Web Analytics
Are Your Analytics Reports Breaking News or Listing Facts?
I have a friend who works in the online marketing department for a multi-million-dollar clothing retailer in Canada. Because they’re still stuck in the dark ages and don’t yet have an online store, the company’s web marketing team consists of four people.
A week ago, my friend called me to ask, “What’s the industry average time spent on a site?” Her boss asked her to find out because she was doing a presentation to the marketing team and would be attempting to describe what was happening on their website.
My friend was looking at her analytics reports, assuming they should be reporting metrics like “time spent”, but she couldn’t give me any explanation as to why they were measuring certain things or how it all fit together. This marketing team had no idea what their analytics were trying to tell them.
Sound familiar? Whether or not we care to admit it, this problem is all too common. By themselves, the facts can be deceiving. If the facts don’t fit into a larger story line, they’re meaningless. Just because something happened, that doesn’t make it newsworthy. That’s why…
Marketers should think like news editors.
Your web analytics program works for you, not the other way around. It’s the news wire that serves your staff of reporters and, as editor-in-chief, it’s your job to decide which stories are most important.
There are two types of approaches to web analytics reporting:
• The beat reporter reliably follows the same story from day-to-day. If you tell the beat reporter to follow “time spent”, she will diligently explain where visitors spent the most time, how much time they spent overall, and how much time they spent today versus yesterday, last month, last year, and so on.
• The investigative reporter tries to find the meat of the story; to get the bottom of what truly matters. If you tell the investigative reporter to follow the “time spent” story, she’ll start to ask big picture questions. She’ll want to know why time spent matters, how it relates to your other metrics, whether “time spent” means one thing on one page and something very different on another, and whether it even matters if visitors are spending more — or less — time on your site verses the competition’s. She even wonders if this whole “time spent” thing is really a distraction. She doesn’t want to spend her time chasing false leads.
Like other default metrics, average time spent tells us nothing on its own. The company that my friend works for has over a thousand employees. Most of the staff in their home office and brick-and-mortar stores use computers every day, and many of them likely have their browser set up to go directly to the company’s homepage automatically. Each day, a large amount of their traffic probably comes from employees, not potential customers. If this is the case, the average time spent on their site tells them very little about the customer experience on their website, because employees’ time spent would skew this number. Likewise, the traffic sources would be skewed and the average page views and bounce rates from the landing page would also be skewed.
Don’t use your analytics tool just to report the facts. Become an investigative reporter. For each piece of information you find, ask yourself why it matters. Ask how the metrics tie together. Most importantly, ask yourself how the web metrics you report on tie into your overall business goals.
That’s how reporters break news.
. .
About the Author: Melissa Burdon is an investigative reporter (or Persuasion Analyst) at FutureNow. She’s also a recovering Canadian. Oh, and it’s her birthday.
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Written by:Melissa Burdon
Stop Paying for Bad Keywords in Three Steps
Web analytics reports can be deceiving. They’re great at showing you WHAT visitors did on your website, but they can’t tell you WHY they didn’t do what you hoped they would.
But with the right process and frame of mind, it is possible to use web analytics to get insight into “why” your traffic isn’t converting — especially if you do pay per click advertising.
Here are some ideas for attracting more targeted traffic in order to get higher conversion rates and a much better return on pay-per-click (PPC) spend.
One
• Look at your top traffic-driving keywords (PPC and organic).
Are they highly relevant to the industry you’re in and the products you sell? Do these keywords clearly indicate that the searcher has a motivation to find your solution to their problem? Some keywords may have double meanings and could suggest that the visitor had a completely different search intent than expected. Someone searching “training videos” might actually be looking for “workout training videos,” “management training videos,” or a variety of other things. If the traffic from these fuzzy keywords is converting poorly, don’t be surprised. Stop buying and doing search engine optimization (SEO) for ambiguous keywords. The ultimate goal should be to figure out which key phrases specifically relate to your industry, product or service, and do some PPC and/or SEO to get listed for more relevant keywords.
Two
• Don’t play the generic keyword game.
It both difficult and expensive to get traffic from the most generic keywords in one’s industry. Such keywords are much more competitive in the search engines. You pay more for text ads and it takes a lot of SEO effort in order to get listed organically for these keywords. A lot of these single-word keywords are really only attracting early-stage visitors who are not necessarily ready to buy, anyway! If I’m searching for “purses,” I probably haven’t yet decided on a brand or a style of purse and it could take me a lot longer to convert. When I search for “white Chanel purse,” though, you can be fairly certain I’m ready to buy. Focusing on phrases that are tailored to your product or service is what people really mean when they talk about “long tail keywords” [define] — and often it’s the difference between having visitors who are ready to learn and ones who are ready to buy.
Three
• Speak the customer’s language, not your own.
