Segmentation and Personas Part 1

The Web is all about choices and Analytics is all about understanding the choices by analyzing the behavior patterns:

Who are my right customers? Why do they make the choices that they do? What opportunities are worth chasing? What features will provide the most value? What is the best time-to-market, and most important which customers are most important.

While it’s difficult to make ALL the right choices, one has to make most of them right for the campaign, site, or product to succeed.

Enter Personas

This is a must have tool for marketers for helping them make the right choices. Personas is essentially a technique for capturing the important learning(s) from analyzing users and customers and identifying and understanding the different types of people who use the site.

It is a description of an imaginary but very plausible user that “personifies” these traits. The three key traits which personas help identify are:
Behavior, Attitudes, Goals.

How can Personas Help

• Rallying – Personas can help you build a common vision. If you look at any website, there is so much information that most marketers look at it at an aggregate level. There are literally thousands of details about a user (think pathing, content affinity, referring sources, tools usage, yada yada yada). An analyst, can’t possibly measure or conclude key behavior traits by analyzing these data points. Personas can help group these types at a high level and provide a human face to the types of people.
• Testing and Optimization – As a side benefit, you can test specific creative tactics on these personas. Messaging for the Net Generation (Gen Y) would be different than the messaging for Gen X (Baby Busters) . If you can identify the key behavior traits by type then you can build a test plan around it to drive conversions on the site.
• Targeting – Anil is one of the great thinkers around the topic of One on One personalization. His entries on Behavioral Targeting are a delight to read. Imagine, armed with “statistically significant” behavior data (or traits) you can proactively market or provide content to drive usage and ultimately convert the user. That’s the ultimate promise and the holy grail of marketing isn’t it?

Are there any cons or pitfalls

There are obviously things to watch out for. The biggest ones are prioritization and validation:

As a practitioner I have seen that a lot of research, thought, and homework done in building personas. Usually Strategy gets involved along with Product/Brand Owners and Senior members of the client and is handed down to executors.

What is important to understand is that your website is not for everyone. People will come to your site, tease you, perform competitive shopping, look for products, research about products etc.

It’s not okay to say that your website is for everyone. If you think that way you are deluding yourself. This is extremely difficult for most marketers to grasp. I try hard to explain to my clients is to focus your efforts or release or a landing page on a single persona. It doesn’t mean that the website or landing page will not be useful or usable by others, but if you gradually build the user experience around each type or user profile you will ultimately do a great job in attracting the highest quality users to your site. That’s the promise of Qualitative surveys and Quantitative analysis.

Another pitfall I have seen is that teams create personas based on their "assumptions" which usually comes from the Highest Paid Person In the Organization (HIPPO). In my mind this is guesswork and not based on any analysis; the right thing to do here is to take time to analyze your web data, interview/take time to talk to real users and verify if these personality types or personas really exist.

So are you using or thinking about personas for your website? Does your agency recommend taking the approach? Share it with us.

Next time we will talk about different techniques both qualitative and quantitative to measure personas.

Thoughts? Comments?

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This is a guest post from my friend and ex-coworker Kanishka Surana. Kanishka is currently the Head of Web Analytics for Ogilvy. He runs Ogilvy's Web Analytics group in North America, he has been in the Web Analytics space since 2002 and has worked in London, Seattle, Greece, Seattle, San Francisco, Salt Lake City, and most recently in New York.
Before that Kanishka worked at Gerson Lehrman Group a pioneer in proprietary research space. Kanishka and his wife Mini live in New Jersey.
This is first of a series of posts that Kanishka will be doing on this blog.

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

Current Open Positions

• Marketing Strategy Research Analyst at Magnani Caruso Dutton New York
• Digital Strategist at Magnani Caruso Dutton New York
• Sr Data Analyst at Capella University, Minneapolis
• Landing Page Optimization Analyst at Red Ventures Armed Forces - Europe

5 Web Analytics Misconceptions

There are several misconceptions in web analytics (created by some author/bloggers/experts) though many others have tried to clarify them from time to time but they keep reappearing. I recently had a conversation with someone who was so much in love with one of the misunderstood metrics, listed below, that it prompted me to write this blog post. So without much delay, here are the most common five misconceptions that I come across all the time:

1. More Page Views are good – Unless you are an ad supported site that sell advertising via CPM (cost per thousand impressions) more page views might mean that the visitors are lost on your site and can’t find what they are looking for. More pages views/visit could indicate issue with your site navigation. For effective analysis, set your baseline and then watch for significant deviations (up or down) from the baseline.
   
