Future of the Web Analyst

Tomorrow’s web analysts will look very different from today’s.

Being a web analyst today usually means being lonely. Most companies don’t hire full-time analysts to work onsite. They hire consulting agencies or they hire a web analyst and make them do SEM work on the side (or vice versa). In the few companies that do hire a full-time analyst, that person ends up being by themselves. That means being lumped into an existing organization that doesn’t make sense (IT, marketing, new media, etc.) and needing to defend analysis and recommendations alone. [Read more…]

Web Analytics Careers: 4 Great Blog Resources

Career chat has always interested me.  When I was a new college grad I spent a fair amount of time in my alma mater’s career services office, getting advice as I prepared to make a start for myself.  I’m glad I did it.  The career counselors liked me enough to use my resume as an example for other new grads, and I managed to land an internship at a multimedia CD-ROM publishing company (which, back in 1995, was so totally cutting edge).

After more than a decade out in the workforce I feel like I’ve learned a great deal about my strengths, preferences and motivations when it comes to my career.  But I also know that career planning didn’t end when I left my college campus – it’s something I must always keep in the back of my mind.  I like hearing about how my peers are handling their own career choices, and I think it’s a productive thing for us to talk about with each other.

So I’m planning to write about career-related topics, now and then, in this blog.  Before I get started I’d like to acknowledge 4 fellow bloggers who’ve already written some great web analytics career-related material:

  1. Alex L. Cohen
    I appreciate Alex’s enthusiasm – right now he’s doing an interactive marketing tip-a-day for the entire month of November [really, Alex, even on Thanksgiving?].  Occasionally he writes about career-related issues, including this piece on how to write a good web analytics resume.
  2. Stephane Hamel
    As Stephane was contemplating his own impending career move he wrote this very compelling post on the importance of doing regular career self-evaluations.  I liked it so much I wound up using it in my presentation on career management at eMetrics.  Neither Stephane nor I can fly a kite too well, but luckily that’s not a requirement for our line of work.
  3. Avinash Kaushik
    Oh, what’s not to love.  I wouldn’t say Avinash has written about careers, though, so much as he’s written about the flip side of the coin – hiring.  I thought this post about whether to hire fresh blood or old hands was especially good, and you can see from the comments that many of his readers turned it around and talked about the issue from the job candidate’s perspective.
  4. Anil Batra
    Anil has compiled a whole collection of interviews with web analysts; as of this writing he’s accumulated 32 career-related posts.  I’ve really enjoyed reading the interviews – just to get a sense of who “we” are – but I think they could be equally valuable to someone who’s contemplating an entry into web analytics.

Read what these fine gentlemen have to say, and read my blog, too.  I think there’s still more we can and should talk about when it comes to careers in web analytics, and I aim to be a part of that conversation.

Originally posted at: http://june.typepad.com/june/2007/11/web-analytics-c.html

Targeting Cart Abandonment by Email

A while ago I read an article called Four Ways to Improve Marketing ROI Through E-mail by John Rizzi, CEO of e-dialog. This is a good article for those who are trying to determine how to collect email, learn from email marking and email effectively. In his last point he says “Use Behavioral Targeting” to convert abandoned carts. He suggests using incentives to bring customers back to complete the cart they had abandoned. This is a great idea but I want you to be aware of following two issues before you jump into it.

  1. Lack of Email Address: If you don’t have an upfront email collection process it is very likely that visitors (customers) will leave even before they give you their email address. If that’s the case then you won’t have any email to target (You can still deploy anonymous on-site behavioral targeting. Check out my article on behavioral targeting).
    If you decide to put email collection up front it might cause cart abandonment rate to go up. You have to provide a very good reason to your customers on why they should provide you email even before they started buying anything or checking out. Like any other change on the site, I suggest conducting A/B testing before you start collecting email addresses for all your customers. If the tests do not show desired result you might be better off with on-site anonymous behavioral targeting.
  2. Backfiring of incentives: Let’s assume you have the email address and are ready to send an email incentive. As you already know the word spreads very fast these days. Most of your customers (visitors) will find out about your offers which could ultimately result in two outcomes:
    • If the incentive is not too enticing (such as free shipping) your customers (even regular customers) might find out about it and start abandoning the cart in anticipation of receiving that offer or they might just use the coupon or offer code given to them by somebody on the internet.
    • If the incentive is too good (such as $10 free for any purchase over $5.00, not sure why would you do that but I have seen companies giving free money just to get users to signup), the word will spread sending new customers to your site. So be prepared to handle the amount of traffic this viral marketing will generate and a possible bankruptcy.
      Appendix A shows what happened to Starbucks when they sent out an e-coupon to limited number of employees (or that’s what Starbucks thought).

