Proof of Concept: What It is and How to Do It Right
Before developing an idea into a product, there’s a crucial step that every business must take: executing a successful proof of concept. Learn more.
Data is only valuable when we know how to use it. Even with better access to data, many marketers still don’t know how to interpret it effectively to better understand their customers. The brands that extract the most value are the ones that make testing a priority, take a pragmatic approach to collecting customer data, and know how to turn information into action. These seven tips will help you run successful tests and use your data-driven marketing decisions more effectively:
The test you would run for a group of 1,000 users may deliver completely different results for a group of 10,000 users. There are many ways to estimate the right scale for your test, but this easy formula for a population of any size will give you a 95% confidence level, with a standard deviation of 0.5 and a ± 5% margin of error:
sample = population / (1 + (population*0.0025))
For example, if we were looking at a population of 10,000, we’d aim for a sample of 385 individuals:
sample = 10,000 / (1 + (10,000*0.0025)) = 384.6
If your sample volume is too low and you can’t easily reach the scale you need, just extend the period of time allocated to testing. The improvements in accuracy to your data driven marketing strategy will be worth the extra time it takes.
How much value your key stakeholders assign to data-driven marketing depends on their previous experience and current priorities. To get them excited about—and willing to invest in—your programs, look at data from their perspective. Show them how marketing data can support the programs that matter to them and drive the business goals they care about most.
To get out in front of your competition, start early and don’t be afraid to make mistakes. Allocate a testing budget, so that experimenting won’t affect your bottom line, and then test repeatedly. By building testing into your budget, you can encourage your team to take risks and cut through the red tape that might hold up innovation and experimentation. Scour industry journals for trends and emerging platforms to fuel your experiments. Hold informational meetings to get new perspectives from other stakeholders. Be flexible, and iterate early and often when using data in marketing.
Data has a place in every decision, but that place isn’t always at the center. Data can tell you a great deal about past performance and help you project the results of future experiments, but it can’t tell you anything about the test you haven’t thought of yet. Companies that use data well rely on their creative human insights to propose new tests and use computers to collect and evaluate the results.
When using data in marketing is a priority, you should view your data partners as a marketing tool. Pick high-quality vendors who share your goals and leave you in complete control of your data. Look for flexibility and transparency, and be open to new and interesting ways to apply any technology you invest in.
Click-through conversions carry a different value than view-through conversions and customers who have purchased in the past behave differently than new customers. Try to avoid looking at your data as a monolithic block—instead, find ways to separate your data pools so that you can pull the most relevant insights from each data set.
Because so much data is available, it’s easy to get trapped in a cycle of collecting and evaluating without taking action. But without action, all the data-driven marketing decisions in the world won’t deliver results. Companies that seize the testing possibilities in every new input—and see the potential for data collection in every new idea—will find themselves on top in this era of big data.
To learn more about testing, collecting data, and taking action based on your findings, check out this AdRoll webinar and start building your measurement toolkit today.
Last updated on August 17th, 2022.