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White Paper - The Problem With Price - Part 3 of 3

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Conjoint Analysis – Trade-Off Research

In the 1960s and 70s, academics were looking to understand how people made decisions. If you just asked people, they tended to say what was top-of-mind, or what they thought the interviewers wanted to hear and so what people said didn’t necessarily reflect what they actually did.

However, the academics noticed that almost all choices involve compromises and trade-offs as the ideal is rarely attainable (we might want a Rolex watch, but we typically have to compromise to something a little less expensive for example).

In their studies, the academics found that by looking at how people made selections between a limited number of products involving different trade-offs, they were able to accurately predict which choices would be made between previously untested products. Conjoint Analysis was born and is based on the understanding of how people make choices between products or services, so that businesses can design new products or services that better meet customers’ underlying needs.

To understand how conjoint analysis works, we need to be able to describe the products or services consistently in terms of attributes and levels in order to see what is being traded off.

An attribute is a general feature of a product or service – say size, colour, speed, delivery time. Each attribute is then made up of specific levels. So for the attribute colour, levels might be red, green, blue and so on.

For example, we might describe a mobile telephone in general terms using the attributes, weight, battery life and price. A specific mobile phone would be described just by levels say as 80 grams, 8 hour battery costing £150.

Conjoint analysis takes these attribute and level descriptions of product/services and uses them in interviews by asking people to make a number of choices between different products.

For instance would you choose phone A or phone B?

Phone A Weighs 200g has a battery life of 21 hours and costs £70

Phone B Weighs 120g has a battery life of 10 hours and costs £90

In practice you can see how difficult some of the choices can be. The thought process might be:

“Phone A is bulkier, but has the battery life and lower cost, but Phone B is smaller and neater yet more expensive and with lower battery life. Lighter weight is worth more than the loss of battery life, and it’s probably worth the extra £20, so I’d choose B in this instance.�

By asking for enough choices (and with good design to minimise the number of choices you need to ask), the researcher can work out numerically how valuable each of the levels is relative to the others around it – this value is known as the utility of the level.

The problem for business researchers until now has been the cost of carrying out conjoint analysis. In order to arrive at reliable results it is necessary to carry out at least 100 interviews and we feel more comfortable with 200 or more. These interviews have to be face to face so that respondents can view the concept cards and make their choices (in practice the choices are usually presented on a laptop computer screen). Think 200 face to face interviews scattered across Europe and you are thinking €300,000+ survey cost. For many companies this will break the market research budget. However, the same project carried out on line could be carried out for a fifth of the price. The conjoint on-line interview would use the telephone to recruit and qualify the respondent and collect base data while the conjoint choices are made by the respondent in a self-completion interview that is e-mailed back to the research company.

SIMALTO - Simulated Multi-Attribute Level Trade Off

Trade-off grids are an approach to collecting information from respondents that recognises that an individual customer cannot have everything. He or she has to make trade-offs to get the best product they can buy. The classic trade-off is between price and quality, but in practice when considering most purchases we make trade-offs between different features and service levels and even emotional risk.

A trade-off grid is a method of getting underneath a customer’s general wish list to really understand what they must have and what are the nice-to-haves. This means we can see what is really valuable to a customer and with a few further questions, we can also understand what their priorities would be for trading up or improving the current system.

The factors that a customer may be interested in (also called attributes) are laid out on a grid showing different levels (see figure 8 below) - low levels of the attribute at the left rising to higher levels towards the right hand side of the grid. With the grid, we can then ask the respondent to complete a number of tasks. Typically the first task is to find out where he or she would want a “first class supplier� to perform – this sets the ideal standard. Next we can ask where your company is currently performing. We can then ask them to do a number of different things – for instance to prioritise improvements in your company’s performance one square at a time, or to ask questions such as if you had more of x, what would you be prepared to sacrifice from y.

Each level of attribute has a number which is used by the respondent in a “points spend� question where they are asked to show how they would spend 30 points (by way of example) to improve the offer they receive at present. The way that the points are spent indicates the trade-off that each respondent is prepared to make to move from one level of delivery that they receive at the present to one that could be offered (but at a higher price). This trade-off enables us to see specifically what a supplier could do to win more business and at what price. The outcome is thus a detailed understanding of where the customer would like improvements and what those improvements should be.

Figure 8 Simalto Grid

SIMALTO grids have the advantage over conjoint in being easier to apply in business to business situations. For example, we often have to test many attributes in business to business customer value propositions and this creates a complex task for the development of the conjoint choices. Respondents get tired in conjoint interviews which require them to make dozens and dozens of choices between attributes or to consider concepts, which, after the 30th one has been shown, begin to look the same. Also, the output from a SIMALTO survey makes complete sense to a manager in business who wants to know what proposition should I go for and how much should I charge. They are saved from the black box mystery of the conjoint utility values.

The Guiding Hand Of The Agency

With product life cycles shrinking, customers becoming more sophisticated and demanding, and tougher local and even global competitors emerging in most markets, markets are shifting at faster rates than ever. The payoff for getting your company’s pricing strategy right has never been more important.

Pricing research usually concentrates on customers’ sensitivity to pricing. This price sensitivity is driven by the nature of the market, the competitive environment, the target within that market, the differentiation level of the product or service, and the value of the brand.

The responsibility of any research agency is that of the being a realist. The subject of pricing research is an emotionally charged area and who can really say what a customer will do until it comes to them actually putting their hand in their pocket. We need therefore to have the confidence to say that a specific price is the one that respondents have stated they would buy at – but we know that it is all hypothetical and that sometimes a ballpark is needed to enable a test market experience so to gather buying patterns on how buyers/users will react.

Pricing research can be used to obtain an understanding of the pricing levels for specific product service offerings. It can also be used to attain an understanding of the additional services customers subscribe to and what additional price they would pay, to identify the elasticity of demand for a product or service and to establish where customers would welcome an improvement in either products or services offered and what premium they would pay for those improvements.

To view the previous parts of this white paper click the links below:

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