So should you provide incentives to bring back customers who have abandoned carts? Yes I think so but think about all the pros and cons before you jump into it. Below are some of the steps that you should include into your process for using email incentives

  1. Select a sample (say 20%) of visitors, who abandoned the shopping cart, who will receive any offer (I am assuming you have already created and tested a process for upfront email collection).
  2. Test different offers within this selected group. Testing will show you which offer works and which ones don’t.
  3. You can use more behavioral data (and I encourage you to do so) to determine what offer will make sense to which visitor segments (create few manageable segments so that you can stay focused). E.g. A customer who abandoned at shipping step might be more interested in free shipping than a user who added products to the cart but then left without clicking on the final checkout button (provided the customer has given you the email address), a 10% off coupon might be a better offer for this customer.
  4. Unless you purposely want to engage in viral marketing, make sure coupons and codes can only be used by those for whom they were intended for and for specific period only. Also don’t forget to configure your web analytics tools properly so that you can measure effectiveness of these offers.

Note: If you provide users the same kind of incentives 2-3 times to a customer then he/she (most of them) expects it every time.

Appendix A: Starbucks Lawsuit
“Starbucks e-mailed the grande iced beverage freebie to a limited number of employees in the Southeast on Aug. 23, with instructions to pass it on to friends and family.
The forwarding turned into a frenzy as the coupon landed in thousands of inboxes and on Internet message boards – forcing the chain to reject scores of coupon-touting java lovers pouring into stores for the perk.” Source: ocregister.com

Originally Posted at : Targeting Cart Abandonment by Email – Web Analytics, Behavioral Targeting and Optimization by Anil Batra

What is Behavioral Targeting?

Behavioral Targeting (BT) is the ability to target users based on their behavior on the internet. Most commonly it used to target online ads but the technique can be very well used to target products and content.

Behavioral (Ad) Targeting promises to precisely target the audience that matter most. Hit the users with the right message, a message that they care about. It is all about audience.

How Behavioral Targeting work?

Users are segmented based on the content they view or actions they take on a site(s) and then are targeted with a message (ad) relevant to that segment.

There are two ways behavioral targeting has been deployed

  1. On-Site Targeting
  2. Network Targeting

On-Site Targeting:

The user are segmented based on content views or actions on one site and then are targeted on the site itself.
For example: Users who view 5 or more pages related to auto and view online interest rates page they can be classified as “In Market Auto Buyer”**. Once classified these users can be then targeted with messages from those advertisers who want to reach “In Market Auto Buyers”.

Network Targeting:

The user are segmented based on content views or actions on one site (usually advertisers) and then are targeted where ever they go on sites participating in the behavioral ad network.
For Example: A user views pages 5 or more related to Alaska tours on a travel site, this and then leaves the site without buying. This user is segmented as “Alaska Tour Buyer”**. A very valuable segment for the travel site. This travel site can then tap into the network and share their segment (based on cookie – more on this later) with others in the network and then target them with relevant message to bring them back to the site and convert the sale.

**(How users are segment and what they are called is totally dependent on how marketer wants to define their segment. There is no industry standard, however every now and then I have seen push for creating industry standard way of creating these segment. In my opinion it is too hard to create standards for creating segment as it totally depends on each individual business).

Originally posted at : Behavioral Targeting 101 – Web Analytics, Behavioral Targeting and Optimization by Anil Batra

Who moved my traffic?

