Context is Critical: Creating a Culture of Web Analytics

Continuing my series on Creating a Culture of Analytics I would like to touch on a very critical aspect of creating a culture of Web Analytics and that is Context.

What is Context

According to Princeton.edu context is

• Discourse that surrounds a language unit and helps to determine its interpretation
• the set of facts or circumstances that surround a situation or event

Context takes the ambiguity out of the equation. As an Analyst it is very important that you provide full context when reporting your web analytics data. Context gets everybody on the same page. Do not leave anything for interpretation by the end users of your reports, give them the insights in a simple and easy to understand format.

Let’s look at an example to understand critical context is.

60 Degrees

If I say it is going to be 60 degrees tomorrow. What will be you reaction?
If you are in Minnesota – You will yell “Summer”
If you are in Seattle, you will think – ““Spring”
If you are in Florida, you will say “ Damn… Cold”
If you are in India, you will say “WTF….” (Indians measures temperature in Celsius and 60 degrees Celsius is 140 F)

Some other question that might pop in people’s mind are:

• What is the temperature today?
• Is it normal to have 60 degrees this time of the year

Without context 60 degrees does not mean much. Right.
Similarly when you report your numbers and tell report on visits, page views, time on site etc. it does not mean much unless you provide the full context.

Web Analytics & Context

Just saying that Visits are down by 10% from last week is not enough. You have to put that 10% decline in full context. Tell your end users what happened and why they should or should not worry.

So add something like : Visits are down 10% from last week and also 10% lower compared to the same time last year. Prior to this week we saw a 10% year over year growth but last week was abnormally down. Isn’t that betting better now?

You should go even further: Last year we got some free advertising from local newspaper sites that drove 20% additional traffic same time last year. Since we did not have the advertising deal this year, it impacted our visits this year. We noted the potential impact of newspaper site advertising in our last year’s annual recap (here is the link to last year report – people forget so remind them). If we take out the impact of spike from newspaper sites then we have a consistent pattern of 10% year over year increase. As noted in last few reports, that increase is due to our social media efforts this year. Now the picture is much clearer. Of course you should look into the full impact e.g. conversion, bounces, sales etc. (Note: How you present this story will depend on what format you chose to present your report)

Now everybody is on the same page and knows exactly what those numbers mean. Without that context, everybody would have had their own interpretations of the data. Misinterpretations lead to wrong action and/or mistrust in the data and the analytics team.

Final Words

Do not provide any reports without providing full context. Keep in mind that most of the canned and automatic reports do more harm than good because they do not provide context.

Other posts in the series

• The Curse of Knowledge: Creating a Culture of Web Analytics
• Creating a Culture of Web Analytics

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Follow me on twitter @anilbatra

Facebook Page http://www.facebook.com/pages/Anil-Batra-Page/130050670343547

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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

• Web Analytics Senior Implementation Consultants (Contractor)  at Acceleration Emarketing (New York, NY)
• Web Analytics Analyst at Designory. (formerly Agency.com) (Chicago, IL)
• Web Games Analyst at Arkadium (New York, NY)
• Online Performance Data Analyst at Announce Media (St Louis, MO)
• Web Data Analyst at Genworth Financial (Richmond, VA)
• Web Games Analyst at Arkadium (New York, NY)
• Web Metrics Analyst at Omnitec Solutions (Alexandria, VA)

Value of Social Shares

Adding a widget such as AddThis , ShareThis and Facebook Like button on your site makes it very easy for your site visitors to share your site and content with their friends and followers via email or social media. Even though these are small widgets, that your developers/designers might not have paid much attention to, they add a tremendous value to your business.

According to a recent report by eMarketer 47.5% of the people trust the recommendations of their social media contacts. In order to leverage social sharers you have to make it easy for them to share you content and widgets like these do a good job in making your site shareable.

A small widget like this can save you thousands of dollars in customer acquisition and even retaining the customers via either direct conversions from the traffic driven by shared links or by the brand awareness that those links create.

