Marketing analytics can help you measure and optimize your marketing performance, but how can you convince your stakeholders and customers that your methods and findings are valid, reliable, and ethical? In this article, you will learn how to justify your marketing analytics approach and results using six key steps.
Before you start any marketing analytics project, you need to clearly define your objectives and metrics. What are you trying to achieve, and how will you measure it? How do your objectives and metrics align with your stakeholder's and customer's goals and expectations? By setting clear and realistic objectives and metrics, you can establish a common ground and a shared vision for your marketing analytics project.
In my experience from the journey of Product Portfolio Management we should go by *Data driven decision making, focused customer approach* and we should keep our eyes open for continuous improvement.l! Understanding personalized requirement and assuring ROI for the marketing budget made and it should give results and forecast for the future.
Most of the experts take this step for granted. First, the Objectives need to be S.M.A.R.T and align with stack holders vision. Second, the right metrics should be chosen, based on the industry of the business, the stage of the business, the platform is being used and etc. Third, make sure the data for the metrics are gathered and stored correctly.
Once you have your objectives and metrics, you need to choose the best methods and tools to collect, analyze, and visualize your data. You should consider the type, quality, and availability of data, as well as the level of complexity and sophistication of your analysis. You should also consider the ethical and legal implications of your data collection and analysis, such as privacy, consent, and compliance. By choosing the appropriate methods and tools, you can ensure that your marketing analytics project is feasible, accurate, and ethical.
As you conduct your marketing analytics project, you should document every step of your process and the assumptions you make along the way. This will help you keep track of your progress, identify any gaps or errors, and explain your rationale and logic. You should also document any limitations or challenges that you encounter, such as data quality issues, missing values, or outliers. By documenting your process and assumptions, you can increase the transparency and credibility of your marketing analytics project.
Before you present or share your findings, you should validate and test them to ensure that they are robust, reliable, and relevant. You can use different methods to validate and test your findings, such as cross-validation, sensitivity analysis, or peer review. You should also compare your findings with other sources of data or evidence, such as industry benchmarks, best practices, or customer feedback. By validating and testing your findings, you can enhance the quality and validity of your marketing analytics project.
After you validate and test your findings, you need to communicate them effectively to your stakeholders and customers. You should use clear and simple language, avoid jargon and technical terms, and use visual aids, such as charts, graphs, or dashboards. You should also highlight the key insights, implications, and recommendations that derive from your findings, and how they can help your stakeholders and customers achieve their goals and solve their problems. By communicating your findings and recommendations, you can demonstrate the value and impact of your marketing analytics project.
Finally, you should solicit feedback and improvement from your stakeholders and customers on your marketing analytics project. You should ask them for their opinions, questions, or concerns about your methods, findings, and recommendations. You should also ask them for their suggestions, ideas, or requests for future marketing analytics projects. By soliciting feedback and improvement, you can foster a collaborative and continuous learning culture for your marketing analytics project.