The Need for a Formal Decision Framework Seldom do people realise that business, just like life, is merely a series of decisions.

And businesses have a growing need for the necessary information concerning the demand for existing and new products, shutting down a business unit, customer perceptions, brand awareness and positioning, price elasticity, adverting recall and effectiveness, market trends, market forecasts, and competitor activities among many others.

While there are many ways to arrive at an action plan such as relying on gut feelings, listening to the opinions of close networks or using what is in the media, it is a necessity for decision-makers to have a structured and transparent framework to base their decisions on. Decision-makers use market research to support their decision process, making it easier, more reliable and more objective.

by AJ DABYDIN

MARKET RESEARCH:HOW TO GET THE RIGHT DATATO MAKE THE RIGHT DECISIONS

THE SINGAPORE MARKETER 05

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COVER STORY

Market Research: an Investment or a CostIt is always a gamble when you spend money aiming to get something from it. You can spend half of your marketing budget on advertising without any guarantee that it will boost your sales. There are risks but there are also rewards. You can only hope that you make the right decisions.

Similarly, spending on market research can be perceived as a cost rather than a valuable investment that can open up new markets, foster new products, enhance customer satisfaction, build loyalty, beat the competition, increase market share, prepare for the future and fortify a company’s overall position and secure its future. It is a cost when your research fails to provide the insights you need to design strategies that can help you meet your business goals. The next thing you know is a sit-down with senior management to explain failure rather than growth plans. However, if by the end of your research initiative you get the answers to your questions and a detailed understanding of what you should do, then the money and time spent on research would be a pay-off.

The Need for Market IntelligenceThe need for market intelligence is driven by the need to find the optimum way to function or carry on business. The aim is to gain foreknowledge of the market and make strategic decisions to take advantage of the situation. Market dynamics change every day much like stock prices. It is getting harder to compete and sell and even harder to create loyalty.

Winning firms are organisations that most successfully master the business issues critical to their performance, and develop the most precise understanding of the creation of value for their customers. Organisations prosper by improving their products, their marketing, their positioning, their presence, their leadership, their structure and competitive intelligence is at the core of the objective of improving competitive advantage.

Getting the Right DataThe key to getting the right data depends on five key factors: questionnaire design, the sample, the sample size, the methodology, and the quality of data collection. The very first step in setting data collection into motion is to design the questionnaire or script. It is very important that the team designing the questionnaire to be forward-looking and capture the research objectives. The types of questions used – rating, ranking or agree / disagree, etc. – is critical in determining the types of analysis that can be performed and how the data would be interpreted. The questionnaire must also be practical. No one would want to answer a survey if it’s too long or too complex to understand. A pilot test is usually conducted to iron out any impracticalities or biases before the actual survey is launched.

The sample is the people or group of people that you have targeted to respond to the survey. If you want to launch a breakthrough

new woman shampoo, you wouldn’t be surveying men and asking about their hair problems, would you? Your sample must be relevant and consists of people that you have earmarked as users or potential users of your products.

The sample size is the number of people that you want to interview. It must be large enough for the data obtained to make any sense. The key here is to be representative. You can’t interview 300 people about the state of courtesy in Singapore and take the findings as being representative of the whole nation. In sampled research, to be representative at a margin of error of 5, we must survey 385 people. For a lower margin of error, a sample size of 1,017 is required.

The research methodology is the mean by which data is collected. Broadly, methodologies are categorised between claimed-behaviour methodologies such as surveys, interviews and focus groups that are based on the respondents’ ability to recall and explain their behaviour. Actual behaviour methodologies such as observations and mystery shopping are those where information is gained directly through observing the behaviours of interest. The use of either methodology depends on the research objectives. If you seek to obtain information about, say, people littering behaviour, observations would be most practical and effective. If you want to understand a shopper’s awareness of a particular brand, a survey would do.

Effective data collection is also reliant on the sampling methods used to collect data. There are sampling methods that can be used to structure data collection: simple random sampling, systematic sampling, quota sampling, convenience sampling, snowball sampling, stratified sampling, kish grid sampling, etc. The method that you choose has to ensure that the data you collect will not be biased or skewed towards a particular group which will ultimately affect the survey results. Once, the sampling methods have been agreed, the user needs to find the best mode to collect data whether it will be online, through telephone, face-to-face, through observations or a mixed mode tailored to the need of the respondents.

The fieldwork team that conducts the survey must be trained and experienced surveyors. Too often, research agencies hire students and retirees with no or very little training and experience because they are cheap. Just walk around Raffles Place and Orchard Road and you will see a bunch of kids running up to you to complete a survey. The team that carries out the survey not only must abide to the fieldwork plan but also interact with the respondent and administer the survey in a professional and ethical manner. They have to see themselves as an extension of the client brand.

Finally, the data collected must be validated before it is sent for processing and analysis. Some questionnaires will contain missing data and even mistakes by the surveyors for not ticking

AJ Dabydin is the Managing Director of Market Research Agency BDM Intelligence (www.bdm-intelligence.com).

AJ will be speaking on “I Am the Media” at the Marketing Institute of Singapore’s Marketing Guru Talk on 2 July 2009. Please call 6327 7592 or email membership@mis.org.sg for more information.

COVER STORY

the boxes properly. In such cases, the fieldwork needs to call back and request for the missing answers. In some research agencies, the practice is to have 10% of all responses collected checked. If more than 10% of these questionnaires have missing values and errors, all the questionnaires are checked. If there are too many errors in the questionnaires, they would be discarded. When the validated data is sent for processing, another level of check is to run statistical checks such as outlier tests, box plots and syntax to find any logical or data entry mistakes. Once these steps are undertaken, you are confident that the data analysis would be based on good data.

Making Informed DecisionsData comes to life and starts talking during analysis. To make effective decisions, the decision-maker must have a 3-dimensional view in interpreting the data by finding correlations and churning out the relevant statistical analysis. Many users tend to look at percentages, that is, how many people said this, how many would do that, etc. but it can be more revealing to look at statistics such as mean, median, mode, and run probabilities, cross tabulations and regressions. Other statistical techniques such as biplots and discriminant analysis can be very powerful ways to understand customers’ perceptions and preferences.

Besides the actual survey results, current secondary data from the media or other information archives can be a valuable add-on to data interpretation. The survey results may synchronise with trends, rebuff previous findings or reveal new patterns never identified before. The key is to always try to look at the survey results in all the possible angles to spot hidden evidence. With businesses moving faster than ever, it is essential that decision-makers get quality data in the shortest amount of time to make intelligent choices.