Monetary value of Social Shares

Most of the sharing widgets have built in analytics to measure the virality of your site/content. Use the analytics report to understand how valuable those shares are. Make share analytics reporting part of your web analytics reporting so that other stakeholders can see the value too. If you need to convince your boss on why they should pay attention to these social shares, tie the value of shares to something more tangible i.e. Dollars/Pound/Euro/Rupee. Here are some of the ways you can tie the value of social shares to money:

• Direct revenue
• Life-time value of customer gained via social share
• Advertising cost savings from the shares

Let’s do a simple calculation to see the value of social shares. In this example I tied the value of “Social Share” to the amount saved in paid search advertising

Example Calculation

Data that you will need:

1. Clicks Generated– The number of click/visit/visitors generated from Social shares shares. (You might only get clicks/share from the widget analytics but you can easily estimate visits or visitors based on the data from your web analytics tool)
2. Cost of a visit – You can estimate this from either a blended cost of all your online advertising or simply from paid search.

That’s all. Using the above information you will be able to calculate the “Cost Savings”, the cost you would have paid to drive those visits that you got for free from social shares.
Note: If you are able to tie the social sharing with your web analytics tool then you can not only get accurate count of visits (or visitors) instead of just clicks but also can get the conversions and revenue generated from those shares.

A/B Testing & Optimization
The location of you share widget will have an impact on the number of social shares you get. Social shares present a great opportunity to drive lots of valuable traffic. A/B test different locations of share widget to see how it impacts your bottom line and find the best location for those widgets.

I have attached a spreadsheet that will allow you to calculate the value of those shares and the opportunities optimization present. Just plug in some basic numbers and see the results. Download the spreadsheet from http://anilbatra.com/digitalmarketing/downloads/socialshares.xlsx

Related post: 3 Tools for Measuring the Virality of Your Content

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Follow me on twitter @anilbatra

Facebook Page http://www.facebook.com/pages/Anil-Batra-Page/130050670343547

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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

Web Analytics Senior Implementation Consultants (Contractor)  at Acceleration Emarketing (New York, NY)

Web Analytics Analyst at Designory. (formerly Agency.com) (Chicago, IL)

Web Games Analyst at Arkadium (New York, NY)

Online Performance Data Analyst at Announce Media (St Louis, MO)

Web Data Analyst at Genworth Financial (Richmond, VA)

Web Games Analyst at Arkadium (New York, NY)

Web Metrics Analyst at Omnitec Solutions (Alexandria, VA)

3 Tools for Measuring the Virality of Your Content

Several studies have shown that people trust the link and site recommendation they receive from their friends or experts in the field. To capitalize on this opportunity websites have long used features like “Recommend to a Friend” or “Email this” kind of functionality. Recently we have seen a rise in usage of tools/widgets that make it easy for the visitors to share links via email and social media.

Measuring Virality
Many of the tools/widget that allow you to add easy sharing now also have built in analytics to help you track things such as which content is getting shared, how many people like to share etc, what methods do they use to share etc.

3 tools that you should look into are:

• ShareThis
• AddThis
• Tynt

Tool Comparison

ShareThis and AddThis

ShareThis and AddThis are very similar in functionality with some minor differences but they look more like each other.

Both this widgets have very similar reporting and tell you

• How many links were shared
• How many people shared them
• What content was shared
• Number of clicks back to you site from those shares
• Sharer’s interest
• Geo locations of the sharers

AddThis and ShareThis only capture the information if a user uses the widget provided by these companies. However, these widgets won’t’ track the content shared by old fashioned copy and paste of either the URL or the actual content of the page. This is where Tynt comes into picture.

Tynt

Unlike AddThis and ShareThis Tyne does not have any share widget. Instead it works by automatically appending a unique hash value (a number folder by #) to each URL and the copied content. It uses that hash value (sort of like unique cookie) to determine metrics such as how many times the links/content was copied from your site, the number of visits it brought back and various other metrics.

