Posts Tagged ‘Digital Analysis’
I am getting most of my research done now while I rock the baby to sleep every night. He’s not much of a sleeper so I am getting a LOT of work done.
Last night something in particular jumped out at me that could be the mostinteresting piece of industry news I have read all year. Eric Peterson of WebAnalyticsDemystified is working with the Web Analytics Association to build a web analyst ‘code of ethics’, so that we as an industry can take a stand on how we want to deal with the terabytes of personal information that we work through every day.
(As an aside, it’s great to see WA Demystified and the WAA working together on such an important issue. Based on the twitterblogosphere there have been some WestSideStoryesque Sharks-Jets moments in the past….)
Mr. Peterson has written a great first shot on goal at a code that all analysts can use and buy into – and our respective stakeholders (Both bosses and site visitors) will be able to read to better understand and trust our work. I am sure that this code will evolve over the coming months and the Napkyn team is both looking at them and planning to adopt them, but this blog isn’t to talk about things that I feel need to be changed. I would like to contribute by explaining why this code is awesome.
Now a code of Ethics isn’t a set of rules, they are a set of guidelines. If someone decides to do something sketchy with personal data, there won’t be a WAA SWAT team at their cube the next day. So why am I excited about it? The key points are below.
Managing Web Analytics is about managing limitations
Web Analytics, while still very much an emerging discipline, is constantly under intense scrutiny by its practitioners. Not surprising, since the entire goal of the space is about clear understanding and continuous improvement.
In the early 90s, web analytics was not a marketing activity. Rather it was about technical performance of the website, and the reports were generated from logs and owned by the same guys and girls who keep the server room running. At some point in the mid 90’s, Marketing realized that they could use that data to understand the business impact of the website and a discipline was born. This was the golden age of WebTrends, the first marketer facing web analytics tool.
Because of the fact that this software was built by IT, the unit of measurement was around hits, or individual calls to the web server. 10 images on a page would be 10 hits. Not the richest data for business analysis. An analyst could discover which elements of a site got the most ‘hits’ but could not tie them to types of visitors or business goals in such a way that they could affect change.
In the late 90’s new vendors like Omniture, Coremetrics and WebSideStory entered the analytics space (as well as Urchin, DeepMetrix and IndexTools, which would later become Google, Microsoft and Yahoo Analytics). These vendors built products around marketer requirements rather than IT, and this gave rise to both page tagging (removing the main limitations of log analysis), and richer reports designed for Marketers.
This period from 1997-2000 (when the first dotcom bubble burst) was the first big vendor gold rush in digital marketing. Many of the bigger companies (and lots of the failed ones) in digital marketing were founded in this period (think Akamai, Offermatica, Lyris, ATG etc.).
The limitations of these types of analytics tools and vendors are significant:
Tracking the Visit and not the Visitor: While tracking visits is a lot better than a server call, it is still not the best base unit for measurement. No one sells to a visit they sell to a visitor, and a lot of high value information is left on the table because of the lack of this kind of tracking. Want to know how many visitors to your site created an account and then came back later to buy? Forget it.
No sharing of data: Each product has it’s own proprietary reports, data capture and data naming conventions. This means that it was impossible to create a decent report on a full set of digital marketing campaigns. This taught most digital marketers to treat each use of a product as a ‘campaign’, and analyze each campaign as a standalone. This explains why offline marketers will think of a marketing campaign as a multi-message, multi-medium program (think TV ads, radio ads, sponsorships), and online marketers will think of a campaign as a single activity (think one email newsletter, one personalized ad, one coupon code).
Last week, I finished up presenting our Napkyn Analyst Program report to my clients. Working with a number of clients’ web analytics data and then going through the data, insights, and recommendations with them is an amazing process – it reveals something new about the nature of the web and website visitors each month.
Some of these pages are so deep, you'll need a shovel. Or a search engine.
For a particular client this month, I attempted to chart (or graph, depending on your persuasion) traffic by medium, top landing pages, second-click pages, and then transaction or conversion… and the chart landed up looking overly complicated. I didn’t present it to the client, but the research behind this messy chart was invaluable.
