Bounce Rate
Measuring Visitor Engagement: Tools + Tips
“Engagement” in the web analytics world is about as emotionally-charged a word as it might be with someone you’ve been dating for a week. At best, it’s a conversation-killer. At worst, it’s a nuclear warhead. Marketing and analytics experts have a hard enough time agreeing on what exactly engagement is, let alone finding the metric(s) to illustrate it.
But this confusion among smart people makes sense when you think about it. When was the last time you had a face-to-face conversation with someone, only to realize they weren’t listening? How can we expect to measure engagement with metrics, when we often can’t tell if the person right in front of us is truly engaged? In fact, the only people who can reliably tell when you’re tuning out are your friends, family, and significant others. There’s a reason for that. They’ve seen your behavior before, analyzed it, and suddenly, in their minds, you’re easier to predict than Paris Hilton.
Likewise, engagement means different things to different websites. Since each site has its own unique characteristics and purpose, engagement must be defined by your site’s goals — not by Amazon’s, eBay’s, or Ms. Hilton’s.
The first step is to define how an engaged visitor behaves in terms of your site’s goals.
- What is the ultimate purpose of your site?
- Content site example: Get people to read my cooking blog.
- Commerce site example: Get people to buy hats from me.
- What actions do visitors exhibit when they’re interacting with the site and moving toward its ultimate purpose?
- Content site examples: Reading articles, signing up for newsletter, subscribing to RSS.
- Commerce site examples: Viewing products, reading reviews, viewing about us page, adding items to cart.
So, what exactly does an “engaged” visitor do on your site? What are some of the clues that engaged visitors leave behind in your analytics?
- Do they stay long?
- Do they click a lot?
- Do they visit the site many times?
- Are their repeat visits days apart? Weeks apart?
- Do they penetrate deep into the site or bounce off of it?
- Do they view lots of pages?
- Do they take a given action like sign-up for a newsletter, refer a friend, or download a file?
- Do they leave comments on your blog?
- Do they link, Digg, Stumble, or otherwise find you del.icio.us?
- Do they purchase?
- Do they purchase repeatedly?
Some sites will have an even harder time than others at capturing the elusive engagement in their analytics and may instead need to combine the quantitative data with qualitative analysis, like surveys. (Here are three great survey questions.) But proceed with caution. While many sites could benefit from using surveys on their quest to find missing pieces of the engagement puzzle, it’s easy to be mislead by what customers tell you in a survey. Ever take an online survey where the questions were fundamentally flawed? Do you prefer the taste of New Coke to CocaCola Classic? (The folks who were surveyed did.)
What’s even more dangerous is that only certain personality types bother to participate in surveys in the first place. (And good luck getting a Spontaneous customer to fill out a survey unless they’re either angry or bribed.)
A common approach to getting an initial handle on engagement is to take certain metrics that relate directly to your visitor’s main goals: those that measure if visitors are taking the actions you want them to. Monitor them closely, and see how these metrics play off each other when certain changes happen — e.g., changes in season, updates to a checkout process, special promotions, inactivity on a blog, industry trends — affect the site.
When Metrics Lie
When selecting which metrics to use, keep in mind that it’s easy to be deceived by your own numbers. Proceed with caution by giving an in-depth look into the stories these metrics can tell you before placing your trust in them. In order to be sure that your metrics are an accurate reflection of engagement, you shouldn’t take one-off metrics at face value.
“Page Views” are a great example of a metric not worth trusting on its own. In this case, it may very well be that a visitor isn’t finding what they’re looking for. Perhaps they’re “pogo-sticking” from page-to-page in search of what they need. Now you’re keeping them on the site longer, thus increasing “Time Spent,” which, again, can be deceiving by itself. Although wasting the customer’s time — so long as they don’t leave the site — will increase the page views and time spent, it may not mean you’re actually engaging visitors. (Not in the way we’d hope, anyway.)