Your site traffic is down, you are running up and down the hallway freaking out.  Wait before you get all anxious about the traffic, downturn in your traffic might not be something to freak out.
Below are some of the things to look at to find out why your traffic is down. Some reasons are within you control (stop freaking start working) some out of your control. Some might be very obvious and some might not.

  •  Seasonal Impact – Do year over year comparison and see how the traffic pattern was last year.
  • May be overall traffic is down even for your competitors (do comparison at http://www.alexaholic.com/ )
  • Has a new competitor entered the space? How is their traffic?
  • Traffic drivers – How was the traffic from these sources?
    • Campaigns (Banners, Search, Emails) – Has anything changed.
    • Email – Did anything change there? Did you send out your regular emails, newsletters?
    • Search – Did you change anything here, have search engines changed their algorithm.
    • Search – Did you change your site? Meta Tags? Content?
    • Affiliates – Has any affiliates changed their site.
  • Environmental Factors – How is the weather in the geographical region where you have most visitors from? Nice weather can keep people outdoors, resulting in lower traffic.
  • Was there any site outage
  • Have you made change to your web analytics tool configuration? If yes, investigate what those were? Problems in filter could be filtering out a lot of traffic.

This was originally written in 2006 at – Web Analytics, Behavioral Targeting and Optimization by Anil Batra

Online KPIs – Back to Basics

Those who have been doing web analytics for a while know how important it is to define proper online Key Performance Indicators (KPIs). But believe me, there are a lot of marketers who are confused about online KPIs, difference between KPIs and metrics and how to define them. So I am going back to basics with this post.

What are KPIs

Web analytics tools collect a lot of data and provide a lot of metrics and reports. In fact most of the web analytics tool vendors proudly talk about number of reports that can be created in their tool. These reports, metrics and data might look interesting but we all know interesting is not necessarily important. KPIs, on the other hand, are the important metrics; the metrics that provide a view into the health of the business and are tied to the business goals. They allow business owners to focus on the things that are important to drive their business. Key Performance Indicators tell a business owner whether he or she is meeting their business goals or not. Good KPIs provide context and hence are usually represented as ratio, percentage, indexes etc and not as raw numbers. KPIs drive actions within an organization.

KPIs are specific to a business role. So, not all people in the organization have the same KPIs though all the KPIs should ultimately be tied to overall business goals. The CEO has a set of KPIs, a merchandising manager has a set of KPIs and a marketing manager has yet another set of KPIs. However, all of the respective executives (departments) need to be defined keeping overall business goals and CEO’s KPIs in mind.

Another way to understand KPIs is that they are the metrics that make people freak out when they go in the reverse direction from the expected and call for immediate actions.

Since so much is riding on the KPIs, it is very critical that you pay due attention in defining your KPIs. Understand what business goals are and then think about what activities and/or user behaviors relate to your business goals. Put together a list of all the metrics that will measure those activities and/or user behaviors. Weed out the unimportant metrics, figure out what are important metrics and what are critical few (and hence KPIs) that have an impact on the business goals. Note: For your analysis you will need to look at more than your KPIs to provide you a bigger picture. Remember, all KPIs are metrics but not all metrics are KPIs

Characteristics of KPIs

Dennis Dennis R. Mortensen lists following 7 KPI characteristics on his blog “Visual Revenue”

    1. a KPI echoes organizational goals
    1. a KPI is decided by management
    1. a KPI provides context
    1. KPI creates meaning on all organizational levels
    1. a KPI is based on legitimate data6. a KPI is easy to understand
    1. a KPI leads to action!

Those are all great characteristics of KPIs. I however differ a little on point number 2. In my opinion great KPIs are those that are agreed upon by those it directly impact and will be taking actions so they are not just handed down by the upper management. And as I said above they should all be tied to overall business goals.

How many KPIs should you have?

I don’t think there is any rule but in my experience you should limit it to no more than 6.