Through a maze of arrows, boxes, and pie charts, one realization came to the fore: Every page is a landing page. For web analysts, this might not be a grand revelation, but some small or medium-sized online business owners, it’s not said often enough.
Here are 3 steps to improve conversion and serve your deep landing page visitors better.
We had a great time at the Internet Retailer conference in Chicago last week. It’s always great to get some face-time with our
Can conversion rates grow at the same rate?
customers and partners, look at new business opportunities, and see what kinds of technologies are coming down the pipe.
There were over 500 exhibitors this year at IRCE, and apart from some interesting new tech, the thing that really resonated with me was that the standard boilerplate one liners hadn’t changed when it comes to technology impact.
“We will double your eCommerce conversion rates”
“Every campaign you run with us will improve conversion rates”
“We will let you take control of your conversion rate”
Et cetera, et cetera…
When I was on the vendor side 6 years ago, we were using the same pitch, and it is both as effective and as untrue now as it was then.
I have been stewing all week over a great blog post I read by Evan LaPointe, a digital marketer out of Atlanta. The post was entitled “I don’t want an analytics job”, and it seems to carry over the same feelings and themes of an earlier post he wrote called “Web Analytics Sucks, and it’s nobody’s fault.”
These posts both excited and annoyed me at the same time.
On one hand, it was almost liberating to read that someone is living in the same trenches that we are at Napkyn. A lot of the points of frustration that Evan talks about – like navigating both internal politics and sub-par data as well as having the role of web analyst considered a low-level technical job rather than a high level executive job – hearing someone else say this stuff will make any analyst grin and buy in. It’s like reading a good Dilbert cartoon and thinking “Hey, that is SO where I work!” – it’s cathartic, but not productive.
Hence my annoyance. Evan touches on all the challenges with being an analyst, and outlines all the skills (data analysis) and opinions (Always Be Testing) that good analysts bring to the table. But his conclusion is that good web analysts don’t actually want to be web analysts, they just represent the next generation of executives-in-waiting – web analysis is beneath them. He says that web analytics actually want to be the ‘shepherds’ of a business, who use data to help guide the organization to ongoing successes. There’s already a job title for that – it’s a CIO.
So while I totally agree with the sentiments, I thought I would share my thoughts on what the real issue is.
Being a Web Analyst is hard.
I don’t want to reopen the whole “Web Analytics is Easy/Hard” debate, but I do want to agree with and elaborate on Evan’s key points.
Most organizations aren’t ready for information based decision-making, and while many firms know that analysis brings results, they do assume that an analyst will generate a ‘magic report’ rather than help move the business forward over time. This is frustrating, and it takes a lot of patience, diligence, and small wins to earn the right to change this perception. With every client we work with, this process takes time, and it always pays off.
Very few tools play well together in the digital sandbox. In a lot of cases, it would be easier if certain kinds of technology didn’t exist – their standalong datasets add zero value unless a ton of work is thrown at them to make them align with corporate data (pay for performance vendors and dynamic CMS systems come to mind immediately here). It’s awfully hard to internally sell the value of analysis if you spend half your time talking about what you can’t see clearly because of technology/disparate data issues. Tools vendors make analysts look bad.
I don’t think that most web analytics practitioners secretly wish they were a CIO. A lot of us live for that ‘eureka’ moment that happens when you uncover amazing insight about the business, or implement a small change that immediately creates a big impact. There’s a big difference between someone who love continuous improvement and someone who wants to run the whole business.
Just because it is hard to be a web analyst right now doesn’t mean that it will be forever. As more of us start to organically change the culture of the organizations we are in, performance management and analysis will start to trump “I think, I feel, I want” and we will get better seats at the table. These information oriented organizations will refuse to accept the vendor data shenanigans and we will get better and easier visibility into the entirety of the digital data.
I for one, love having my web analytics job. It’s not always easy, but panning for gold in the digital wild west has a lot of payoffs that make the frustration worth the while.
