{"id":63438,"date":"2021-05-04T15:57:44","date_gmt":"2021-05-04T13:57:44","guid":{"rendered":"https:\/\/visionarymarketing.com\/?post_type=glossary&p=63438"},"modified":"2023-05-26T07:58:14","modified_gmt":"2023-05-26T05:58:14","slug":"survey-biases","status":"publish","type":"glossary","link":"https:\/\/visionarymarketing.com\/en\/glossary\/survey-biases\/","title":{"rendered":"Survey biases"},"content":{"rendered":"

Let\u2019s look in detail at survey biases in market research<\/a>. <\/span><\/em>Survey biases are systematic errors introduced into sampling or testing by selecting or encouraging one outcome or answer over others.<\/span><\/em> While B2C research is straightforward when addressing people on known topics, B2B research is more complex. The real difficulty is to measure perceptions on terms that are not always well understood.\u00a0<\/span><\/em><\/p>\n

Survey Biases in Market Research<\/h1>\n
\"B2B
B2B market research: questioning biases<\/figcaption><\/figure>\n

Since online surveys (or CAWI for Computer-Aided Web Interviewing) have democratised access to marketing research, almost anyone can go into the field and design their own survey. <\/p>\n

When designing a survey, however, it is important to avoid a number of errors known as \u2018survey bias\u2019, which have existed since long before the Internet.<\/p>\n

Main Survey Biases<\/h2>\n

One of the main<\/strong> survey biases, if not the main one, is to ask profile questions (age, gender, location\u2026) at the beginning of the survey when they are really meant to be asked at the end. These questions can in fact dissuade respondents from answering as they can be considered to be too intrusive when posed at the beginning of the survey. The second<\/strong> bias is to administer a survey without having first run it through a small group of respondents.<\/p>\n

It is then necessary to avoid double-barreled questions, that is, questions in which two questions are asked. For example, \u2018Do you think Martinique is a nice and cheap destination?\u2019 A person may think that Martinique is a nice destination but not cheap, or vice versa\u2026<\/p>\n

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Another Bias<\/em><\/strong><\/h4>\n

Another bias <\/strong>is often found in questions that already include the answer or at least the opinion of the person who wrote the question (or someone else): \u2018Would you buy this fridge despite its design flaws?\u2019 Hard to answer objectively\u2026<\/p>\n

One should also be careful of halo<\/strong> effects: \u2018Do you also think, like the President of the Republic, that taxes are too low?\u2019 Referring to a known person undermines the neutrality of the question.<\/p>\n

Designers of surveys should avoid the use of jargon<\/strong>: \u2018Would you use this DBMS in your professional life?” Terms that are too generic are recommended to be banned. For example \u2018Would you use dematerialisation to process this task?\u2019 It is necessary to specify what is meant by dematerialisation: software, a specific procedure\u2026<\/p>\n

When using a list of responses, the list should be as exhaustive as possible or include an \u2018other: please specify\u2019 or an \u2018I don\u2019t know\u2019 choice. Example:<\/p>\n

What is your favourite dessert?<\/em><\/p>\n