Engagement Metrics + Toolkit
With your site’s goals in mind, and a rough understanding of how an engaged visitor behaves, here’s a sample of some metrics that may be useful relative to your site’s purpose:
- Visitor Engagement Index = (Visits) / (Visitors)
- Take Rate = (# of Visits Taking Part in Desired Activity) / (Visits)
- Repeat Visitor Share = (Repeat Visitors) / (Visitors)
- Heavy User Share = (# of Visits with X or More Pages Viewed) / (Visits)
- Committed Visitor Share = (# of Visits Lasting Longer Than X Minutes) / (Visits)
- Committed Visitor Index = (# of Page Views in Visits Lasting Longer Than X Minutes) / (# of Visits Lasting Longer Than X Minutes)
- Committed Visitor Volume = (# of Page Views in Visits Lasting Longer Than X Minutes) / (Page Views)
- Bounce Rate = (# of One Page Visits) / (Visits)
- Scanning Visitor Share = (# of One Minute Visits) / (Visits)
- Scanning Visitor Index = (# of Page Views in One Minute Visits) / (# of One Minute Visits)
- Scanning Visitor Volume = (# of Page Views in One Minute Visits) / (Page Views)
- Average Order Amount = (Total Sales) / (Total Orders)
- Sales Per Visit = (Total Sales) /(Visits)
- Repeat Order Rate = (# of Orders From Existing Customers) / (Total Orders)
- Order Acquisition Ratio = (Marketing Expense/Number of Orders) / (Marketing Expense/Visits)
- Conversion Rate = (Number of Sales) / (Visitors)
- Page Views per Visitor = (# of Page Views) / (Visitors)
- Average Time on Site
(Eric Peterson even offers his own complex engagement calculation, and discusses the web analytics community’s challenges to it.)
Once a set of metrics is selected that directly relates to potential engagement on your site, constructing a weighted average of the set might help. This needn’t be some painfully complicated multivariate regression model, needing someone with rocket science experience like our buddy John to make sense of it; just some metrics that can serve as a collective vital sign to measure how well your site is engaging people while carrying out its core mission.
Jim Novo makes a potent case for using visitor recency to measure engagement and how to leverage it. If you can collect information relative to the history of each specific user, and the recency of their visits, his approach can send your ROI skyrocketing.
Novo’s approach shows how recency can explain a visitor’s potential value, given their propensity to return to your site frequently, as represented by the horizontal axis below. The vertical axis, meanwhile, shows how often the visitor has taken the action being measured.
Although fuzzy and directionally correct at best, engagement is vitally important to measure because it’s a predictive metric. If your current visitors are exhibiting behaviors indicating that they’re engaged, they’re likely to return soon — and often. If you see signs that visitors are becoming less engaged with the site, it’s safe to suspect that recent changes to your site or the flow of its traffic may be working against you. Either that or your competition’s finally outdone you. Regardless, it’s always good to know when to hang it up and try something new.
Engagement can also be a useful measure of the effectiveness of your branding. If visitors are showing signs that they’re engaged with your site, they’re generally showing affinity for your brand.
While engagement has become a heated buzzword, and arguably an excuse, it’s important not to be mislead. Since it’s a state of mind for your visitors, and therefore not easily quantifiable, there’s no simple way to measure engagement. But attempting to measure will help you to keep your site from proposing on the first date.
Do you have any unique approaches for measuring engagement? Let us know. We’d love to get a conversation going in the comments.
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Written by:Ronald Patiro
Established Brands Beat Newcomers With Usability
Having a recognized brand buys you a lot of forgiveness with potential customers. But, regardless of your brand’s position, time is money when it comes to online conversion, and homepage design & usability play a big role.
The Rimm-Kaufman Group’s Larry Becker writes about a recent study suggesting that:
. . .high growth companies are not evaluating and improving their home page designs in a systematic way. By comparing the home pages of the Fortune 30 against Inc Magazine’s fastest growing companies, researchers from Minnesota State University found the Fortune 30 had a usability score over 36% higher than the fast growing companies.
Sure, the brands in question were compared on “best practices” from 2001, but it seems the bigger brands are still beating the smaller guys at the fundamentals.
How has usability–good or bad–changed your opinion of a brand? Let’s hear some stories in the comments…
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Written by:The Grok
Measuring the “Piss-Off Factor” — Part II
Okay… So, the methodical types have called me out on my last post. While I explained the “Piss-Off Factor,” I didn’t explain how to measure it. Although “measure” was indeed in the title, I didn’t mean it in the web analytics sense; rather, I was hoping to get people thinking about the customer experience as a whole. More to the point, that what we can’t measure is sometimes more important than what we can.
For instance, my example that although a “live chat” option may improve conversion rates incrementally in some cases, this minor conversion boost says nothing of how many customers you’ve turned off by demanding they interact on your terms–if only to “close window” and be done with it. Even worse, a conversion boost from something like a pushy live chat could mask the fact that you’re annoying potential customers. Rather than being concerned, you’d likely think you’re adding value. (I’ll explain more in a moment.)
Still, I do love you guys. You keep me honest.
So, how do you actually measure your “Piss-Off Factor” (POF)?
Like anything else, in order to know how to fix it, you must first define the problem.