Reporting on KPIs

KPIs should be presented in an easy to consume dashboard. Web Analytics tools have built in dashboards but most of them are limited in terms of the functionality and flexibility. My recommendation is to present KPIs in a separate dashboard that not only shows KPIs but also trending and brief analysis. Without trending and analysis the KPIs might not provide a complete picture. Excel, PowerPoint or third party dashboard tools work the best for reporting the KPIs. Since they are outside the web analytics tool they also allow you to integrate other data sources, as needed.

Books on Web KPIs

Eric Peterson has a great book on the subject, called The Big Book of KPIs

Originally Posted on Web Analytics, Behavioral Targeting and Optimization by Anil Batra

How to grow your web analytics skills (within your current role)

If you are an analyst looking to further develop your skills, what can you do (within your current role) to further grow and develop? Here are a few of my thoughts, though I am certain there are many others.

In no particular order …

1. Interact with others in the industry

  • Join Twitter, follow your web analytics peers. Twitter can be an amazing educational resource if you use it for something other than “I ate a ham sandwich today.” You get to hear about the challenges that analysts working with different business models or analytics tools face, what is going on in the industry, what the vendors are saying and perhaps new functionality they’re releasing.
  • But more importantly than reading what others say on Twitter: contribute. Voicing your views will force you to think them through. And everyone disagreeing with you (it will happen one day!) will be a great learning experience to see those other viewpoints.
  • Go to Web Analytics Wednesdays
  • Take the time to go to lunch/happy hour/etc with your peers within your company and “geek out”. While you may work in the same company, your responsibilities and experiences may still differ, and you can learn from the experiences, thoughts and views of others.

2. Take advantage of free learning opportunities

  • Attend free webinars. There are so many out there (you’ll find out about them through Twitter, blogs etc) and they can be a great resource
  • Attend free trainings (yes, they do exist. I can’t tell you how many emails I get from MicroStrategy about free one-day trainings.)

3. Attend conferences

  • This one can be tougher if your employer doesn’t support this. However, make an argument for why it is of benefit to the business. Trust me, the vendors give you plenty of information about how to sell their conference to your company!
  • If you can swing the cost, you do have the option to pay for it without your company’s support (or “financial assistance”) …!

4. Volunteer

  • Join the Analysis Exchange, a program that brings web analytics students, mentors and non-profit organisations together, to give more web analytics experience to the student and analytics assistance to the organisation.
  • Know a friend/family member/co-worker with their own site? Blog? Small business site? Volunteer your time to help them set up a free web analytics solution, and take time out of your schedule to analyse their site on a regular basis. Don’t know anyone? Why not start your own site? It doesn’t have to be big. It also doesn’t have to be about web analytics. But it will certainly give you a taste of analysing a different type of site, as well as some of the challenges of getting traffic!
  • Volunteer to work on things outside the scope of your standard role within your company. Is there a project out there that you think analytics could help with, but no one is asking for help? Volunteer it!

5. Read
6. Read
7. And then read some more

  • There are a lot of great books out there. Start with one. (A hint: If this sounds completely dull to you, and you can’t imagine anything worse than reading about analytics in your spare time, really take a look at whether you are in the right field …)
  • Read both corporate blogs (e.g. web analytics vendors: Omniture, Google Analytics, etc) and those of your peers
  • Ask your peers for their recommendations of books, blogs, journals, magazines, articles, etc
  • But don’t stop just at web analytics books. Start reading about related fields. Product development. Design. Usability. Marketing. Social media. Statistics. Even cognitive psychology!

8. Keep your eyes open to what employers are hiring for

  • Sure, maybe you’re happy where you are at your current company. Maybe you don’t feel you’ve extracted all the learnings you can from your current role. (That’s a great position to be in!) But keep your eyes open for what positions are out there.
  • Why? Seeing what employers want will allow you to keep a mental checklist of what skills you need to improve on, prior to your next promotion or job change. Better yet, think about what you want your next move to be, and monitor the companies that are hiring for that type of role. What are the requirements and responsibilities they have for it? This ensures you’re working towards filling those requirements in the future. You can’t grow into a position if you don’t even understand what it involves!