P.S. Evan, keep up the great writing and if you ever decide to move to Ottawa I have a job for you – we can work together to come up with the right title
We’re in the thick of working on our monthly digital analysis reports
here at Napykn. At this point, we’re bringing together ideas developed from last month’s reports, looking at the most recent month’s data and refining our techniques based on our readings from numerous online sources.
Recently, we’ve been working with a few catalog-based companies who are increasingly shifting their focus into online sales. One proven segmenting technique that we’ve been recommending to these clients is to register alternate domain names and direct their catalog-based traffic to these domains.
It’s not a new idea. Anyone with a cursory knowledge of landing page optimization will tell you to register a particular domain name in order to draw in a particular group of visitors. But in the case of catalogers, we’re using it to segment their traffic into two sources:
- Visitors who use the website to make orders based on the catalog, and;
- Visitors who found the website through other means (organic or paid search, referring sites, etc.)
For example, a catalog company with the domain redfiretrucks.com also distributes a catalog. In the catalog itself, suggest to readers that they visit redfiretruckscatalog.com (and then it can be as simple as just redirecting the traffic – or you can do more interesting things with behavioral targeting). This way, we will know which website visitors have read the catalog, and which visitors are a product of the company’s online marketing efforts.
For $10-$15 per year, registering an additional domain name is a small investment to help give some order to the chaos of your online traffic.
The role of the Digital Analyst
is becoming central to the digital marketing roster in any organization with a growth strategy today. This statement holds true for any and all sorts of companies of all sizes and shapes, but is particularly salient for B2C transactional businesses – eCommerce shops in particular.
Ad-hoc reporting is no longer considered satisfactory. To truly understand the impact of all of the pressure being applied digitally (Traffic generation, email marketing, performance marketing, etc.) businesses require holistic, standardized internal reports that speak to individual initiatives, as well as the cross-discipline impact of each initiative.
I am going to stop my self here, as the Analyst’s workload and responsibilities are not the focus of this post. I wanted to talk a little bit about the status of today’s rock-star hires in eCommerce circles.
Just yesterday, almost every post on the front page of the IR site was about someone’s new gig. Gilt Groupe, Shutterfly, Deckers Outdoor, and Hancock Fabrics all brought top talent into their organizations reciently. Even though I know none of these people, each one of these hires inspires me to fist pump in the air.
You see, our industry has matured to a point where hires like these are justified. Gone are the days where you hired someone and hoped they could move the needles – folks are out there who have done it multiple times over. Hire someone today who you know can have an impact.
It’s exciting for us here at Napkyn to work in lockstep with some of our customers. In fact, our work as a trusted virtual employee is creating the exact internal scrutiny described above. Working with digital analysts like Napkyn can help accelerate initiatives, and careers – it’s the way online business is moving, and top retailers are taking notice.
One of the most common recommendations that Napkyn makes to our clients is to properly tag emails so that they can be tracked in Google Analytics. The key to actionable and insightful digital analysis is clean data that properly represents an online business – and tracking email sendouts is a pretty simple way of cleaning up your data.
How do we set up email tracking?
Unless you’re lucky enough to use one of these fine email marketing services with automatic Google Analytics integration, you’ll have to set up email tracking manually with a bit of coding.
First of all, let’s stop thinking in terms of email tracking and start thinking ‘link’ or ‘URL tagging’. That’s the key. Your emails contain links back to your website, and if you want to monitor the impact of your email sendouts, you have to add tags to all your links. Tags are short additions to the URL that tell Google Analytics how to categorize traffic.
But not to worry, it’s actually pretty simple.
Let’s get started!
Great! A little effort now will make your data much more valuable in the near future. Let’s use the Contact Us button on the upper right-hand corner of this blog as an example. It really doesn’t matter if you’re tagging a link in an email, on a blog, or on a website.
It links back to:
But I wanted all the traffic that was sent to napkyn.com using that button to be noted that it was coming from this blog and from that button. So I added some tags to the URL – this will not interfere with sending traffic to the right page, it just labels it. Now the button links to:
You can plainly see how I wanted the traffic labeled.
Source = ‘contact_button’
Medium = ‘blog’
Campaign = ’04152010′ (The date the button was placed on the blog)
Now, when I look at the Napkyn.com Google Analytics account, I can see that the source and medium have been labeled as we intended.