Sometimes, marketers get so focused on their own sales process that they convince themselves that would-be customers actually care about the words they use to describe their own products and services. When someone is searching for a solution to their problem, they enter search terms that sometimes don’t match up with what the company thinks people should be searching for.
Are you buying traffic for keywords that mean something to you but mean precious little to your customers? We’ve all done it before. Even brilliant marketers can assume that customers will think and behave as they do. This is what we like to call “Inside-the-Bottle Syndrome.” Although contagious, it is curable, but your web analytics reports alone can’t diagnose you.
Let us know if you’d like to optimize paid search from the customer’s perspective.
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Written by:Melissa Burdon
Using Funnel Reports to Boost Conversion
Funnel Reports are a good way to gain traction while competitors spin their wheels in muddy data.
Most web analytics programs give you the option to run a funnel report; a powerful tool, particularly for e-commerce sites, that shows where people are exiting the site’s sales process.
By analyzing the exit rate data in a funnel report, you can focus on optimizing the pages that need it most. First, look for areas with high exit rates. Then, once you have test pages selected, target specific elements to find improvements.
Ideally, your tests will boost conversion. But what if they fail?
If at first you don’t succeed, test, test again…
Here’s an analogy: If a visitor moves through your house (page-to-page) and reaches a locked door (a conversion barrier) for which they don’t have a key, they have no choice but to exit. You can test making changes to the door, but if you haven’t given them the key, your exit rate will remain high.
What’s the key? Confidence. If you haven’t given the visitor the information they need, you haven’t given them the confidence to move forward with the transaction. When the exit rate is high for a given page or step, chances are that you haven’t told the visitor something they were hoping to find out earlier in the buying process. So, it looks like they’re taking a step forward only to take a step back, when really they just didn’t have enough information to feel comfortable moving forward.
Elastic Path Software shows some examples of how funnel reports can be used effectively. Here are two more:
- The funnel report shows that the payment page, which follows a “Shipping Information” step in the checkout process, has a high exit rate. We test showing the visitor when they’ll receive the product before they hit the payment page. This lowers the exit rate for the payment page and boosts conversion.
- A funnel report shows that the shopping cart page has a high exit rate. We look at the previous step and find the product page isn’t telling customers whether their item is out of stock. Since visitors have to “add to cart” to get this information, we now have reason to believe that showing items as “in stock” or “out of stock” on the product page will lower exit rate, so we test it.
Since each site has its own unique characteristics, it’s best to think of our web analytics reports in terms of how they can help us empathize with visitors. What’s holding them back from converting? A funnel report can help you create a hypothesis and test to see what your visitors prefer. That’s how to optimize.Remember, it’s important to look beyond the page with the high exit rate. See what’s happening in previous steps. And if you’re still stumped, get an outside-the-funnel perspective.
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Written by:Ronald Patiro
Executives Run Out of Reasons to Fear Google Analytics
For some executives, it sounds crazy: Why should they entrust their business’s metrics to a free tool powered by the search engine that runs most of their pay-per-click ads?
To many others, though, the idea makes both dollars and sense. In fact, 60% of Fortune 100 businesses now use Google Analytics. And after recent updates to both product and privacy, even the skeptical minority are running out of reasons to fear it.
Here’s why…
Last week, Google Analytics released an industry benchmarking feature that allows you to weigh your site’s performance metrics against those of your industry at large. It looks like this:
This is a wonderful addition to the GA toolkit, so long as marketers don’t use it as an excuse to be lazy. (If your industry’s average conversion rate is 1.6% and your website converts at 2.3%, that doesn’t mean it’s time for Dom Pérignon. If you have a 70% bounce rate, knowing that the industry average is 72% won’t exactly calm your CFO’s nerves.) Still, it is nice to know.
Now, about those privacy concerns…
Although the Google Analytics team understated this in their announcement of the industry benchmarking feature, they also rolled out new privacy control settings, pictured here:
The incentive to (anonymously) share your data with the Google Analytics community it that it will help to make the industry benchmarking data more accurate and therefore more valuable. But what’s good to know here is that it’s “opt-in” — you don’t have to participate.
Perhaps this overt demonstration of privacy control will help to persuade executives who haven’t yet been willing to invest in web analytics to finally do so. Besides, it’s not like they used to give away your data unless you opted out. It’s just comforting to have the “Do not share” option.
According to the “benefits” page on the Google Analytics website,
Google takes the trust people place in us very seriously, and is pledged to safeguard the privacy of your corporate data. We understand that web analytics data is sensitive information, so we accord it the ironclad protection it deserves.
Don’t get me wrong. The hesitations on behalf of executives to adopt Google Analytics has been at least partially understandable. Having “don’t be evil” as their corporate mantra hasn’t exactly kept Google from being accused of rigging their own game. But…
Wouldn’t sacrificing your data be Googlecide?