2. All that bounces is bad – I have written 2 detailed posts showing why all that bounces is not really bad. Bounce rate is one metrics that people overly obsess with. Keep in mind all bounces are not bad. The things that cause high bounce rate are:
   1. Links to external sites that you want visitors to click
   2. Ads on your site take visitors out of your site
   3. Returning visits might bounce because they might come to your site to read your daily/ weekly/monthly update
   4. Visits that are for a specific reason e.g. find your phone number
3. Focus on reducing the bounce rate and everything will be ok- Well that’s the advice many people give without even looking at the other data points and analyzing if reducing the bounce rate will really help you achieve your goal or not. Reducing the bounce rate might not be the most effective way to increase ROI. You should create a monetization model and determine the impact that reducing the bounce rate will have before you start creating different version of a high bounce page to A/B test to reduce your bounce rate. I have seen cases where you won’t get positive ROI even when you reduce the bounce rate to 0%.
   
4. Time on site (or page) shows how much time people are spending on the site – As I wrote in my blog post titled Understanding the "Time Spent on the Site" Metrics there are many issues with measuring the actual time spent on the site or a page. One of the main reasons is that the last page that a user views/reads on your site is not counted in this calculation. So if you have a non-ecommerce sites then the chances are that the visitors spend most of their time reading the last page but that page won’t not counted in this metrics and hence your time on page and time on site metrics will be way off. As long as you know that you need to watch the trend instead of using this metrics as a absolute measure of time spent on site then go ahead and use this metrics.
   
5. Referring Sites report shows all the traffic sources including campaigns – Well… not really. There are a lot of reasons for the referring source to be lost from the time the visitor clicks on the link to the time they arrive on your site, two big reasons are
   • Server redirects – This happens a lot with ad serving. Suppose you buy an ad though a 3rd party company who then uses an ad network to place your ads on a publishers site e.g. yahoo, each party does some processing and redirect of its own. In doing all these redirects the referring information is lost or shows one of the sites that does the redirect. For example, you might see atdmt.com showing up in the referring sites which means you were serving ad via Atlas even though the ad might have been served on MSN.com. Many URL shortening services used on twitter also show up as referring domain instead of twitter.
   • 3rd Party Apps – This is a big issue with Twitter URLs. A lot of twitter users use 3rd party apps and any clicks to your URL posted on twitter from these 3rd party apps will show up as direct traffic.
   
   If you are running a campaign or posting links in social media, blogs, forums etc, make sure to tag them with campaign identifiers so that you can use campaign reports instead of relying on referring sites report.
   

Thoughts? Comments?

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image source: ct4me.net

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

Current Open Positions

• Marketing Strategy Research Analyst at Magnani Caruso Dutton New York
• Digital Strategist at Magnani Caruso Dutton New York
• Sr Data Analyst at Capella University, Minneapolis
  
• Landing Page Optimization Analyst at Red Ventures Armed Forces - Europe

Compound Metrics in Web Analytics

Should you use a compound metrics in your web analytics reporting? This was a topic of discussion in one of my classes at UBC Web Analytics course.

What is a Compound Metrics?

Before we get into answering the question, let’s look at what a compound metrics is.
Simply stated a compound metrics is when you take two or more simple measures and combine them together to form one metrics.

So should you use it?

Short answer is - why not? Sometimes simple metrics such, such as visits, page views, clicks etc., are not enough to explain a complex concept and that's when you need a compound metrics, e.g. engagement metrics, visit quality measure etc.

But isn't compound metrics hard to explain?

It depends on how you define it but then a lot of people still struggle with
visits, visitors, hits and pageviews. With that in mind, I agree that initially it might be a little hard to grasp the compound metrics. Over long term, compound metrics actually helps simplify the measurement of a complex concept.

Some of the common uses of the compound metrics are

1. Credit Score (Everybody has one and it affects them every day but how many actually know how it is calculated?)
2. Google Page Rank
3. Twitter Resonance (it will use several factors such as retweets, clicks on links etc.)
4. Twitter measurement. Many twitter measurement tools use compound metrics since it is not easy to explain Reach, Impact, Engagement in simple metrics.
5. Facebook's "Likeability Index". Ok, I made this one up but I am sure that's coming soon.

Example

Let's look at an example and see where such a metrics will make sense in your current web analytics reporting.

