Environments Around An Organisation
For marketing efforts to be successful, an understanding of the environments around an organisation is vital as they can have varying different impacts on an organisation- these can be negative, positive or a mixture of both. Environments can be classified as two types: the micro and macro environments.
The micro-environment are all of the influential parties directly around an organisation, and thus have a close and direct impact. These include the organisation itself, its suppliers, competitors, partner companies, intermediaries, the customers, and publics (such as the media, consumer groups and so on).
The macro-environment are all of the influential, over-arching parties that, whilst aren’t in direct contact with an organisation, have a larger impact due to their nature. These include the demographics or characteristics of the larger markets and society, economic forces, the natural environment, technological forces, political, legal and governmental forces as well as larger cultural impacts.
Competitive Forces Within a Market
Competition always have a direct impact on an organisation. The best way to analyse the competitive strength within an organisation is to look at five key aspects:
(1) The current industry competition, or segment rivalry between organisations
(2) How much power the suppliers have
(3) How much power the customers/buyers have
(4) The potential threat of new competitors entering the market
(5) The threat of substitute products
By judging the extent of these five forces, an organisation can determine how tough the competitive force is within a market.
Marketing must always be able to gain an understanding of the current situation the organisation is in within a market. By doing so, a marketing strategy and action plan can be devised to correctly leverage strengths, minimise or remove weaknesses, capitalise on opportunities and be wary of threats.
One way to analysis the market is through a SWOT Analysis- Strengths, Weaknesses, Opportunities and Threats. The first two are internal to the organisation and can be a list of what the organisation does well and what it doesn’t do well. The last two are external to the organisation and comprise of a list of potential events on the horizon that an organisation must be always aware of to ensure that it can perform to deal with such events.
Naturally, gathering information and performing research within a market is a fantastic way to gain knowledge on a market. There are many different types of research goals, such as those based on discovering the level of customer satisfaction, potential innovations, product redesigns to better match customer demands, product testing, promotional research and so on.
However, before anything is actually conducted, it is vital that a strong Marketing Information System (MIS) is established. All research has a benefit and a cost, just like customer value. A good set of rules and systems that compose an MIS should weigh up the benefits and costs of conducting research and to what extent.
After assessing the need for information and research, the MIS must also devise a system and strategy for effective data collection, analysis and distribution of the results to the correct parties.
This works alongside the natural progression of the research cycle: first, the problem must be clearly defined. The more concrete this definition, the better the research will be as there is a clearer target to aim for. Second, a research plan is developed. Third, the research is implemented and lastly, the data is interpreted and made available in a report.
Primary and Secondary Research
Upon conducting the research, there are two types of classifications, both with their purpose, benefits and costs.
Primary Research is when a team conducts a completely new, very tailored and specific research plan that aims to directly address the defined problem at hand. Whilst expensive both in a monetary and resource/timing sense, it aims to be the most accurate and most detailed to the problem it is attempting to address as all actions and efforts are specifically designed solely for that one problem. Primary research usually comes after secondary research.
There are a few common approaches to primary data research, most commonly exploratory, which is observing
Secondary research refers to absolutely every piece of research ever conducted before by other parties or by those on different projects to the defined problem at hand. These include past research plans and projects, internet research, and so on. Whilst cheap, abundant and very accessible, it is data that has been collected by other parties which means it may not perfectly fit the current defined problem, there may be accuracy issues, it may be too old or even biased.
Regardless of research type, data must aim to be relevant, accurate, current and impartial to be of any practical use.
Collecting Data For a Research Project
There are many different ways to collect data, each with their own characteristics, channels and methods.
Firstly, the approach. You can focus on the observational approach, which revolves around exploratory research by watching behaviour. The second is the descriptive approach through surveys and questions, and the last is the experimentative approach, which is utilising groups to determine the cause-and-effect relationship, known as causal research.
Collecting information can include online questionnaires, personal interviews, telephone interviews and focus groups.
Choosing a sample for research is another key attribute that can greatly affect the research outcome. Questions like how many, who is to be surveyed and how is the sample chosen are all important questions.
Probability Sample (random)
A simple random sample is where all members of the population have a completely equal chance of selection at random. A stratified random sample is where a particular characteristic is chosen first (such as age or location), and then from that specific group, all members have an equal chance of random selection. Lastly, a cluster sample, the total population is divided into a subgroup clusters and the research is conducted on those only, rather than the whole population.
Nonprobability Sample (non-random)
A convenience sample is where the population most accessible is chosen. A judgement sample is where the researcher decides who to choose based on their belief of which population members best represent their target. A quota sample is where specific numbers of the population are the goal of the research, rather than random representation.
Big data refers to the phenomenon where, today, huge amounts of easily accessible, live data is available pretty much at our fingertips, allowing people to make educated decisions almost instantly. Big data has rapidly changed every market and industry, especially with the rise of social media and the internet.
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