <strong>in</strong> the Capital among <strong>London</strong>ers <strong>in</strong> 2014<br />

was 70 out of 100. This was the same as <strong>in</strong> 2013, but reflect<strong>in</strong>g a substantial uplift<br />

s<strong>in</strong>ce the earliest measure <strong>in</strong> 2009, due to the range of improvements described<br />

above <strong>in</strong> section 7.5.<br />

135 <strong>Travel</strong> <strong>in</strong> <strong>London</strong>, Report 8

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