What other advice would you give?

[Originally published at MicheleHinojosa.com]

Top 10 Things I Wish I Knew When I Started in Web Analytics

I remember what it was like to walk through the door at my brand new job, my very first job as a web analyst, wondering what I’d gotten myself into. In retrospect, what did I wind up learning the hard way? What would been helpful to know up front? What should I have been prepared to expect? With that in mind, here are 10 things I wish I knew when I started in web analytics:

  1. You will sit between the techies and the marketers. Figuratively, and maybe literally. Make friends on both sides of the fence.
  2. You will learn all about your business. Not just the stats part. Not just the web part. The work you do in web analytics will only make sense once you’ve put it in the general context of your business.
  3. Ahem, what is this thing you call a “Visit”? Know your standard web metric definitions by heart, and be able to recite them concisely for people who ask. They will ask.
  4. Dirty, dirty, dirty. Numbers won’t match, they won’t add up, they won’t make sense, sometimes they won’t even exist. Know how much dirt you’re willing to live with, then accept it and move on.
  5. You will learn to love the query string. You will come to see it as a beautiful haiku. You will know it backwards and forwards. You will repeatedly explain its usage to people who need to append campaign codes to URLs.
  6. CSV stands for “comma-separated value” … it’s a file format, every data analyst’s friend, and – inexplicably – it doesn’t even have to be comma-separated. Huh.
  7. Operators are standing by. Know the support hotline number for your commercial web analytics vendor of choice, and don’t be afraid to call. If you have one sticky note on your monitor it should be that number. Actually two sticky notes. The other one should say, “Patience is a Virtue.”
  8. Don’t fall into the “report monkey” trap. Manually-repetitious activities are not a good use of your time, so automate wherever possible. Strive to spend your cycles doing thinking fellers work, and leave robot work to the robots.
  9. You are not alone. Right now there are other web analysts sitting at their own desks, somewhere between the techies and the marketers, and they’re facing exactly the same issues that you are. You will meet them at Web Analytics Wednesday.
  10. Think long-term. From the very beginning, think about where you want your career to go and make every effort to develop in that direction. Your entry-level position in web analytics can/should/will lead to other things, so know what you’re targeting and go for it.

Originally Posted at: http://june.typepad.com/june/2010/03/index.html

 

Looking to fill your Web Analytics or Online Marketing position?  Post your open jobs on Web Analytics Job Board.

Individual Visitors Tracking or Aggregate Data – Which One Is The Right Method?

Should web analytics tool track visitors as unique individuals or at the aggregate level? John Squire, Chief Strategy Office of Coremetrics says that tracking at Individual level is the way to go and this is how his company is differentiating itself (from Google analytics). Brian Clifton, former heard of Google Analytics in EMEA, responded by saying that aggregation is the way to go.

In my opinion both of them are right. Which route to go really depends on what you want from the web analytics tool?

Aggregate Data

If you are new to web analytics or you just want to track and analyze the overall health of your website, aggregated data will work for you. If you want to know how your marketing efforts are performing in terms of driving traffic or online conversions than aggregate data will just work fine for you. If you want to know which pages of your site are bleeding and then conduct A/B testing or Multivariate testing to improve them then aggregate data will work for you.
Individual Visitor Tracking

However as companies mature in their use of web analytics data they will need individual level tracking.

A company which is ready to do personalization will need to understand each individual browsing/purchase behavior to put the right offers/products in front of her. That is not possible with aggregated data.

It sounds perfectly ok to know that 75% of visitors abandoned the shopping cart but won’t it be nice to know who those 75% are or a way to convert at least some of those 75%? This is where individual tracking will come in handy. If visitors, who abandoned the shopping cart, leave an email during the process then you can send them a targeted email based on how far along they were in the shopping process, what products they had looked at, what product they had in shopping cart, etc. You don’t need to analyze every single data point but you can have business rules that can trigger those emails. However, to do so you will need to track at individual level. Even if you don’t want to send an email if you know the cookie id of the visitors you can put a personalized offer in front of them when they return back to your site and this will require tracking at individual level.

