Experimental research is a method of testing the causal effects of a marketing strategy by manipulating one or more variables and measuring the outcomes. It can help you validate your assumptions, optimize your campaigns, and generate new insights. In this article, you will learn how to use experimental research to test a new marketing strategy in six steps.
The first step is to define your research question, which should be specific, measurable, and relevant to your marketing goals. For example, you might want to test how a new pricing strategy affects your sales, or how a different messaging style influences your brand awareness. Your research question should guide your hypothesis, which is a tentative statement about the expected relationship between your variables.
Defining a clear and focused research question is the foundation of any successful marketing study. It sets the stage for hypothesis development and ensures that the research is aligned with strategic objectives. By testing specific variables, such as pricing strategies or messaging styles, marketers can gain valuable insights to inform their decision-making processes.
Experimenting with new marketing strategies can be a game-changer. Here's a quick guide to make it smoother: 1. Clear Hypothesis: Define what you're testing. Clarity is your best friend. 2. Smart Design: Choose between-subjects or within-subjects wisely. 3. Baseline Control: Always have a control group. It's your reference point. 4. Pilot Test Pitstop: Test small before going big. 5. Look Beyond P-values: Practical significance and effect sizes matter too. 6. Ethical Checkpoint: Respect people. Get consent and make it positive. 7. Real-world Rollout: Winners from the lab/promising ones get a shot on a larger scale in the real world.
To avoid a biased confirmation of the results you expect or hope to see, draft your questions so that they can be proven or disproven equally. This is the same as writing a well-formed hypothesis. Example: You’ve heard that Google Ad campaigns can increase sales by as much as 50% within 2 months. For your business, the cost of running a new Google Ad campaign is equivalent to 10% of your monthly sales. Weak Question: Will running a new Google Ad make us more money? (Hard to test because undefined criteria) Strong Hypothesis: Running a new Google Ad will increase sales by 15% or more after 2 months, over 3 consecutive months. (Test, then accept/ reject)
When conducting marketing research, it is important to start by defining a specific and measurable research question that aligns with your marketing goals. Your research question should be relevant and guide your hypothesis, which is a tentative statement about the expected relationship between the variables you are studying. For example, you may want to investigate how a new pricing strategy impacts sales or how a different messaging style influences brand awareness. By formulating a clear research question and hypothesis, you can focus your research efforts and gather meaningful insights to inform your marketing strategies.
The next step is to choose your experimental design, which is the structure and logic of your experiment. There are different types of experimental designs, such as randomized controlled trials, factorial designs, or quasi-experiments, each with its own advantages and limitations. You should select the design that best suits your research question, resources, and ethical considerations. For example, if you want to test the impact of a new email subject line on your open rate, you might use a randomized controlled trial, where you randomly assign your subscribers to two groups and send them different emails.
Selecting the appropriate experimental design is crucial for ensuring the validity and reliability of marketing research. By carefully considering factors such as research question, resources, and ethical implications, marketers can effectively test variables and derive actionable insights. For instance, employing a randomized controlled trial to assess the impact of email subject lines on open rates can provide valuable data for strategic decision-making.
The third step is to identify and operationalize your variables, which are the elements of your experiment that you manipulate or measure. You should have at least one independent variable, which is the factor that you change or control, and one dependent variable, which is the outcome that you observe or measure. You might also have one or more control variables, which are the factors that you keep constant or balance across your groups, and one or more confounding variables, which are the factors that might affect your results but are not part of your experiment. You should operationalize your variables, which means defining how you will measure or manipulate them in a clear and consistent way. For example, if your independent variable is the email subject line, you should specify the exact wording and format of each version.
Selecting and defining variables is essential for a well-designed experiment. Carefully operationalizing independent, dependent, control, and confounding variables ensures clarity and consistency in measurement and manipulation, ultimately leading to reliable research outcomes.
The fourth step is to select and recruit your sample, which is the group of participants or units that you will include in your experiment. You should choose a sample that is representative of your target population, which is the group of interest for your marketing strategy. You should also determine the sample size, which is the number of participants or units that you need to achieve a valid and reliable result. You can use statistical methods or online calculators to estimate the sample size based on your research question, design, and variables. You should recruit your sample in a fair and ethical way, and obtain their informed consent if necessary.
Selecting a representative sample is crucial for a valid marketing strategy. Determining the appropriate sample size using statistical methods ensures reliable results. Ethical recruitment and informed consent are essential for maintaining integrity in research practices.
The fifth step is to conduct your experiment, which is the process of implementing your experimental design and collecting your data. You should follow a detailed protocol that describes the steps, procedures, and materials that you will use in your experiment. You should also ensure the quality and integrity of your data by minimizing errors, biases, and external influences. You should document and store your data in a secure and organized way, and follow the ethical principles and guidelines for your field.
Conducting an experiment requires meticulous planning and execution to ensure reliable results. Following a detailed protocol, minimizing errors, and adhering to ethical principles are crucial for maintaining data quality and integrity. Proper documentation and storage of data are essential for the validity of the experiment.
The final step is to analyze and interpret your results, which is the process of applying statistical methods and techniques to your data to test your hypothesis and answer your research question. You should choose the appropriate statistical tests and tools based on your research question, design, and variables. You should also report and communicate your results in a clear and accurate way, using tables, graphs, and summaries. You should interpret your results in the context of your marketing goals, and discuss the implications, limitations, and recommendations for your marketing strategy.
Analyzing and interpreting results is the critical phase of any experiment. Choosing suitable statistical methods, clear reporting and contextual interpretation are essential for deriving meaningful conclusions. The implications and limitations of the findings should inform future marketing strategies, ensuring practical relevance and impact.