Most of the reporting is very similar to AddThis and ShareThis widgets. Here is a list of some of the data that Tynt reports on:

• How many times your content was shared
• How many visitors you got back from those shares
• What content was shared and how much
• It even tells you how your sharing compares to others
• Geo locations of the sharers and clickers

However, There is one report that only Tynt provides and that is the keyword report. It shows you

1. Inbound keywords - keywords that visitors searched to get to your site (AddThis has a different variation of keyword report)
2. Outbound keyword - the keywords that visitors found on your sites but left your site to find out more about them. This is a really cool report because it tells me what else I can write more about on my site so that my visitors don’t have to leave the site to find out more about them. I will be using that report to add more content to my blog/site.

I will cover some more details on these tools and how we use them for our clients in future but for now I suggest you look at these tools and let me know what you like or don’t like about them.

Do you know of or use any other service? Send me the details.

Note: In addition to above three there is “Facebook Like” button too.

The Curse of Knowledge: Creating a Culture of Web Analytics

Presenting the data is what Web Analysts do majority of the time. It is critical for Web Analysts to present the data in a way that is easily understood by their intended audience. However, I have seen time and again that this simple rule is missed. Why? Because we all suffer from what is known as "The Curse of Knowledge".

What is The Curse of Knowledge?

Here is what 37Signals.com write on this subject:
Lots of research in economics and psychology shows that when we know something, it becomes hard for us to imagine not knowing it. As a result, we become lousy communicators. Think of a lawyer who can’t give you a straight, comprehensible answer to a legal question. His vast knowledge and experience renders him unable to fathom how little you know. So when he talks to you, he talks in abstractions that you can’t follow. And we’re all like the lawyer in our own domain of expertise.

"Curse of Knowledge" becomes a big issue for Web Analysts and Managers who are trying to create a Culture of Web Analytics. We assume that people know what we know because it seems so simple, right? Think again. Even simple metrics such as Visits, Visitors and Page views that seem so simple and no-brainer to you are difficult for others to understand.

If the numbers/data/reports that you present to the stakeholders do not provide them what they need in a simple and easy to understand format then you are in for a very though journey to building a Culture of Web Analytics.
To further illustrate my point, let me tell you about a situation that I personally had to go through.

I was approached by a mortgage agent who wanted me to refinance my mortgage and claimed that he had better rates than any other lender in the area. So I thought, sure let me see what this guy has to offer. So we met and I gave him my goals

1. The amount that I wanted to refinance
2. The interest rate range that I was comfortable with
3. $0 closing fee

I also asked him to tell me how much my monthly payment was going to be for those interest rates. We decided to watch the interest rates to see when they fall in my range and he promised to send me the daily interest rates.

That’s all.

Next day he sends me the following table with some explanation of the two columns. All this did not make sense to me, and I deal with numbers all day long. He also wrote that he will explain this to me over the phone.

So he called and tried to explain me the above chart but he still did not answer my earlier questions. See the problem?


If you have to call someone to explain your data that mean you have not done a good job of understanding him and his needs.

You see how easily you can alienate someone by not presenting the information in the right way. That’s the issue you face when you are trying to sell value of analytics within your organization. People look at your reports few times, find it too complex to understand and move over to other things. If that happens then you are done.

So do not fall a victim to “Curse of Knowledge”, step in your audiences’ shoes and make your reports really simple and actionable. Three key points to remember when presenting the data are

1. Understand your audience and their goals
2. Understand their level of understanding of the subject matter
3. Customize the data presentation to meet your audience level of understanding of web analytics and needs. Make it a no-brainer to understand and tie everything back to the business goals

Questions? Comments?