During a panel discussion at SES London, Future Now’s Bryan Eisenberg discussed these issues with — among others — Brian Clifton of Google Analytics and Ian Thomas of Microsoft, whose forthcoming “Gatineau” analytics program is sure to encounter similar resistance.
In a post aptly titled “Trust me, I work for Microsoft,” Ian explains the awkward market conditions at play for these two supposedly gentle giants:
. . . Can we be trusted not to misuse the data entrusted to us for nefarious ends?
[Google’s Brian Clifton] was a little coy about this, insisting that for Google to misuse the data it gets from Google Analytics (for example, to manipulate bid pricing) would be tantamount to fraud, and so of course would be out of the question. I believe him, and believe the same of Microsoft too - it would be suicidal (not to mention morally reprehensible and howlingly naive) of Microsoft to take anything other than the greatest care with the data we collect from [Microsoft analytics tool] Gatineau. But - and let’s not beat about the bush here - this data is of value to us, and the benefit we get from it subsidizes the development of free tools like GA and Gatineau. And we need to be open and honest about that.
Where Brian and I differed on the panel was that I can all too easily believe that the general public will not be totally reassured by any insistence we make that we will look after their data and only use it responsibly. Maybe this is because I work for a company that - how can I put it? - doesn’t enjoy the highest levels of trust in the industry. For me, building trust in our stewardship of data is something that we have had to do day by day, brick by brick, but more importantly something that we will always need to continue to do - a garden that we will always need to tend, if you like.
It’s certainly not enough simply to stay inside the law and expect to maintain user trust simply because nothing bad (like a data leak) has happened on our watch. Even if we feel we are doing everything right, if we stop trying to build trust, it will wither away.
I know what you’re thinking. “Did he just suggest that nothing they ever say or do will convince the market that Google and Microsoft have good intentions with our data?”
Well, to tell you the truth, in all this excitement I kind of lost track myself. But being as this is Google, the most powerful company on the Web, and they could use your data against you in some nefarious, suicidal and illegal way, you’ve got to ask yourself a question: “Do I feel lucky?”
I’m feeling lucky. Are you?
. .
Want to outperform industry benchmarks? We can help.
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Written by:Robert Gorell
What Are You Measuring?
My good friend, Jim Sterne — producer of the eMetrics Marketing Optimization Summit and fellow co-founder of the Web Analytics Association — would like to know.
Please answer 9 questions in 5 minutes to complete this web analytics survey from eMetrics.
The survey is attempting to find out which channels marketers and analysts are measuring, how they’re using that data to optimize marketing, and their main objectives for marketing optimization this year.
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Written by:Bryan Eisenberg
Happy Web Analytics
Some people say web analytics is hard. Others try to keep web analytics simple. But at least one company is trying to reduce web analytics rage with a smile on its face.
Most web analytics use an invisible gif to track Web traffic, but WordPress uses a small smiley face gif on their pages (scroll to the bottom-left of WordPress.com). Some bloggers are surprised to see a smiley face in their blog themes, but it’s actually part of the WordPress stats plugin.
Other than the smiley face, what images have you seen being used for data collection?
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Written by:The Grok
Google Analytics Updates — Next Stop, “Event Tracking”
The Google Analytics team just announced some nice updates. Yes, the interface has been translated into Thai, Filipino, Indonesian, Czech, Hungarian, and Portuguese, but there’s another story happening between the lines about the switch from “urchin.js” javascript to the new “ga.js” standard, which doesn’t require tagging an entire Web page just to measure a single action. The big news is how the switch to ga.js javascript will change how Google Analytics users plan and optimize their online marketing.
The change in script reflects the fact that “page views” are dead (although some have replaced them with zombie metrics). Additionally, this round of GA updates makes it easier to track ecommerce transactions and see how metrics relate to each other. But you can’t see how visitor actions relate to each other — yet.
Now that visitor action can be called “events” and tracked with ga.js tags, it’s going to be much easier for GA users to see how a series of actions tie together. Fortunately, Google has built an “event tracking” interface to help you take advantage of the more robust ga.js script. For now, it’s in closed beta, but when it launches, the reports will look something like this:
The challenge for marketers, analytics specialists, and anyone who’s a little of both — either by training or necessity — is to realize that standardized metrics aren’t enough. Event Tracking isn’t about measuring how many times visitors complete one-off actions. (If you do only that, the feature will be, in most cases, meaningless — or “cool,” which can be even more misleading.) Nope. Event Tracking is about measuring scenarios.
Since it’s designed to help you measure the relationships between actions and content, the to-be-launched Event Tracking interface should encourage GA users to do a better job of planing the visitor experience and to not be content with the same old generic data.
Looks like 2008 will be good year to be in the scenario planning and optimization business! 
