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Revenue and Investment Optimisation

Taking the guesswork out of tuition fee pricing decisions

Adjusting tuition fees can have an impact that's immediate and far-reaching. 

But setting fees isn't easy, and more often than not, there's an element of guesswork. 

Edified’s Revenue and investment optimisation (RIO) helps universities optimise revenue and make more informed investment decisions by designing programs and setting course fees which are based on student preferences and demand.

Using choice modelling and microeconomics, inspired by Nobel Prize winning economist Daniel McFadden, we obtain insights into student (and parent) decision making to determine revenue optimising tuition fees. 

This reduces risk, improves pricing accuracy, helps universities achieve financial sustainability and make wise investment decisions.

Edified’s Revenue and investment optimisation is delivered in partnership with QS in the UK

Deliverables

Increased revenue
Increased demand for targeted programs
An improved market position relative to competitors
Scholarship optimisation by market
Price-setting policy consensus
The market's propensity to pay for program attributes

How do we do it

Put simply, we simulate the marketplace to accurately forecast demand.

Universities commonly make pricing decisions on an ad hoc basis. These are often based on adjustment to historical prices, costs (e.g. cost-plus pricing), or competitors’ prices (e.g. market-based pricing).  

All these approaches fail to consider the single most important factor in setting prices: student demand. As such, they're less likely to achieve their revenue potential.

By using these compromised approaches to pricing, universities can unknowingly be 'leaving money on the table'. Sometimes, a lot of money.  This can result in unnecessary stress on university budgets and lead to suboptimal decision-making.

Our solution helps universities set prices based on student preferences and demand.

What problems we solve

What tuition fees and prices should we set?

Establish revenue-optimising tuition fees for a set of courses or fields of study

Avoid ‘leaving money on the table’

What types of scholarships should we offer?

Identify the scholarship program features which optimise revenue

Avoid giving away too much in unnecessary or poorly targeted discounts

What product and brand features should we build into our offering?

Build in course inclusions and university features which students value most

Know how much incremental revenue would be generated by an increase in ranking or adding program features

What combination of promotional messages should we use?

Optimise and target marketing messaging for different markets according to what students value most

What investment projects should we prioritise?

Rank major facilities and infrastructure investment decisions by value to students

Know how much incremental revenue would be generated by investing in specific infrastructure or services

Key steps in the process

1

Choice experiments are used to generate the microdata required for producing the data i.e. demand and revenue functions, price elasticities, and willingness-to-pay estimates.

2

Specialised econometric models are fit to the data. The models are then used as input into the creation of a pricing wizard. The wizard is used to explore new policy settings for pricing and related decisions, and to forecast the impact of policy changes before they are implemented.

3

The wizard is data-driven, evidence-based and is a powerful tool that’s used to greatly enhance pricing decisions.

4

More accurate forecasting leads to increases in revenue and more informed investment decisions.

Example of willingness-to pay-estimates that can be established from choice modelling

The willingness-to-pay estimates offer strategic insight into the configuration or design of program attributes and help shape the future investment decisions of the university.

Example of possible output from the pricing wizard 

The pricing wizard is a decision support system and a visualisation of the data and econometric model(s). The tool can be used to solve for the revenue-optimising tuition fees for the university’s programs.

It can further be used to solve for the optimal configuration of program attributes.The wizard is provided as a sophisticated excel sheet that allows complex ‘what if’ analyses.

The image here is a visual representation of the kind of information that could be extracted.

Case studies

Strategic Transformation for a Group of Eight university in Australia

Project sponsors

Deputy Vice-Chancellor Academic, Chief Financial Officer, Chief Marketing Officer, Chief Marketing Officer

Objectives

Optimise revenue for price, redesign scholarship programs, reposition university in the market.

Scope

Broad fields of study of the university, existing and prospective students in key markets.

Recommendations

Systematically reprice the programs, significantly alter the scholarship programs of the university, substantially refine the marketing and communication messages to reposition the university.

Results

Identified pathways to increasing revenue from international student fee income by 30 percent (from $250m to $325m) and to reconfigure scholarship program.

Product Design for a top tier university in Aotearoa New Zealand

Project sponsors

Director International, Director Online Programs

Objectives

Forecast demand for online, on-campus, and hybrid course offerings, establish priority fields of study for new program development, establishing revenue-optimising prices for online offerings (relative to on-campus and hybrid offerings).

Scope

Broad fields of study of the university, prospective students in key markets.

Recommendations

Systematically reprice online offerings based on revenue optimising prices, specify priority fields of study for new program development, set directions for market development strategy.

Results

Credible pathways to generating significant sources of growth in student load and revenue were identified and are being implemented as part of a new internationalisation strategy.

Our Revenue and Investment Optimisation team

If you have questions or you would like to explore the potential for our pricing and revenue optimisation to aid your organisation, please get in touch.

Jason Newman
Chief Commercial Officer

jason@qs.com

Sharyn Martin
Senior Partner

Sharyn has more than 25 years of experience at a senior level in international and domestic university strategy, marketing and recruitment in government, in the private sector, and as a consultant and a Senior Partner at Edified.

Dr Len Coote
Pricing Expert

Len advises in the areas of demand and revenue management using the concepts and methods of microeconomics and micro-econometrics. He has advised a wide range of organisations from global corporates, private equity firms, professional service firms and universities.

Dr Edward Wei
Pricing Expert

Edward is an experienced marketing and management insights specialist and market research professional with advanced quantitative analytics and choice modelling skills. He has over 25 years of experience in various consultancy and research roles.

Ben Martin
Associate

Ben has a finance background and is an education industry specialist. He is an accomplished strategic planner and has a proven history of developing and implementing marketing and customer experience initiatives to build brands and drive customer acquisition.