Tuesday, 20 September 2011

Sentiment Indicator: Social Media KPI

People talk, they say good things about a brand, they say bad things about a brand or they just talk. Social media has become a place for people to make sure whatever they are saying is heard loud and clear by their friend and followers on Facebook, twitter, blogs etc.

Going through all this social media chatter to understand and figure out what is going on about your brand is a very labor and time intensive work. Even though many Social Media Monitoring tools have done a great job in aggregating the data from various sources, but to understand the context of those conversation and provide that to marketers in a meaningful way still needs a lot of work. Currently it really needs a human to understand the full context of the conversations and understand the sentiments of consumers.

However there are some metrics that can provide you a measure of the sentiments (positive or negative) of these conversations and indicate which direction they are going.

Social Media Sentiment Metrics


Almost all of the social media monitoring (listening) tools provide following metrics to help you understand the sentiment of the conversations about your brand in social media.
  • Total number of conversation or mentions about a brand, product or topic
  • Number of positive conversations or mentions about a brand, product or topic e.g. a tweet saying: I love brand ABC
  • Number of negative conversations or mentions about a brand, product or topic e.g. a tweet saying I hate brand ABC
Many social media analysts use these raw number of positive and negative conversation to monitor the health of their brand, competitor or industry in social media (positive is good and negative is bad, unless that conversation is about your competitor).

However,these numbers are not KPIs. For example, if one day there are 100 negative conversation about your brand and the next day you have 50 negative conversations then what does it really mean? On the surface it looks like you have done something good to bring down the negative conversations by 50%. Is it really true though?

To fully understand those numbers we need a little more context. Looking at the total number of conversations about your brand might provide some context. Say, there were total 200 conversations about our brand on day1 and 100 on day two. If we take percentage or ratio of positive conversation to total conversations and ratio of negative conversation to total conversation we find that we did exactly the same on both the day.

On Day 1: Negative Conversations/Total Conversation Ratio = 100/200 = 50%

On Day 2: Negative Conversations/Total Conversation is 50/100 = 50%

As you can see these ratios or percentages provide much more information than the raw number did. Even though raw negative mentions were down, as a percentage your negative conversation were about the same on both the days. This is where many social media analysts and marketers stop and use the above 5 metrics as KPIs. Let’s relist the 5 KPIs discussed so far
  1. Total Conversation about a brand, product or topic
  2. Number of Positive Conversations about a brand, product or topic
  3. Number of Negative Conversations about a brand, product or topic
  4. Ratio or Percentage of Negative Conversations/Total Conversation
  5. Ratio or Percentage of Positive Conversations/Total Conversations

But something is still missing in these metrics. Those who have analyzed social media conversation know that majority of the conversations are classified as “Neutral”. Neutral means that there is no positive or negative sentiment in the sentence or the conversation in which that brand, product or topic is mentioned. In my experiences, over 90% of the conversations are neutral. So let’s take another example to show how that messes up the above KPIs.
  1. Day 1
    Total Conversations: 1000
    Negative Conversation: 5
    Positive Conversations: 10
    Negative/Total Conversation = 5/1000 = 0.5%
    Positive/Total Conversation = 10/1000 = 1%
  2. Day 2
    Total Conversations: 1500
    Negative Conversation: 5
    Positive Conversations: 10
    Negative/Total Conversation = 5/1500 = 0.33%
    Positive/Total Conversation = 10/1500 = 0.67%
In the example above, it looks like our positive and negative conversation both dropped on day 2. Though in reality, looking at the raw numbers there was no difference in the volume of positive or negative conversations. It just happened that “neutral” conversations went up on day 2 causing the percent of positive and negative conversations to go down.
So as you can see, in this case raw numbers are a better indicator than the percentages or ratios. So you can see how none of the above 5 KPIs provide an accurate view of sentiments of conversations in the social media. We need a better KPI.


Sentiment Indicator

I use another KPI, that I call "Sentiment Indicator" or "Sentiment Index", which in my opinion, is a better indicator of sentiment then other metrics that we discussed. Here is how I calculate “Sentiment Indicator”:

Sentiment Indicator = (Positive Conversations – Negative Conversations)/(Positive Conversations + Negative Conversations) 


(Note: Even though neutral comments are still good for analysis, I do not use them in my calculations of Sentiment Indicator.)

Using our example above Day 1, The Sentiment Index will be 10-5/(10+5) = 33%, which is exactly the same as that on the Day 2.

This metrics is more actionable than other metrics. If it goes in negative direction that means we are getting higher number of negatives as compared to positives and it is time to get into action. If it goes in the positive direction then we must be doing something good and time to find out what that is. Also, many times I will use the volume of conversation along with it to make sure that while we are maximizing the positive conversation we are also enabling the total conversation volume to go up.

Note: You should still dig deeper into those conversation, particularly the negative ones and see what is going on. Sometimes even one negative comment can quickly go viral and ruin your reputation.

Your turn now. How do you measure sentiment?

If you are not sure and need help, don't hesitate to email me at batraonline (at) gmail (dot) com or leave a comment on this blog post.

