By Sarah Montoya
As my previous post on scrappy marketing strategies and the importance of market research have mentioned, I am on the management team of an all volunteer run non-profit. I am not a product developer but I am taking Femgineer’s Ship It course because so many of the topics apply to managing an organization that is committed to keeping our overhead cost down to nearly nothing.
Despite my love of the ego boost that comes with building followers, I am aware that organizationally numbers that make us look good but are not connected to actions are not helpful predictors of how effective we are. As Do Good Lab moves forward with our marketing strategy we need to focus on real metrics to see the black and white information in front of us. People are either responding to our marketing by donating or they are not. With that in mind I was excited to learn how to use analytics for something other than my own narcissism. I signed up for the class on scrappy marketing and the follow up class on analytics because I want to be sure that we are developing a lean market strategy and once that strategy is going I need to be able to know if it is working.
One of the most significant things Poornima said in the scrappy marketing class was that these strategies need to be built to scale. Once we know what our audience responds to we can grow our audience and our reach. With Do Good Lab’s commitment to keeping costs low, knowing that we don’t have to take on costs as we scale is huge. However, we can’t know if what we are doing is working if we don’t know how to analyze the numbers once we have them.
As we are moving forward we are experimenting with ways to reach our target audience and as with any good experiment we need to gather the data and adjust our practices in response. The class goes through all the steps needed to isolate information such as:
How to determine causation vs correlation in data.
What are key performance indicators.
How to recognize patterns that you need to respond to.
It also sets out good reminders of what we all learned in science class in middle school about determining our measures of success in advance. We need to create a hypothesis and compare the results in order to know what our patterns and measurements mean to us. Once we have done that we need to do it again. Gathering and analyzing data is an ongoing process once we have our product out there.
Deciding what these numbers should be is one of the challenges we have to figure out individually. Industry standards are great, but we are not every other organization, we are who we are and we need to decide what success looks like so we can respond appropriately to the metrics we get back.
Once we have our numbers and our goals, we can use the many free resources out there to gather data. As always Poornima does a great job walking the class through the most accessible options, showing what each chart means and letting us know why we should care. With this information I feel much more prepared to not only understand what is working, what needs to change, and what might factor into the changes.
Want to learn more about metrics that matter and get step-by-step guidance, then check out our Lean Product Development Course Learn more!
