Deciding which product to buy is rarely easy, particularly when offered a wide range of choices. While we would ideally like the best of everything for the lowest price, we inevitably have to ask "What am I willing to give up?" and "How much am I prepared to pay?". Since we can't have everything, these types of trade-offs are unavoidable.
Businesses must also make trade-off decisions when offering products to a market, which can affect product development, sales and service delivery. Making the right decisions means meeting customers' needs economically - the customer can buy what they want and the company profits from the sale. Determining the optimal balance of trade-offs is where statistics plays an important role.
Trade-off analysis is known by many names, for example, conjoint analysis, choice modelling and contingent valuation. What these techniques have in common is analysing decision-making where a choice is presented. Trade-off analysis is a collection of standard statistical techniques that provide objective insight into consumer preferences using a quantifiable and repeatable approach. There is a perception that trade-off research is an expensive and difficult exercise but, with the right design, it is surprisingly efficient and flexible.
Trade-off analysis can work in many ways, including allocating a "worth" to every feature being researched on a common scale to determine the combination of features with the greatest value. This allows a dollar value to be assigned to abstract qualities such as colour and shape, thereby letting companies know, for example, how much more customers value (and will pay for) red products compared to blue products.
By understanding the statistics behind trade-off studies, statisticians can design surveys that are shorter and more interesting for the respondent and are also good value to the client. To really benefit from trade-off research, the analysis must be taken into account before the design of the survey, making the statistician's role more important than ever.
The applications of trade-off analysis extend to informed policy planning, setting of fees and charges, understanding consumer behaviour, and identifying values and priorities.
Data Analysis Australia has the expertise to design a balanced questionnaire, analyse the data in context of the research questions and interpret the results and has demonstrated this expertise in a range of applications.
Recreational fishers were presented with a scenario of a way to pay for the next fish they catch using realistic methods such as fishing licences or fish tags with the money raised going to improving fish stocks. Fishers placed value on the next fish by choosing to accept the priced scenario or stay with things as they are.
Water utility customers were presented with various billing options and payment methods were ranked in order of preference. They were trading off frequency of bills against means of payment and discounts.
Trade-off techniques can be used for any research where there is a need to investigate consumer behaviour, preferences and decision-making. Data Analysis Australia can assist in designing the right study and providing meaningful results.
For further information, please contact Data Analysis Australia at daa(at)daa.com.au or phone 08 9468 2533.