The reason POF is so dangerous is the simple fact that measuring POF is very difficult. In the online world, the customer experience is measured largely by analytics. Most companies try to understand their customers by analyzing data about customer behavior. Data can tell you what your customers are doing, but it cannot tell you why.
The other problem with data is it measures only what “is,” and not what “could be.” If the problem is something that exists on your website, then you have an easier chance measuring the POF factor. But sometimes it’s what’s missing that causes a problem. Something should be there that isn’t. How can you measure something that doesn’t exist? I have some thoughts on both.
Find Out Where You’re Pissing People Off:
Look at pages with high abandonment rates. How did the visitor get to that page? What link did they click? What was the verbiage of that link? What were they expecting to see? Did the link deliver on the promise?
EXAMPLE: You’re on a product page. You want to find out more about that particular product. You click on “Learn more about our products,” expecting to be taken to a page that gives more detail about, that’s right, the company’s products. But instead, you’re taken to a product category page that only lists their products with little or no information. You wanted to “learn more,” but the link didn’t deliver on its promise. (A more accurate link would have been “See our products.”)
Check for copy that sounds “sales-y.” What verbiage are you using that’s turning them off? Look for any language that sounds like canned hype. At best, customers are ignoring it. At worst, it makes you seem pushy and fake.
EXAMPLE: “Better than money-back guarantee!” sounds like a gimmick. Instead, try “Money back guarantee. We mean it.” AND if you say you’re the “best,” you’d better have proof to back it up. Grandiose, unsubstantiated claims turn people off.
Mine your customer communications. Look at emails, monitor phone calls, and pay close attention to live chat sessions. Talk to customer service reps, sales people, and anyone else who has direct customer contact. What issues are your customers having? What questions are they asking? What are their objections? Make sure that you’re answering their questions and addressing their objections on the website.
EXAMPLE: You have a subscription model, and you charge a membership fee. Other competitors offer a similar service for free. A common customer objection is “Why should I have to pay?” Make sure you have verbiage on your site, at the Point of Action, that either explains or explicitly says “Here’s why you should pay.” Clearly explain why you’re different from the free site and list out the specific benefits members get with your paid memberships. Ignoring objections and not answering your customers’ questions will piss them off.
Gain customer insight through usability testing. I say this with some trepidation. The artificial environment of many usability tests can taint the results. But it can be useful when you’re too familiar with your products and website and need a fresh perspective on how customers approach and use your site.
EXAMPLE: You think a Call to Action is perfectly clear, yet the visitor has to look really hard to find it.
Only ask for the personal information you absolutely must have. The more personal information you ask for, the more you’ll piss off would-be customers. Ask for the minimum and be very clear about why you need that information and what you’ll do with it.
EXAMPLE: My personal pet peeve is when sites ask for a title “Mr., Mrs., or Ms.” I’m not a Mrs., but I despise Ms. Men can just click “Mr.” But for women, why do you need my marital status?
See what blogs are saying about you. Search the blogosphere to see if anyone is talking about their experience with your website or product.
As far as exit surveys go, proceed with caution. You can get some very valuable information, but they can also increase your POF.
What You’re NOT Doing That’s Pissing People Off:
This one is a lot more tricky. What is it that your customers want from you that they’re not getting? What are they looking for that they cannot find? What deeper motivations do they have that you are not addressing?
This is where the “data” problem intensifies. This is where “what” your customers are doing is little or no help; it doesn’t provide the deeper customer insight you need.
That’s why Future Now developed Persuasion Architecture™ (click to download the white paper). The methodology gives you deeper insight into your customers and allows you to see your website through their eyes. We do this by creating customer personas.
Personas allow you to view your site through the eyes not of your “average” customer, but from the viewpoint of different customer buying modalities taking into account different needs, motivations, knowledge levels, and goals. What one customer likes may actually turn off another customer. One customer may only need one question answered; another may need lots of questions answered.
In my experience, personas are by far the best way to truly look at your website from your customer’s idiosyncratic points of view. Plus, it takes into account different points of view and allows you map out what’s missing–and what “could be.”
EXAMPLE: If you’re a wireless company selling phones on the Internet, customer personas will have differing buying needs. Some are very knowledgeable about these phones. Some are not as knowledgeable. Some care about having lots of cool features like Internet access, taking pictures, etc. Another persona may care about personalized ringtones. Read about my experience with Verizon Wireless to get a sense of how what’s missing is actually causing a high POF.
To sum it all up: Use the suggestions above to gain insight into what you’re currently doing that’s causing a high POF. If you want to know what you’re NOT doing that is causing a high POF, consider creating personas to give you the deeper insight that data and analytics can’t provide.
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Written by:Holly Buchanan
