CXL Institute Growth Marketing Minidegree Week 2 Review

  1. Design Your Experiment: Start with your objectives. What is your goal from running the experiment? Make sure you’re tying it to a specific metric like retention rate. Also be sure to structure a hypothesis correctly.The key components of a hypothesis are the independent variable, dependent variable, and your assumptions.
    A. Independent Variable: An example of this would be the number of emails or communications about the product or service.
    B. Dependent Variable: An example of this would be the % of new customers who buy or purchase the product or service.
    C. Assumptions: You include your assumptions about the outcome. As an example, people who will buy more from more communication because they will be more educated/informed about the value of the product.
  2. Ship: Get your experiment built and make sure you are tracking properly. Set the test up in a staging environment and thoroughly QA the experiment.
  3. Analyze: Look at the results of the test and see if it was a winner or not. Make sure you have quantitative measures in place as well as qualitative measure on the experiment to observe behavior.
  4. Automate and Scale: The reason that you automate and scale the results of the experiment is because you don’t want to continually experiment just to create more work for everyone else, so this should be considered when selecting experiments (how easily does it automate and scale?). The reason why you automate is so you can obtain that permanent lift in value to the company without creating continual resources to maintain that lift.
  1. Sales Team: They have contact with the customer every single day. They will know a huge amount in their heads already about the customers. They will also know firsthand what the most common objections they get and the reasons for not purchasing.
  2. Customer Support Team: They have incredible insights because they deal with frustrated customers after the sale and can also inform of how the product/service is performing at the moment to customer expectations. They also very likely have a rich database of commonly asked questions. If these items are addressed through the initial sales and marketing, this will also likely reduce the time of closing a customer and free up resources of customer service representative’s time after close.
  3. Social Media: They will not only have insights from their social media analytics about the customer, they will also have insights from interacting with the customers on social media. They will be able to speak to what the common questions customers are asking, common criticisms, along with “top fans” on a platform like Facebook, which you can deep dive into and look more into those exact users.
  4. Analytics: Insight from this team can come from quantitative data like Google Analytics and qualitative data like Hotjar.
  5. Any other Customer-facing Staff:
  6. Internal Data: What search terms are users searching for on the site? What search terms are people landing on the landing pages from (look into Adwords, Bing, Google Search Console, Google Analytics, or a tool like SERPstat for this). Where is people’s attention on the site (what pages and how long are they spending on those pages)?
  7. Social Media Pages: This is broken into two different types of pages.
  8. Followers Pages: What else are they following? What do they share? What do they care about? What questions do they ask?
  9. Competitor Pages: Use Google Ad library to see what ads they are running and how they are communicating with customers. Which ads have they run for the longest. What is their tone for communicating with customers? Are they actively engaging with their customers or just posting content?
  10. Surveys: Surveys through your website, email, app, or even over the phone through customer service after a call can also be immensely helpful in obtaining user-centric data. Don’t fall into the trap of asking too many questions and making it too long. That’s just going to frustrate the customer and you’re going to get less responses. It’s also going to potentially give you more data than what you know what to do with. Also, be mindful that your sample size will be much smaller for a survey. The survey needs to short, succinct, and have a single clear idea of what you want to know from the customer.

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