Lets take an example of a product information site. The products are sold offline via 3rd party retailers and since this company does not want to compete with its retailers it doesn't sell anything online. This site provides information about the various products that this company sells. It provide white papers with pre-purchase information and post purchase information/support. The site has some videos and some stories that are published every now and then. Well there is a sign-up form to allow users to save their product information.

The whole goal of the site is to provide information to current and future customers.

Now your big boss asks "We spent thousands of dollars to build this site, is this site working?".

You reply, well... Visits are down but repeat visits are up so seems like people like it and are coming back. However, page views/visit are down. More white papers are downloaded as compared to last month. However, video views are down and sign ups are also down. Seems like some things are up and some things are down.

Boss goes...."What does that mean? Is it working or is it not? Are customers finding information?"

How do you measure that?

As an analyst you can look at all the metrics and come to a conclusion but you have to be able to convey the end result to the VP of marketing. He needs to know if the site is successful or not.

This is where a compounded metrics comes in handy.

A simple formula for this could be

(% of visits viewing X pages or more + % of visits viewing video + % of visits downloading white papers type 1 + % of visits downloading white papers type 2)/4

we used 4 in the denominator because we are using 4 different metrics with equal weight

Now you can add other metrics that matter to the business and also assign different weight to each, so your formula could be something like:

(1*% of visits viewing X pages or more + 4*% of visits viewing video + 1*% of visits downloading white papers type 1 + 2*% of visits downloading white papers type 2)/8

1,4,1 and 2 are the weights assigned to each metrics based on their importance to the business.

Once you develop a baseline for your metrics, you can confidentially tell you boss if the sites performance is better or worse than the last month. Keep in mind that you are an analysts and you should always get under the hood to analyze each component and find opportunities for improvement.

What do you think?

Questions? Comments?

Other articles on similar topics are

• http://www.juiceanalytics.com/writing/franken-measuresor-how-construct-useful-composite-/
• http://www.usca.edu/polisci/apls301/compound.htm

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

Current Open Positions

• Marketing Strategy Research Analyst at Magnani Caruso Dutton New York
• Digital Strategist at Magnani Caruso Dutton New York
• Sr Data Analyst at Capella University, Minneapolis
  
• Landing Page Optimization Analyst at Red Ventures Armed Forces - Europe

5 Questions to ask before starting a Retargeting Campaign

Retargeting or Remarketing is way to put your ad in front of the people who have been to your site before and are likely to respond to you ads and offers.

Retargeting via Google Adwords

Retargeting is not new, I have been writing about it since 2006 and working in this area since 2003. Recently, Google Remarketing, via adwords, has brought retargeting to the masses. Though, in my opinion, Google has not done a good job in educating advertiser on how to effectively engage in retargeting. To start with, Google says, you should retarget every visitor who came to your site. That is a wrong approach and I highly discourage it. As you read through this post , you will know my reasoning behind it. You have to understand remarketing to effectively use it. I am listing 5 questions that you should ask before you put that JavaScript code to start remarketing.

5 questions to ask before starting a Retargeting Campaign

1. What is the purpose of this retargeting campaign?
   This is first question you should always ask. Also ask, Why are we doing this? What is the purpose of retargeting? As you answer this question, you will automatically start to answer some of the questions listed below.
   
2. Who are your target customers?
   Remarketing to all of you visitors, in most cases, not a good idea. If you are a portal, news site, have daily updates then it might (maybe) make sense to remarket anybody and everybody who visited your site. For most of the sites it doesn’t make sense to retarget everybody. Think about this, why would you want to target me with an ad to sell TV when I recently bought a TV from your site?
   
   
   
   
   Trying to sell ice to the Eskimo?  Try it. You'll be sorry. To be effective, you should segment your visitor base and understand their needs. For example, by targeting the shopping card abandoner you have a better chance of conversion. By targeting those who have already downloaded a whitepaper, you have better chance of selling your free trial. The message (ad) you will put in front of these visitors will speak to their needs and hence will be more attractive than a generic message. Which leads to our third question.
   
3. What will be your message?
   If you know the purpose and audience segment for the campaign then it is much easier to write your message (ad copy). Your ad copy has to be effective to drive people to take action. Make it right. Say you want to target all the people who downloaded a whitepaper on A/B Testing but did not sign up for free trial then your message can be “You know A/B Testing leads to higher conversions. Get started with a Free trial of xyz tool”. Alternatively, if you are trying to remarket to all the visitors who came to your site, reviewed few page and left without downloading the whitepaper then your message should drive them to download the whitepaper. Remember, one message does not fit all. Message has to resonate with the segment that you are targeting.
   
