The Use of Analytics in Higher Education

JISC ProjectYork St John University / Applied Web Analytics

January 2010

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Structure

• What is analytics?

• Customer journeys

• Three phases of analytical development

• Key concepts

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Definition of web analytics

“The process of collection, measurement and analysis of user activity on a website to

understand and help achieve the intended objective(s) of the website”

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JISC project - using analytics

“The process of collection, measurement and analysis of interactions between the university and its various audiences, to understand these

audiences and help achieve the intended objectives of the university”

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Possible ‘interactions’ with YSJ

Time

Life

tim

e V

alu

e

P/G Student

Careers Advice Centre User

Part-time student

U/G Student

Donor / Alumnus

Joint research grant

Sole grant provider

Employer, referrer

Speaker to business school

Supporter

Benefactor

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Stages

1. Data collection

2. Gaining insight and taking action

3. Embedding the approach

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Stage 1

• Data collection and measurement – Collecting these interactions into a single

database, to provide a single view of a contact– Collecting results on previous communications

with that contact• Revenue (“Tangible resources”)• Costs of communication• Response rates• Surplus / profits created

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Replacement of disparate databases

Faculty and Directorate databases

Contact management database

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Stage 2 – Getting insight and taking action

• Developing insight and taking action– Identifying patterns in the data– Developing hypotheses– Performing tests

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Getting Insight

InformationData Insight

Identifying patterns in the

data

Developing hypotheses

Performing tests

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A continuous process

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Stage 3 - Embedding the process

• Involve stakeholders• Make one person responsible for analytics• Focus on insight / ad-hoc queries, not

reporting • Have a positive attitude to testing and ‘failure’• Set goals for improvement• Focus on tangible outcomes • Start with a small win

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Key concepts

• Data driven decisions / statistical analysis• Events / interactions recorded in single database• Closed loop marketing – who did you interact with

and who and who did not respond• Past behaviour correlates with future actions• Segmentation – different messages to people who

are different in their behaviour• Lifetime value and retention rates• Return on Investment (revenue – costs / costs)

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Thank you

Dan Croxen-JohnApplied Web Analytics

dan@appliedwebanalytics.com0800 990 3580

Follow me on Twitter:Dan Croxen John or ApldWebAnalytix