Tuesday, June 07, 2016

Web Analytics Under the Hood



Do you understand the mechanism of Web Analytics? Do you understand how data is collected and translated into the nice reports that you see in Google Analytics, WebTrends, Adobe etc.? Now you can.
Signup for my online course - "Web Analytics Under the Hood".

This Online course will go under the hood and show you how the data gets generated, collected and processed to generate beautiful reports that you
see in your Web Analytics tools.

Having a good understanding of what happens behind the scene will provide you the confidence you need to support your understanding of the reports and provide a fresh new perspective on Web Analytics reports.

This course will be helpful for both newcomers as well as seasoned professionals. I will cover topics that I ask in interviews while hiring a web analyst. This course will help you:
  • Understand how browser/server communication happens.
  • Understand how data gets passed to server.
  • Understand how data is collected ( Javascript, server logs) - Basics of Data Collection Javascript using Google Analytics as example.
  • Understand how cookies are used (we will look at Google Analytics cookies)
  • Understand how data is stored in the back-end.
  • Understand how data is processed.
  • Understand how data gets Converted into Visits, Visitors, Page Views, Referrer and various other reports.
Signup below to be notified when the course becomes available in Mid-July.  You can also pre-order this course for $50 (instead of $100). You will get a link for payment after you signup.

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Wednesday, April 27, 2016

As many of you already know, I teach few courses in Digital Marketing and Analytics at various universities and colleges including University of Washington and Bellevue College in Seattle area.
Last year I was asked if I can design a course on Data Visualization using Tableau. Since we were actively using Tableau at work I decided to do it.  I have taken that same course, that I taught, and developed an eBook. The audience of this eBook is beginners who want to learn the basic of Tableau and get familiar with various interfaces and terms used in Tableau.  If you are someone who wants to learn Tableau or have looked at Tableau but don’t fully understand it, then this eBook is for you.
I am giving away few copies of the eBook in return for the feedback.  If you are willing to provide me the feedback on this book within a week, then email me at batraonline at gmail.com or tweet me at @anilbatra and I will send you a copy of it.
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Want to learn Tableau but don’t have to provide me the feedback on eBook, here are few Tableau Books on Amazon
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Sunday, January 10, 2016

What does 1st, 2nd and 3rd party data mean?

1st, 2nd and 3rd Party Data Demystified

I have referred to 1st party and 3rd party data in a lot of blog posts. Based on the queries I get, both via email and in the classes I teach, it is time to clarify what various data sources mean.
1st Party Data
1st party data is the data that you (brand/publisher/retailer) have collected about your visitors, customers, shoppers etc. You own the data outright and all the rights to it. You can use it for any purpose you want based on the agreements with your visitors, customers, shoppers etc. as specified in your data collection and use policies. Some examples of 1st party data are:
  • Site registration data – name, email, address, gender etc.
  • Visitors behavior data on your site – time of visits, minutes spent, products looked at, source of visits etc.
  • Shoppers/customers purchase data – products purchased, transaction amounts, coupons used etc.
  • Email data – emails sent, opened, clicked etc.
  • It is most widely used data for the marketing purposes. Generally, you use the 1st party data for customer retention using email marketing, retargeting and onsite personalization.
2nd Party Data
2nd party data is the data that is collected by some other company and shared with you(brand/publisher/retailer), in other words it is their first party data. A strategic data sharing partnership between two brands/publishers can help both of them grow their customer base and monetize that customer base.
You can generally use 2nd party data to:
  1. Augment the data you already have about your customers (or visitors) – for example, if you do not collect “Household Income” during customer registration/signup data but have a need for that data you can partner with another brand that collects that data to get that data to enhance user profile. Another example is Google Adwords sending the keyword/campaign data to enhance behavioral data collected on the site.
  2. Add a list of new customers – for example, if you are hotel booking site, you can have a partnership with airline to share information about customers who recently booked. If a customer books a flight, then you can use the data from partner to reach those customers and offer them hotels. Similarly, the airline partner can reach the customers who have booked hotel on your site.
3rd Party Data
3rd party data is the data collected and aggregated by someone other than the 1st party (data collector). In other words, the data aggregator doesn’t directly collect the data from customers/shoppers/visitors but have relationships with several companies/sources that collect the 1st party data. Some examples of the 3rd party data provider are BlueKai, Acxiom and i-behavior. These data providers aggregate the data from different sources to build a comprehensive profile of a customer/person. These enhanced profile let you understand a visitor/shopper more than what a 1st party or 2nd party data sets can provide.
For example, if you are a Financial institution, it will be very helpful for you to know which of your customers travel frequently, this will help you offer them a credit card that provides added travel rewards and benefits. This is where 3rd party data becomes useful that can provide such information based on data collected from various data sources such as hotel booking sites, airlines, location based data on several other places, other credit card providers etc
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Tuesday, October 06, 2015