Individual tracking also comes in handy when the sales people call the lead that they just got from the website. Knowing what the person, who filled the contact us form, did on the website could provide a lot of information to sales person who can then tailor their conversation based on this information.

There are several more scenarios where aggregate data just won’t work. You will need individual level tracking.

I agree that tracking individual has privacy implication that need be properly addressed before tracking each person. However privacy issues also exist when you anonymously track visitors at aggregate level and those need to be addressed too.

So should you choose a tool that aggregates the visitor data or the one that tracks them individually? It all depends on what you want to do with that data. If you need help in figuring out what tool will work best for you feel free to email me at batraonline at gmail.com

Comments/Questions?

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Looking to fill your Web Analytics or Online Marketing position? Post your open jobs on http://www.web-analytics-jobs.com/
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Originally Posted at : Individual Visitors Tracking v/s Aggregate Data – Web Analytics, Behavioral Targeting and Optimization by Anil Batra

Web Metrics Pitfalls and Incentives

Website managers operate in a data rich environment. If it happens on your web page, & you decide you care about it, you can track it. And if you can track it, you can set goals around it & hold people responsible for meeting those goals…. The marketing team is responsible for transfers. Repeat visits are the responsibility of the engineering team. John is responsible for new account sign ups. With appropriate instrumentation & tracking (sometimes more difficult than it sounds!!), an organization can evaluate whether individuals & groups are meeting their goals. Evaluation is step one towards compensation, and when compensation is on the line, you can be damn sure people are going to be focused on making. their. numbers.  If you are a boss, YOU better be damn sure you are giving your people the right numbers to focus on.  In large organizations esp., many people end up  managing to a single number.  And throughout large organizations, even when many metrics are consulted, the drive for simplicity & collective understanding (and hopefully the organizational focus that results) will often lead people to a single number. One metric to rule them all, if you will.

One obvious way to go wrong when using this model is by picking the wrong metric(s). Again, focusing on a single number magnifies this danger.  For example… driving transfers to your site is your goal. Single-minded pursuit of THAT number can easily result in driving unqualified, unproductive traffic to your site. All while you comfortably make your goal. Oops. In this case it would be best to balance w/ length of session and/or repeat visits. Admittedly, this introduces complexity.

The more insidious way of going wrong is gaming the system. Metrics are about measurement. And measurement requires a known process. And known processes are gameable. You could change your URL structure to get previously uncounted pages counted; you could split articles into multiple pages to spike page views; you could redirect established traffic funnels.

And let’s not forget about who’s at the wheel… a bunch of type-A achieveaholics.  And that’s life, but if you give a type-A achieveaholic resources or an established traffic funnel and a number to make… suddenly massive amounts of traffic are being redirected to achieve goals. And on the collateral damage side of the equation.. the users.  They end up getting jerked around so people can make their goals & get paid (worthy goals, no doubt!).

And here’s an additional downer, if an independent party is responsible for measurement & you get caught gaming their system, it could sully your relationship w/ them & look bad publicly. Internally, the consequences are potentially worse. You’re going along thinking you are doing fine, all the while you could be undermining yourself.

So what do you do?  Most people say to go simple.  But single-minded focus on achieving a number can blind you to the complexities of what is happening on your website.  Instead, I recommend countering the drive for simplicity with some supplementary complexity.  Single numbers (or small numbers of numbers) are powerful tools for clarity & focus.  This is especially valuable in a large organization where people can easily lose sight of their goals.  But there have to be additional numbers that people watch.  Ideally these would be metrics that can provide contrary evidence to success in the face of growth in the key metric.  To repeat the example from above, if driving trials is your goal, stay focused on that number, but also keep an eye on repeat visits, & length of session.  Ultimately, you want to direct your numbers towards your users.  Of course, in a cookie based tracking system, you can’t really identify the user all that well.  But that’s why the job is fun, or at least, they need someone to do it.

Originally Posted at: http://www.menggoh.com/63/web-analytics/web-metrics-pitfalls-and-incentives/