Part 14: Making Sense of Visitor Responses

How to read and interpret data

Understanding trends in data is the most important thing you can do when developing a business strategy.

Let’s navigate to the responses tab, if this is a new account, you’re going to need at least 1000 data points for things to start populating in a way that allows you to start to see patterns, this is about 250 subscriptions. so you’ll need about 2500 new visitors that haven’t purchased or subscribed prior.

Click on the Responses menu item

The first thing I do is navigate to “When are you looking to purchase?” question.

This is the first step to understanding our quality of audience, are the majority of people that are filling in our forms fully at least in buying mode.

This is the first lesson in understanding that not even everyone that signs up for your popup offer is looking to buy even in the next few days, combined it’s about 80% of people that are looking to buy quickly, but when we look at conversion by answer.

There’s one clear winner. Today.

So all forms have this question and the results have been the same across every single company we’ve worked with, which means it’s a constant distribution.

So we’re going to click on today.

This is going to add “Today” as a filter to our answers, so we see what the answers that people said “Today” said for the other questions as they convert at the nearly 3x the level of those that say a few days.

The above is based on product type, in percentages that answered “Today” – essentially this is telling us which products to advertise, based on answers and order quantity. we should also toggle quickly to absolutes to make sure none of the numbers are irregular or over represented.

So if we’ve narrowed down our answers to Today with the highest conversion rate and Boxer Briefs as the outsized revenue and order driver, we should click on “Boxer Briefs” then work to the question “What matters most?”.

Let’s click Boxer Briefs.

Now we’ve gone down two levels to determine what to advertise that has the highest chance of conversion from our traffic.

So we’ll look at “What matters most to our audience” for “Boxer Briefs”

We’ll evaluate both Percentages and Absolutes

From here we’re seeing a pretty cascading answers to orders correlation. No matter what someone says matters to them, if your product offers it, the conversion should be similar.

We can see though that both on the revenue side and the conversion side that “Super Soft Fabric” and “Large Pouch” are values that not only convert at a higher amount but also drive more revenue with fewer orders.

Waistband that doesn’t flip though is the top ranking answer, order, and 3rd in revenue.

When we go to create Ads for Boxer Briefs it’s now clear we should focus on different variations related to waistbands that don’t flip, super soft fabric, and large pouch.

We’re going to run this back on the second most popular product Briefs.

And also in absolutes.

From this data we can see that for Briefs, “Support” and “Super Soft Fabric” are the top two angles driving the most revenue and the most orders.

We’re likely going to need more data to fully act on these, but this a a great start from a small data set.

The more data you have the more patterns emerge.

Create a Preset

When you’ve drilled down to Today and your top product, make sure the time frame is at least 30 days then save it as a preset.

Then name your preset

My suggestion for naming your preset it 30 Day – Boxer Brief – Ad Angles

Time, Product, Context

Once saved, it will appear as a tab next to the default view

The other tabs in Responses worth paying attention to are the “Time to Purchase” Tab in the Default View.

These are done in confidence intervals over the course of the time period selected.

So in the above example we’re using 30 days and showing that 90% of sales from subscribers over this period happened withing 3.9 hours.

So they got one email via the welcome series. The vast majority of people using this approach convert within minutes of signing up.

The below part of the graph requires a bit more time to develop but will tell us the time between 1st and 2nd order by percentile for the last 180 days, so when you’re planning marketing activities and or offers to people you should know when to amp up the efforts to make sure people shop again.