Data Spotlight: Conversion Rates

Talk data to me!

I'm a systems geek, but I'm also a data freak.

In pavement management, we use data to tell a story: we follow how pavements perform over time, track trends using deterioration models, use those models to predict future pavement condition, and develop a maintenance and rehabilitation plan to maximize the condition of the network while minimizing the cost to do so.

In business, we use data to tell a story: we follow how our marketing efforts perform over time, we track performance using metrics, use those metrics to anticipate the outcome of future marketing efforts, and develop a marketing strategy to maximize sales qualified leads while minimizing the cost to do so.

Correction: we *should* use data to tell a story...

As engineers we live and breathe data but somehow that passion doesn't translate to business data. As engineers move up their organizational food chain, they inevitably have to learn how to generate revenue to sustain a business. The marketing and sales process can be daunting, but only if you allow yourself to be overwhelmed by perceived smoke and mirrors.

It's not magic; it's just data.

One metric (of many) that is essential to track in any business is the conversion rate. A high conversion rate is essential for any business. It means that for every visitor you have, you want to see at least one action taken – whether that’s a purchase, a submission or some other form of engagement. There are many factors that can influence your conversion rate, like your marketing strategy, copywriting skills, landing page design, and optimization of your website’s analytics. By understanding these factors and putting in place effective measures to optimize them, you can increase your bottom line while keeping your customers happy. Keep reading for tips on how to understand and optimize your conversion rates.

Step 1: Understand What a Conversion Rate Is

Wait a minute... What's a conversion?

A conversion happens when someone responds to your call to action (or CTA). Your conversion is tied to whatever your CTA is. 

Wait a minute... What's a call to action?

Any time you ask your audience to take a specific action, that's a call to action. A CTA might look like:

• If you like what you've read in this article, don't forget to "like" this post!
• What resonated with you the most? Comment below!
• Share this article with someone who needs to see it.
• Subscribe so you won't miss any future issues of the Doing More with Less newsletter!

*wink*

You get the idea.

So what's a conversion rate?

Your conversion rate is simply the ratio of conversions to the audience. 

If your CTA is to "like" a particular post, every time someone "likes" that post, it's a conversion.

If 10 people "liked" your post and 100 people viewed it, your conversion rate is 10%.

If 10 people "liked" your post but 1,000 people viewed it, your conversion rate is 1%.

Step 2: Identify Your Goals

What are you trying to accomplish? Do you want more engagement? Do you want more email subscribers? Do you want more followers?

Your goals should be specific and measurable.

Let's say you have a landing page for visitors to subscribe to your newsletter and you want to grow your email list by 100 subscribers (I like using examples with 100... can you tell?). Assuming that you have a 1% conversion rate and change nothing about the design of your landing page, you would need to get 10,000 sets of eyeballs on your landing page to get an additional 100 subscribers.

Alternately, you can optimize your landing page to (hopefully) increase your conversion rate from 1% to 10%. This means that you would need only 1,000 views to get 100 new subscribers.

It's not magic; it's just data.

Step 3: Understand Your Data

It's not enough to just collect data. Data isn't a gift shop knick knack that you put on a shelf after your family vacation to Hilton Head; always within view but never truly seen. You have to understand your data so that you can use it to make data-driven decisions.

 A client of mine sent out a survey to a list of 100 people.

1 person completed the survey.

Her immediate thought was that there was an issue with her mail deliverability.

I invited her to look at the data.

The survey went out to 100 people (it really was 100 this time!).

Of those 100 people, 90 clicked the survey link and viewed it (there goes the mail deliverability hypothesis!).

Of those 90 people, 1 completed it.

There are two metrics at play here: click-through rate (i.e. % that clicked on the survey link) and survey response rate.

Her click-through rate was 90% (which is insane; even 20% is impressive).

Her survey response rate was 1% (ideally you'd want this to be >5%).

The data shows that most of the people in this audience were highly motivated to click on that link, however, they're being turned off by some aspect of the survey (my guess: it was too long!).

It's not magic; it's just data.

Step 4: Monitor, Analyze, Test, Optimize

Once you have a solid understanding of what you're tracking and why you're tracking it, you can use your data to pinpoint exactly how you can improve.

Example A: You send periodic emails to your list. The open rate is low, which tells you that people are not motivated to open your email.

Test 1: You assume that the subject line is not appealing so you tweak the way you craft your subject lines.

Result: No change.

Test 2: You assume that your list is too broad so you segment your list to send more targeted content to each group.

Result: Your open rate increases.

Example B: You send periodic emails to your list. The open rate is average, but the click-through rate is low. This tells you that people are not motivated to click on your links.

Test 1: You assume that you need to change the location of the CTA in your email.

Result: Your click-through rate increases slightly.

Test 2: You assume that you need to update your copy to clarify and/or highlight the benefit of clicking on the link.

Result: Your click-through rate increases significantly.

It's not magic; it's just data.

Keep an eye on your data, use it to make hypotheses, tweak and test, and optimize through iteration.

The Bottom Line

While a conversion rate is the tip of the iceberg, this one metric illustrates the power of using data to optimize your processes. Understanding conversion rates is the first step to optimizing them, even if it seems intimidating at first. Continuous testing can help you make smarter choices that ultimately boost your conversion rates. With the right tools and mindset, you can learn to consistently improve conversion rates, and your user experience, and in the long run, your bottom line.

It's not magic; it's just data.

Oh... I almost forgot...

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