4. Where will the visitors land?
   You have identified why you want to engage in remarketing and who you are targeting, now you have to make you sure that when customers arrive on your site they get the relevant information and clear call to action on the page they land. Sending visitors to an appropriate landing page is critical for the success of remarketing .
   
5. How will you know you are successful in remarketing?
   You can’t manage what you can’t measure. Define your KPIs so that you can measure the effectiveness of remarketing. Properly defined success measures will also allow you to take necessary actions (test and fine tune ad copy, message or even the segments) to ensure you achieve your goals.
   

Google Remarketing Gone Wild.

Recently I came across two examples of remarketing where, in my opinion, the thought was given to the first 2 questions. I have an example to share with you. A while ago I visited Lyris newsletter template download page via a newsletter link. I gave my email address and downloaded the templates. Since I am done downloading, I don’t have a need to download them again.

However, the remarketing campaign keeps remarketing to me with a message inviting me to download the whitepaper (see below). If they have something new to offer then I might go back. If they have to offer the next logical step in moving me towards the sales, I might pay attention to it but I am not going to go back again to download the same templates that I downloaded few days ago. Seriously! Do not waste your impressions on me. If increasing brand awareness is the goal of this campaign then they should have a different message in the ad copy.

(Note: Currently there is a limitation in Google Adword retargeting which makes it harder to segment and target that segment only. If you are interested in segmenting and targeting then send me an email and I will provide you a solution that will help you target efficiently.) 

Sidebar: Below are some of the ways you can use remarketing

• Cart Abandonment – Target visitors who have abandoned the shopping cart to bring them back to the site and complete the purchase. This is the most widely used and talked about use of remarketing.
• Next Steps towards Conversion - Target visitors who took some prelim steps but did not complete the next steps towards purchase. E.g. Target the visitors who downloaded a whitepaper but have not come back to sign up for free trial.
• Cross Sell/New Products – Target past customer with an up sell or cross sell. If a visitor bought a shirt recently maybe it is time to show them an ad for a tie that will go well with that shirt.
• Brand Awareness – Remarket to people who have visited your site in past. Remarketing can put your brand right in front of them to further build brand awareness. Though this one is difficult to measure.

Thoughts/ Comments? Are you doing remarketing?

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Looking to fill your Web Analytics or Online Marketing position?
Post your open jobs on Web Analytics Job Board
Landing Page Optimization Analyst, at Red Ventures (Fort Mill, SC)

Web Analytics is Money

How do you convey the value of Web Analytics to an organization that has never used web analytics or has used it but at a very elementary level? This is one of the questions that I constantly get from students of my UBC Web Analytics classes, where I am an online tutor.

My answer to them is they should start the conversation with something like, “Web Analytics is Money” or “Web Analytics helps companies make more money” etc.

When you say those words, you are very likely to get audience who want to know more. Money invokes curiosity.

You should not tell the CEO how web analytics can help the company understand customer behavior, find bottlenecks in the site, improve bounce rates etc. You should show him/her the impact in terms of dollars (or Euros, Rupees etc.).

Every web site analysis can lead to actions that have an impact on the money. You can tie web analytics to:

• Additional revenue
• Cost Savings
• Profit
• Doing more with less money (particularly for non-profits)

Example:

Let’s take a simple example to illustrate this.

Reducing Bounce Rate

If you are not getting any traction, I assume your analysis might look something like:
“Home page is the top most landing page with 80% of the visits entering through this page. However, 60% of the visits bounce i.e. leave the site immediately, after landing on this page. 60% bounce rate is very high as compared to the industry average.* There is a huge opportunity for us to lower the bounce rate on this page by testing the page layout…..(you provide your reasoning on what should be changed and why).”
Great. As an analyst I can understand and you can understand it. But what about CEO of the company? Will he/she understand it? Why should he/she care about the bounce rate?