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Follow me on twitter @anilbatra

Facebook Page http://www.facebook.com/pages/Anil-Batra-Page/130050670343547

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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

Web Analytics Analyst at Designory. (formerly Agency.com) (Chicago, IL)

Web Games Analyst at Arkadium (New York, NY)

Online Performance Data Analyst at Announce Media (St Louis, MO)

Web Data Analyst at Genworth Financial (Richmond, VA)

Web Games Analyst at Arkadium (New York, NY)

Web Metrics Analyst at Omnitec Solutions (Alexandria, VA)

Web Data Analyst at Alzheimer's Association (Chicago, IL)

Creating a Culture of Web Analytics

All those who have worked at companies which never used or do not use web analytics to make decisions about site changes, know how difficult it is to create a culture of web analytics. It is very hard. Building a culture of web analytics is a grueling uphill task.
After working with various client I have found that reasons for not using web analytics vary from company to company, some of the common ones are:

• Gut feel has always worked or at least it seems like it has worked
• It is an additional step in the process
• New skills are required to use web analytics. They feel they don’t have the required skills for using web analytics
• Fear of accountability i.e. now I will be measured and I don’t like that
• The reports that they got in past were pretty useless
• They didn’t believe in web analytics data because they have no clue on how the data was collected
• They don’t understand how web analytics can help them
• They don’t understand what web analytics is

The first reaction of many newly hired analyst/analytics manager is to start talking about KPIs, reports, what web analytics can do etc. But before you start digging into the data and analysis and start to talk about KPIs, dashboards etc. you need to understand the root cause of why analytics has not been used in the past. Understanding and tacking those issues will give you a better platform to build the culture of analytics on.

Here are few things you need to do before jumping into KPIs

• Identify various stakeholders, who could benefit from web analytics, in the company. You don’t have to have a comprehensive list of every person but some that you think could immediately benefit and you can immediately help is also a good list to start with
• Get a meeting with them, individually or grouped together in groups based on their roles/departments etc.
• Agenda of the first meeting should be to understand why they have not used web analytics in the past and what they would like to see from web analytics group. Don’t talk about KPIs yet. This meeting is about hearing them, if they talk about goals, metrics etc. then fine but don’t jump to discussing KPIs
• Make sure they understand that there will be a follow-up and you are there to help them not to use numbers to find faults. You need collaboration. Don’t let other people’s opinion about HiPPOs put you in an offensive or defensive position
• Schedule a follow-up meeting to go over you analysis of the past meeting, address any concerns/issues that are preventing them to use analytics

The goal of this exercise is to make people feel confident that you can truly help them make data driven decisions without jeopardizing their job. You understand their concerns and are willing to address them.

During this process you will also find out who all (groups/individual) are more willing than others to help you build your case and will provide you small wins that you can use to garner more support. If you have an executive support e.g. your bosses boss then leverage that to help you.

At the end,remember, every company is different. The culture is different, challenges are different, political structure is different so it is critical you understand all those elements. It is not going to happen overnight so be prepared for a long rocky journey.

Comments/Questions?

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Follow me on twitter @anilbatra

Facebook Page http://www.facebook.com/pages/Anil-Batra-Page/130050670343547

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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

Web Games Analyst at Arkadium (New York, NY)

Online Performance Data Analyst at Announce Media (St Louis, MO)

Web Data Analyst at Genworth Financial (Richmond, VA)

Web Games Analyst at Arkadium (New York, NY)

Web Metrics Analyst at Omnitec Solutions (Alexandria, VA)

Web Data Analyst at Alzheimer's Association (Chicago, IL)

Web Analytics Manager at Tig Global (Chevy Chase, MD)

Online Personalization: Issue Is With People Not Technology

Today I came across an article by Isaac Weisberg, titled Unintended Consequences of Targeting: Less Information, Less Serendipity – Part I. In this article Isaac argues that online personalization limits the exposure of information to the individuals. I agree that current personalization practices are very limited though it is more of an issue with the marketers engaged in personalization than with the technology. ( Note: Retargeting, Behavioral Targeting, on-site recommendations, customized emails etc. are all different forms of personalization). So it is not Personalization that limits the flow of information but it is the people engaged in Personalization.

