Quantitative Observation Definition
Quantitative observation is an objective collection of data which is primarily focused on numbers and values – it suggests “associated to, of or depicted in terms of a quantity”. Results of quantitative observation are derived using statistical and numerical analysis methods. It implies observation of any entity that can be associated with a numeric value such as age, shape, weight, volume, scale etc.
This observation technique is conducted on a sample which best represents the target market. It is important to have a larger sample size so that the observations can be made considering most of the diversities that exist in a population. By considering a large population, the observation results are most likely to have higher credibility. Once a market researcher collects data from the sample, the process of analysis begins and observed results are attained.
The University of South Alabama has termed Quantitative Observation as “Standardized Observation” and it is mostly used in scientific research as it produces statistically observed information. Quantitative observation is usually conducted by sending out surveys, questionnaires or polls.
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Quantitative Observation Characteristics
 Accuracy: Under quantitative observation, data can be measured (quantified) and so, it produces accurate results in comparison to other methods such as qualitative observation which produce results that can’t be quantified. For example, the boiling temperature of water at sea level is 100°C is a quantitative observation.
 Constant Results: Results of this observation method are constant – the boiling point of water at sea level will be 100°C and will not change with other variables remaining constant.
 Sample Creation: A sample should be formed for quantitative observation and the size of this sample should be considerably large for researchers to generalize the observation to the entire population.
 Scientific Research: This method measures and “quantifies” multiple aspects mainly for scientific research.
 Biasfree Results: As the results are quantified, the observations derived from those are free from bias but have a margin of error involved and is usually based on a hypothesis.
 Improve reliability of results: For a marketer to have a quantity linked to his/her qualitative observation, he/she needs to conduct quantitative observation as well. A quantitative result can be derived for the qualitative observation to increase reliability on the results.
 Conduct statistical analysis: Quantitative observation verifies details by conducting statistical analysis of a statement.
 Numerical results: All the results of quantitative observation are numerical.
 Use various instruments: Instruments such as rulers, thermometers, balances etc. are used for quantitative observation.
 Methods to process and analyze data: There are various methods and to process and analyze collected information. Rich quantitative observational data can be processed using codes/scores, for example, evaluation scales, checklists, tables etc. can be created to analyze collected data.
 Create a plan: Based on the purpose of observation, a quantitative observation plan is created. On this basis of this plan, settings are changed and method of conducting this observation is decided.
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Quantitative Observation Examples
There are several situations under which quantitative observation can be implemented. Here are some examples of quantitative observation:

 If a market researcher intends to understand his/her brand shareability, they can ask a Net Promoter Score question: “Considering your complete experience with our company, how likely would you be to recommend us to a friend or colleague? ” with a scale from 010. 0 indicates highly unlikely and 10 indicates highly likely. Respondents will be divided into three categories: Promoters (910), Passives (78) and Detractors. Net Promoter Score can be calculated using formula = %Promoters – %Detractors * 100The result will be a quantitative observation, i.e. a numerical value which will depict customer loyalty and brand shareability.
 Another example of quantitative observation is a customer satisfaction survey. “How satisfied are you with our products/services?”. This question can be asked on a four, five, six or sevenpoint Likert Scale– where 1 shows strongly disagree, 2 shows disagree, 3 means neutral, 4 means agree and 5 means strongly agree. Four and sixpoint scale will not have the neutral point and the sevenpoint Likert scale will have slightly agree/disagree. Here opinions are directly converted into numbers by connecting them to different numbers, making analysis a simple task for marketers.
Some other Quantitative Observation examples are –

 30 survey respondents in the age group of 3040 were of the opinion that the age of Donald Trump is 72.
 This auditorium can accommodate 1000 people at once.
 Only 25% of people in the US are considered to be Native Americans.
 There are 15 marketing campaigns scheduled for the last 3 months of the year in an effort to increase signups from the website by 30%.
 The automobile company launched 5 new car models in the last year and observed a 45% rise in their sales.
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