*Typical Bounce Rates by Anil Batra

Now, try the following:

Generating More Revenue

“Our analysis shows that there is an opportunity for us to increase our revenue by $300,000 for the year by optimizing our home page. Home page is the top most landing page with 80% of the visits entering through this page. However, 60% of the visits bounce i.e. leave the site immediately, after landing on this page. 60% bounce rate is a very high number compared to the industry average.* There is an opportunity for us to lower the bounce rate on this page by testing different page layouts. Lower bounce rate will help us drive more people to the purchase funnel and even if our funnel completion rate remains at 20%, by sending more people to the top of the funnel we will have additional 3000 sales leading to $300,000 in additional revenue for the year.”

Tying your analysis and recommendations to money makes it easier to understand the benefit of Web Analytics. Money will make it easier for you to overcome organization barriers and make you a hero.
Web Analytics is money!!!

What do you think?

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Looking to fill your Web Analytics or Online Marketing position?
Post your open jobs on Web Analytics Job Board
Landing Page Optimization Analyst, at Red Ventures (Fort Mill, SC)

Conversion Tip: Making the Most of the Email Confirmation Thank you Page

Email sign-ups are a very common ways for businesses to capture a potential lead. Visitors who are interested in your product or services will likely take a step towards providing their email address to you.

Your job as a marketer in not complete when a visitor gives you’re your email address. You need to make sure that you provide proper scent (links, messages etc.) for them to engage with your site/content/brand etc.

Almost every contact with a potential customer provides a conversion opportunity i.e. an opportunity to engage them to view more content, products and /or sell. If you do not take advantage of that opportunity then you might miss out on many conversions that you could have had.

Email sign-up confirmation page is one such opportunity that is so often forgotten by the marketers. The main reason for that seems to be the use of 3rd party to manage your email subscription list. Often the small details are missed in a hurry to get the system live. I hope you are not making this mistake.
I am going to share two examples to illustrate my point.

Example 1: Missed Opportunity

This is from a site called Daily Checkout. I loved what they had to offer so I decided to sign up for their daily email.

After providing my email address on their site, here is an email that I got from them. (so far so good, though the “from” email address is the address of 3rd party they are using to manage their email list).

I clicked on the link to confirm my email subscription and I was taken to the page below:

That’s all I got. The title of the page shows me some other company’s name. I am sorry, which site did I sign up for? Where is the rest of the page? I want to look at more products on your site, how do I do that? MISSED OPPORTUNITY.

Example 2: Making the most of the thank you page.

This page provides a nice confirmation thank you page and also provides me a link to explore more content. Well Done.


What do you think? Do you have any examples of the email confirmation pages that totally miss the mark or the pages that do it perfectly? If yes, I would love to see them.

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Looking to fill your Web Analytics or Online Marketing position?
Post your open jobs on Web Analytics Job Board
Landing Page Optimization Analyst, at Red Ventures (Fort Mill, SC)

iPhone Analytics & Location Based Ad Targeting– Prohibited by Apple

App Analytics

It appears that, according to the new developer agreement, iPhone and iPad developers cannot use any 3rd party analytics application to collect any kind of iPhone or iPad usage data. According to the clause,
Device Data may not be provided or disclosed to a third party without Apple’s prior written consent. Accordingly, the use of third party software in Your Application to collect and send Device Data to a third party for processing or analysis is expressly prohibited.
(Source: Apple Changes Rules on iPhone App Analytics)

It is not clear what the “Device Data” actually means. Does it just cover the OS/Browser, screen size etc. or does it cover any data collected by the app?
However, based on an email from an iPhone developer, referenced in a venturebeat.com blog post, it appears that this clause might cover pretty much any data collected via the applications.

> We’ve reviewed your
> application and determined that we cannot post this version of your iPhone
> application to the App Store. It is not appropriate for applications to
> gather user analytics. Specifically, you may not collect anonymous play
> data from a user’s game. A screenshot of this issue has been attached for
> your reference.
>
> In order for your application to be reconsidered for the App Store, please
> resolve this issue and upload your new binary to iTunes Connect.


Ad Targeting

Part of this clause is also a statement about location-based ad targeting.
“The use of location-based User Data for enabling targeted advertising in an Application is prohibited unless targeted advertising is the purpose of such Application (e.g., a geo-location coupon application).”

Some other great post on this topic are

• An Open Letter to Steve Jobs by Eric Peterson
• Updated: New iPhone Developer Agreement Bans the Use of Third-Party Analytics and Services

Is this a step to control all advertising on iPhone and iPad? Is Apple is about to roll out its own iPhone and iPad analytics solution? Perhaps buy one of the existing vendors?

What are your thoughts?

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Post your open jobs on Web Analytics Job Board