The purpose of personalization is to provide information that is relevant to an individual and in order to do so you will eliminate a lot of information that the person is not likely to be interested in. However that does not mean that the person cannot be exposed to new information with the personalization.

The issue is that most of the marketers engaged in personalization (targeting) do not exploit the full potential of personalization and limit themselves to basic targeting. I highlighted one such issues in my post 5 Questions to ask before starting a Retargeting Campaign.

Personalization does not mean that you have to limit yourself to the same product or even the category. User’s behavior gives you a clue on what he/she likes. Use that to figure out complimentary items that you might be able to promote and even items that don’t make sense together but you have seen patterns from sales data that tell you that they might go together. E.g. particular pair of shoes is bought by lots of moms, so maybe kids’ shoes might make sense to promote to a user who has shown interest in those shoes. Isn’t that flow of information to the user?
I once worked with a client who used two mutually exclusive behaviors (people who read financial news and view international weather) to promote a totally unrelated product (high end international travel) with a great success.

So, yes exposing people to new information while doing personalization is quite possible as long as marketers doing the personalization are willing to use their creativity and move beyond their comfort zone.

Questions? Comments?

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Open Web Analytics and Online Marketing Jobs

• Online Performance Data Analyst  at Announce Media (St Louis, MO)
• Web Data Analyst at Genworth Financial (Richmond, VA)
• Web Games Analyst  at Arkadium (New York, NY)
• Web Metrics Analyst at Omnitec Solutions (Alexandria, VA)
• Web Data Analyst at Alzheimer's Association (Chicago, IL)
• Web Analytics Manager at Tig Global (Chevy Chase, MD)

HiPPO: Wrong Advice That Will Get You In Trouble

HiPPO is an overly used in the web analytics community to make the web analysts feel good. But this term, in my opinion, does more harm than good to you.

Though I meant to write this post a long time ago, today a post by Steve Jackson - HiPPO could be your best friend finally prompted me to write it.

For those how don’t know, HiPPO is a term used to describe the opinion of the Highest Paid Person (HiPP) i.e. Highest Paid Person’s Opinion. This terms basically says that the person who gets paid the most (it assumes that this person is also the highest authority position) will make decisions that are not based on any facts but rather based on his/her gut feel. As a result his/her opinions are generally wrong. Really? Do you really think that they got into their position by giving wrong opinions?

Some experts even encourage analysts to publicly embarrass HIPPOs by proving them wrong? Really? How do you think it is going to help you? Will you have a job tomorrow?

As an analyst, your job is to help your organization make better and smarter decision by using the information you gain from the data. How is calling Highest Paid Person a HiPPO or embarrassing your boss in public going to help it?

To make your point and get someone to listen to you, you have to make friends and not enemies. Just thinking that all the opinions expressed by the HiPP are wrong and not based on fact will automatically put you in either a defensive or an offensive mode instead of a collaborative mode. You need collaboration to succeed. Web analytics is still not integrated into business optimization process and the wrong attitude towards HiPPO will hinder it further.

Think about this, if you are an analyst attacking a HiPP in the room, who do you think will win at end?

Thoughts? Comments?

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Open Web Analytics and Online Marketing Jobs

• Web Data Analyst
  at Genworth Financial (Richmond, VA)
• Web Games Analyst
  at Arkadium (New York, NY)
• Web Metrics Analyst
  at Omnitec Solutions (Alexandria, VA)
• Web Data Analyst
  at Alzheimer's Association (Chicago, IL)
• Web Analytics Manager
  at Tig Global (Chevy Chase, MD)
• Sr. Data Analyst
  at Capella University (Minneapolis, MN)
• Manager, Web Analytics, Search & Production Support
  at Asme (New York, NY)
• Web Analytics Manager
  at Conde Nast (New York, NY)
• Web Analytics Manager
  at Juggle (Swansea, IL)
• Sr. Analyst Web Analytics
  at Williams-Sonoma (San Francisco, CA)