SIMALTO

Marketers need to understand whether an offer meets customer expectations, which shortcomings matter and how much buyers would pay for improvement. Conjoint analysis can answer such questions, but it normally requires specialist design and analysis software and a sufficiently large sample—at least 100 interviews in the account presented here. SIMALTO offers another form of trade-off research. Its name abbreviates simultaneous multi-attribute level trade-off: respondents consider several attributes together, rank their importance and make choices among different performance levels. For example, a study of sales contact might distinguish among the following service levels.

When to use it

• Use SIMALTO to identify how much value customers place on possible product or service improvements.
• Choose an online or otherwise visual format that lets respondents see all attributes and levels together while ranking and allocating their priorities.

Origins

John Green developed SIMALTO after beginning his market-research career at Xerox. He presented the method at a research conference in Oslo in 1977. It became particularly useful to business-to-business researchers working with small, specialised populations, and Green later advised organisations on its application.

What it is

• no visit from a salesperson;

• one sales visit each year;

• one sales visit each quarter;

• one sales visit each month.

Researchers tailor the levels to the decision being studied. Each respondent identifies the service currently received and the level desired, then spends a limited pool of points across potential improvements. That forced allocation reveals the multi-level trade-offs at the heart of SIMALTO.

Consider a grid designed for a power-tool manufacturer. Its rows contain purchase attributes and its columns describe progressively higher performance. The example figure displays five of the 20 attributes used in the full study. Respondents mark current and preferred performance for every row. A notional value shown in parentheses accompanies each level. Near the end of the interview, participants receive a budget of 50 points and allocate it among the improvements they want. Because the budget is constrained, they must reveal which changes matter most rather than endorsing everything.

SIMALTO can operate with far fewer respondents than a conventional conjoint study. At the limit, one person can complete the grid and discuss the gap between the present and desired offer during an in-depth interview. In practice, researchers recruit a cross-section of relevant customers and group participants who share similar priorities, which can reveal useful segments. The points allocated to unmet needs provide a utility signal; with appropriate commercial assumptions, that signal can also inform a view of willingness to pay and pricing.

Developments of the model

After 40 years of use, SIMALTO remains adaptable across products and services but is less widely adopted than conjoint analysis. A grid can cover as many as 20 attributes, compared with the customary conjoint limit of seven described in this account. Its plain-language performance levels are usually intelligible to both respondents and research sponsors, and the method remains viable with small samples.

Those advantages do not remove the need for judgement. Conjoint analysis can appear more scientific because its calculations are less visible, whereas SIMALTO exposes the design choices. Building a strong grid is therefore the most demanding stage: researchers must select the attributes, define meaningful increments and express every level in language customers understand. Interpreting and communicating the resulting patterns also requires experienced research practitioners.

How to use it

A power-tool manufacturer used SIMALTO to prioritise features for its next product generation. Because respondents needed to compare every attribute, mark present and desired levels and revisit their choices while allocating points, the questionnaire was delivered online rather than by telephone.

The target population consisted of hands-on tradespeople working on building sites, a group that was difficult to recruit for an online study and required a substantial incentive. Researchers obtained and analysed 100 completed questionnaires. Physical weight emerged as an important development priority because a lighter tool could improve productivity. Longer battery life produced the strongest appeal: users needed a tool capable of lasting through the working day, since failure on site imposed material cost as well as inconvenience. Participants indicated that they would pay a high price for eight hours of battery life. The study therefore gave the manufacturer a clear, customer-grounded basis for directing research and development beyond the attributes illustrated in the grid.

Some things to think about

• Consider SIMALTO when a business-to-business population is too small for a credible conjoint survey. It can expose unmet needs and show which of them customers value most.

• The same structure can help an organisation learn which improvements employees want in their working practices.

• Build the grid from the respondent’s perspective. Describe each level using the language customers themselves use for the offer.

Top practical tip

Reserve the limited points budget for the end of the exercise so respondents must distinguish desirable improvements from the few changes they value most.

Top pitfall

Do not rush the grid design. Ambiguous attributes or unrealistic performance levels will make the resulting trade-offs difficult to interpret, regardless of sample quality.

Further reading

• Green, J.L. (nineteen seventy-seven). “SIMALTO.” ESOMAR Congress: Research for Decision Making.
• Green, J.L., Goldsmith, E. and Parish, C. (nineteen ninety-one). “The SIMALTO Approach to Optimal Product Specification.” American Marketing Association Advanced Research Techniques Conference.