How can you use data to support your pitch for a creative project?

The best creative pitch is the one founded on solid consumer/user insight. Coming up with solid data supporting the consumer insights should be the corner stone of the pitch. Then once the business solution for the problem is presented, data comes very handy in supporting the "size of the prize". I would usually start with total addressable market, which is based on hard facts, and then set up share of market targets, usually two or three scenarios.

1. Identify your desired outcome 2. Make it realistic 3. Set a timeframe 4. Break it down 5. Write it down 6. Review and revise

I think when you are trying to decide what kind of pitch you're going to create, you should understand what the implications of them saying yes to your pitch is. You might think that putting a pitch deck together is the end all be all, but ultimately once they approve your pitch, you should begin with the end in mind of if they say yes, then what are the action steps you're going to take to move forward.

1. Informed Decision Making 2. Accuracy and Precision 3. Problem Solving 4. Targeted Marketing and Personalization 5. Performance Evaluation 6. Research and Innovation In summary, relevant data is crucial for informed decision making, accuracy, problem-solving, targeted marketing, performance evaluation, and research. It empowers individuals and organizations to make evidence-based choices, leading to better outcomes and progress.

in the creative industry, it's hard to find actionable data that is not from an old case study or from a case study with a sample size that is not really relevant to your objective. However, putting a large amount of social media posts, Google reviews, or YouTube comments into an AI model like ChadGBT and then creating a trend plot from that data in Excel or some other data analysis tool will help you create the most relevant data. If you are doing something that has a lot of data already, you can cross-reference that with maybe a bigger study, but I think it's best to use all the tools at your disposal to create insight your own data.

Data analysis and marketing are not usually a hand-in-hand combination. I think it's important to clearly label and identify all the variables that you are analyzing and run them by somebody who does work with data, an accountant, a scientist, an engineer, someone in your development team, just somebody who understands how numbers work because your job as a marketer is to market effectively. If you have advanced data analytics training, that's great, but you should always get a second opinion on how you want to analyze your data.

This is a job in and of itself, so I would make sure that you have a good handle on everything you're doing and your data that you have analyzed. Then, go on YouTube or get an AI tool or even Google Sheets to help you create a simple visual of your output. I've been on projects where it took us 20% of the time to organize the data and 80% of the time to create graphs and charts that people liked. Ultimately, that can be a huge waste of time if it doesn't tell the story you're trying to tell.

Once you have your data and analytics put together, you need to put a simple presentation from start to finish about why this is a good opportunity for the recipient of your presentation to approve. I would honestly use as many rhetorical devices as you could in writing strategies, but ultimately, you need to sell an outcome. Say, if you do this, then X, or if you don't do this, then we will miss an opportunity.

You should really just put this presentation together and run it through people who don't know what you're working on and see if it makes sense to them. You're going to be in your head a whole lot about this, and if you don't put it across somebody who is unfamiliar and they don't understand, then you're not going to really go anywhere. Also, understand the scale and magnitude of this project, whatever it is. If it is not a make-or-break situation for your company, you can be a little more lax with some of the details. But if this is something that would go on Shark Tank, for example, or to a board of directors, then you're going to really need to refine this and work on the performance element as much as the data element.