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Wednesday, 30 March 2011

QR Code Analytics

QR codes have started to pop-up in lot of places such as store display, business cards, online ads, postcards etc. Whether QR codes are here to stay or not but from the measurement perspective they do present a huge opportunity in measuring advertising's (particularly offline) effectiveness.

If you are one of those marketers who have embraced QR code or are thinking about it or just curious to know how QR code measurement works then this post is for you.

Measuring URLs in QR Codes

You won’t be able to measure the number of impressions of the QR codes if they are distributed offline. What you can measure is how much traffic those QR codes are driving to your site or to your pages on 3rd party sites like facebook page, twitter account etc.
  • Measuring QR code links to your site

    Measuring QR codes that sends user to your site is as simple as campaign tracking. Just add the campaign tracking variable to the URLs that you have in your QR Codes and treat it like any other campaign. Then you can use your campaign reports to see how much traffic QR codes are bringing and how valuable that traffic is.

    (Note: The tracking code, that you should append, depends on your Web Analytics tool.

    For Google Analytics, you need to append add at least 3 variables, Source, Medium and Campaign Name. to the URL for it to be tracked in the Google Analytics (Check out URL Shortner, http://clop.in as it’s URL builder let’s you append the variables for tracking in Google Analytics, Omniture, WebTrend and Unica NetInsights )

    Example
    Say I want to create a QR code to send people to
    http://webanalyis.blogspot.com

    Instead of simply creating a QR code to http://webanalyis.blogspot.com I appended Google Analytic campaign tracking code so my URL looks like the following http://webanalysis.blogspot.com?utm_source=qrcode&utm_medium=blog&utm_campaign=qrcodeblogpost



    Now I can use the campaign tracking in Google Analytics to see the stats on my QR code advertising.

  • Measuring QR links to offfsite URLs such as Facebook page

    Since you won’t have your own web analytics tool running on a Facebook page you can use a URL shortener like http://clop.in or http://bit.ly (or better yet get a URL Shortener for your own domain with built in analytics from http://clop.in) to shorten the destination URL and then build a QR code using the shortened URL. This way you can use the built in analytics functionality of the URL shortener.

    Example:
    Say I want to send user to my facebook page http://www.facebook.com/TheAnilBatra

    Rather than sending user to the facebook page, via my QR code, I created a short URL using http://clop.in, http://clop.in/PByJfv and then used this shortened URL to build my QR Code.


    Now I can use the analytics reporting of http://clop.in/short-url-clopin.aspx?utm_source=qrcode&utm_medium=blog&utm_campaign=qrcodeblogpost to see the stats on my QR code advertising.

Tracking Phone Numbers in QR Code

To Track phone numbers, that get dialed when someone scans a QR code, use a unique phone number that you have tracking for. If you don't have unique phone number then you can use 3rd party services likes Marchex to get a unique phone number for each QR code that you publish.

Note: To create a QR code use a service like http://qrcode.kaywa.com/ 

Questions? Comments?


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Thursday, 10 March 2011

Underline the Clickable Text and Link the Pictures

Sometimes there are things that you know are not right and need to be fixed immediately rather than testing and waiting for the result. Such was a case that I recently encountered and the results were amazing.

Recently, I was working with a client who sells people expertise (I am purposely vague here because I don’t want to reveal the name of the client). The “Expert” search is the start of the process and then “Expert Search result” page is a second step in the process.

On the expert search page, each expert is listed with a small blurb and the name of the expert was linked to the next step of the “checkout process”.

When analyzing the “checkout” process we noticed that there were 2 things missing
  1. The name of Expert was not underlined – it was linked to the next step in the “checkout” funnel but not underlined. Also, that was the only call to action on that page i.e. to click on the experts name to go to the next step.
  2. The picture of the Expert was static and had no link whatsoever.
Recommendation

Usually I recommend doing A/B testing before making any changes to a page/process but I also do rely on best practices from time to time. In this case underlining the Expert’s name (“product name”) to get more information and to link the image to either next step or the enlarged version of the image with more info made total sense. I was confident that I did not need any test (I sound like a HiPPO, right?). So
So rather than waiting to conduct an A/B test we went ahead and made those changes.
(of couse a clear to call to action link or button might have worked too but that was not an option)

Result
  • Exits from that page dropped from 38% to 33%
  • Funnel conversion rate went up from 40% to 47% (Though 40% conversion was amazing considering there was no highly visible way to get to the next step of the process).
I am sure if you look at your own site you will find plenty of such opportunities for improvement.
Thoughts? Comments?

Friday, 4 March 2011

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




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Monday, 28 February 2011

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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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)



  • Thursday, 24 February 2011

    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:
    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.

      Tuesday, 15 February 2011

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



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

      Current Open Positions




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



    2. Web Games Analyst at Arkadium (New York, NY)



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



    4. Web Data Analyst at Genworth Financial (Richmond, VA)



    5. Web Games Analyst at Arkadium (New York, NY)



    6. Web Metrics Analyst at Omnitec Solutions (Alexandria, VA)



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