For an email, you may want to label your traffic differently than I’ve done here. For example…
Source = ‘newsletter’
Medium = ‘email’
Campaign = ‘fall’
You can use the Google URL Builder or the excellent tool from Cutroni.com to make this process easier.
Of course, there’s a lot more to digital analysis than proper link tagging. So give that wonderfully tagged Contact Us button a click, check out napkyn.com, or leave a question in the comments.
Imagine that you walked into a store and told a salesperson that you want to buy a blender. The salesperson walks into the store room, grabs one off the shelf, comes back and puts it in your hands. “You want it or not?” he says. “Not this one exactly,” you say. He walks away and returns with another blender. “What about this one?”
Any customer would grow tired of this exercise pretty quickly. Online, it’s no exception. Guiding your online customer to the right product and allowing them to browse for a moment before the sale creates a more pleasurable buying experience and will increase conversion rates.
Occasionally, because of various responsibilities, both clients and digital analysts can forget about this very basic premise. Buying online is a process, and walking with your customer through your online store using digital analysis can be a revealing exercise. With Analytics, we can walk with our customers and map the most common paths to a purchase.
We’re talking about visitors with ‘mid-range intent’ – people who know what type of thing they want, but not a specific product yet. Depending on your business and products, these ‘browsing’ customers may make up a large portion of your traffic. (For more information, see Kaushik’s article on customer intent.)
Unless you’re Woot.com, or have a one-time special offer, there should be no hurry to get these types of visitors to the product page. If you shove a product in front of their faces and ask “This one?” too quickly, the customer may choose to leave. This is especially true if your online store is difficult to navigate.
This is where well-designed product category pages can be a boon to your online business.
Not only do product category pages allow customers to browse among the products they’re interested in buying, and compare features and prices, they can also be used to answer FAQs and build confidence in your company. Product category pages can serve as the intermediary where many important buying concerns are allayed.
You can consider this the opposite of sentinel pages. Sentinel pages are meant to act as filters, redirecting visitors who have no business on a particular website. Category pages should funnel pre-qualified visitors (people who have arrived through a search engine, or clicked on a category link) toward their intended product – even if they don’t know exactly what it is yet.
You can also use category pages so that potential buyers are educated as they click through to their ideal product. With every click, they learn a bit more about your business. For example: free shipping, return policy, email campaigns. These bits of information can build customer confidence while they browse.
While highly targeted landing pages are an effective way of attracting and converting customers who know exactly what they want, digital analysts know there’s a ton of traffic that goes through index pages in any case, and still has to be qualified.
Presenting a variety of products with a range of prices and features means your customer doesn’t have to go searching elsewhere to find what they want. Don’t narrow these customers’ view right from the start, or they may go look elsewhere.
All too often, when it comes to online businesses, we tend to simply go with our gut feeling. Will a video on the homepage increase bounce rate? What sort of discount will result in the most sales?
Most online business owners and managers just don’t have the time or mental energy to perform the tasks required to determine these best practices. Well, a blog post by the Harvard Business Review has some harsh words for business owners who just shoot from the hip: There’s a much better way of doing business.
Andrew McAfee states that while there are some cases where human intuition has become a useful tool, in modern business, there’s no reason to ignore data and critical analysis.
Overall, we get inferior decisions and outcomes in crucial situations when we rely on human judgment and intuition instead of on hard, cold, boring data and math. This may be an uncomfortable conclusion, especially for today’s intuitive experts, but so what? I can’t think of a good reason for putting their interests over the interests of patients, customers, shareholders, and others affected by their judgments.
However, if talk of statistical analysis makes you think of punch cards and supercomputers, you’re way off track. There are a plethora of (sometimes free!) online tools that can help online business owners and managers make the best decisions based on real data, generated by your website visitors and customers.
Of course, here at Napkyn, we help business owners and managers make sense of this data using digital analysis. Quite often, we find underserved segments and opportunities for conversion that intuition and guess work would never have stumbled upon.
So you don’t have to trust your gut anymore–unless you’re thinking about lunch, of course.