[Image credit: Marketing Pilgrim. If you’d like to learn more about how to use the latest version of Google Analytics, these updates aside, Avinash has you covered. To read more about the use the most recent updates, see WebProNews and ProBlogger.]
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Written by:Robert Gorell
Web Analytics Association 2008 Industry Survey
This just in from the WAA:
Help uncover the future of the web analytics industry while gaining valuable insight at the same time. It’s easy. Answer the questions in this groundbreaking survey: Web Analytics Association Survey: Outlook 2008. We’ll send you an invitation to the results webcast in January 2008, and provide you with a complimentary survey report.
How are other organizations like yours using web analytics as a function in their business? What are the pressing issues, and the top concerns? Now is your chance to find out answers to these questions and more!
So take part in this unique survey for the industry by the industry. It will take just a few minutes of your time, and it just might give you the answers you need to make more informed decisions in the coming year.
If you’d like to see the analytics industry shape up for the new year, don’t be shy, take the survey!
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Written by:The Grok
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
Unlocking Key Performance Indicators: Order Acquisition Ratio
Now that we’ve taken a look at Take Rate and Bounce Rate, it’s time to look at another very important metric: Order Acquisition Ratio. Simply put, this performance indicator is used to measure the effectiveness of your marketing.You’ll need three numbers to calculate your order acquisition ratio:
1.) Visits to your site
2.) Number of orders placed
3.) Total marketing expenditures (which can include fixed costs associated with maintaining the site, but let’s focus primarily on marketing expenses)*
With these variables in mind, we will get two contributing metrics with which to calculate order acquisition ratio.
Cost per Visit (CPV) = Marketing Expense / Visits
CPV measures how much you’re paying to attract each single visit to your site.
Cost per Order (CPO) = Marketing Expense / Number of Orders.
CPO tells you how much you’re paying in terms of marketing budget to get a visitor to your site who converts and becomes a customer. This is directly related to your Conversion Rate.
Order acquisition ratio is then calculated by taking the CPO and dividing it by the CPV.
Order Acquisition Ratio = (Marketing Expense/Number of Orders) / (Marketing Expense/Visits)
It should be a positive number (if not, you’re in trouble). The lower the ratio, the better your marketing budget is being used. Some of the best ways to lower OAR include:
- Boosting conversion! Increasing conversion lowers your CPO. Since conversion is the website’s primary goal, there are literally thousands of factors that affect conversion. (Conversion is so important to online health and wellness that improving is integral to everything we do for clients.)
- Improving organic search rankings with relevant content. When you spend the time and money to create relevant content, the CPV and CPO should both drop — and you’ll further lower CPO by converting more visitors.
- Targeting quality traffic sources. In your analytics, segment your site’s incoming traffic by source in order to identify where to put those marketing dollars. (Bounce Rate is a great starting point for this.)
- Optimizing PPC campaigns. With an effective PPC campaign, you’ll be able to convert more visitors. While this will increase your CPV, but when done correctly, it will yield a larger decrease in CPO by converting a higher percentage of traffic.**
Order Acquisition Ratio is based on more traditional bored boardroom metrics because it has a close relation to traditional financial statements. It has nothing to do with “Web 2.0,” “Web 1.0,” or Facebook. So, it’s great for sharing with your boss since it’s directly tied to the bottom line. There’s even a cousin to this metric; a non-ratio, cold-hard-cash version of the Order Acquisition Ratio known as the Order Acquisition Gap. To calculate it, simply subtract the CPO from the CPV to get a negative number. This number shows how much money you waste in marketing dollars on visitors that don’t convert.
Order Acquisition Gap = CPV - CPO
There are other close relatives in this family of metrics, all of which focus on costs associated with generating new customers. To calculate these similar metrics, you’ll need to be able to track the same figures discussed above — except they need to be further segmented. Track the following numbers, and you’ll also benefit from a few additional metrics (listed in the bullet points below):
- New visitors to the site.
- Number of orders placed by new customers.
- Total new customer marketing expenditures.
With these figures you can see the effectiveness of your new customer acquisition efforts:
- Customer Acquisition Cost = (New Customer Marketing Expense) / (Total New Customer Orders)
- New Customer Cost per Visit = (New Customer Marketing Expense) / (New Customer Visits)
- Customer Acquisition Gap = (New Customer Marketing Expense/New Customer Visits) - (New Customer Marketing Expense/Total New Customer Orders)
- Customer Acquisition Ratio = (New Customer Marketing Expense/Total New Customer Orders) / (New Customer Marketing Expense/New Customer Visits)
[*Regardless of the expenses you include, it’s crucial to set a standard and stick with it in order to accurately measure and account for the specific impact of such changes.]
[**When monitering your order acquisition ration, never tolerate any increase in the cost per visitor without an accompanying decrease in cost per order.]
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Written by:Ronald Patiro