One huge targeting mistake and how to avoid it: Understand the context beyond few keywords

wrong-targeting

Contextual advertising is not new, when I first started writing about targeting advertising the technology was new, the concept was new and few bold marketers were trying and learning from their mistake while helping others teach on how not to make this mistakes.
A post by Kevin Hillstrom, Highly Targeted Digital Ads That, Well, Just Read The Article., tells me that we have yet to learn from the mistakes that have been made since the early years of online ad targeting.
I remember when we are first dabbling withdisplay ad targeting and retargeting back in early 2000s, one of the things we were trying to solve for is to understand the full context of the content you were reading.  We saw many marketers making the mistake of not understanding the negative context of the content and wasting their ad dollars on wrong content. For example we saw an ad targeted (I believe it was served by Google) on a page talking about plane crash that showed an ad for carry-on luggage. When you are reading such a tragedy, last thing you want to see is an ad about plane travel. Technology and best practices have come a long way since then but the same mistakes keep happening.
Here are two things you can today to make sure you do not make the same mistake as VW dealer (or their agency) made:
  1. Filter ad placement on negative context: If you are going to show an ad about your brand then understand the whole context and then filter out any content that has negative context related your brand. For example the whole context of that video was about negative to VW because of recent emission scandal. You as a marketer need to know that a lot of recent content (video, articles, blog post etc.) are going to be about this scandal, so keeping this context in mind, create a list of negative keyword list e.g. emission, scandal, problem etc. Now filter out the ad targeting on the content which contain “Volkswagen” and these negative keywords because if you place your ads on such content it is likely not going be very effective. Stop wasting your dollars by targeting the wrong context.
  2. Show Ad to counter the negativity around your brand – If there is a message that you have in response to the negative press then use this opportunity to put your message in front of the customer and prospects.
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Thursday, July 30, 2015

Are Your Insights Interesting or Actionable?

actionable

“What is the business objective and who is the audience?” this is the question you should always ask before developing data insights.  This will help you figure out if you need to focus on Interesting or actionable insights. Yes, actionable insights are also interesting but not the way Media thinks. Media hypes Interesting Insights, insights that might not be actionable and valuable to the business. Your business stakeholders might prefer actionable insights over interesting. I said might because some business stakeholders (sometimes) will prefer Interesting even though that can’t do much with it, it just sounds good in their presentation.
Let’s look at example of Interesting insights that gets coverage in Media.
“We can tell you that on a January morning in Miami, if a set of weather conditions occurs, people will buy a certain brand of raspberry,” he says. Not just any fruit. Raspberries. When advertisers ask for an explanation—why raspberries?—Somaya can’t always provide a clear answer. “A lot of times we have to tell them to just trust us.” Other times, he finds correlations that make perfect sense. “There’s a particular dew point percentage that makes everyone in Dallas rush out and buy bug spray,” he says. “We couldn’t figure out why, then we realized that insects’ eggs hatch at that dew point.” Basically, everyone in Dallas was getting bitten at once.
Great, very interesting but as a business what will you do with it? If you are a grocery store in Miami then either you have raspberry in stock or not. If you have it then great, you don’t need those insights. If not then you can’t just go order your distributors to get you the Raspberries when those set of conditions happens.  Ordering takes time and so does shipping, by the time you get those raspberries in your store it is already too late.
Similarly in the second case, you can’t just go ahead and start stocking bug spray when the dew point hits a certain point. Either you have them in stock and you will sell them or you don’t have them then by them time you get that shipment, dew point has already changed. Let’s assume that you are able to use advertising (mobile/online/social/TV) when the right conditions (dew point and other conditions) happen.  But, by the time customer gets the message those conditions are most likely already over, leaving your advertising worthless. But Media does not care about that, all they care about is more readership which comes when there is something interesting.  In a nutshell, such insights are developed for Media, if that’s your goal then sure go ahead and generate and publicize them.
Actionable insights on the other hand might not be as interesting to the outside world but as they are to your business. These insights will certainly provide the value to your business.  If you tell your stakeholders that customers buy notebooks in two weeks leading up to school opens (back to school) and buy calculators a week after school opens, then that is an insight you can use to drive more sales. You can plan your inventory and advertising based on school start dates. Media likely won’t talk about such insights but it is actionable and interesting (for the business).
So when coming up with insights always keep in mind the objective and your audience. Both Interesting and Actionable have their place but don’t confuse one for the other.
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Monday, June 22, 2015

CMOs: Three Major Roadblocks to Insights

whats-in-your-way-success-coach-christchurch-1024x1024

Data is the raw material for developing insights. If the complete data is not available to insights team then you can’t expect the insights to be very valuable. Insights teams will make the best out of what they have available but you will get far better insights if you spend little time with them to understand what they need and help them with these for major roadblocks.
  1. Data Sources and Collection – Insights team has identified the data sources required for them to provide great insights, the data is all there either available internally or externally. The big challenges comes when the data teams actually start to figure out how the data will be collected. For internal data sources the organizational barriers are the biggest ones that prevent one team for getting access to the data that other team owns. Your team will need your help in navigating those barriers and help the free flow of the data. If external data sources are on their list then your help will be needed to provide appropriate funding and legal clearance needed to get those data pieces.
  2. Data Storage – Storage per GB/TB is cheap and will continue to be cheaper but with that the amount of data will continue to go up (see the graph below) All in all, you will end up either spending a lot of money or will need to clear out the data repository to keep cost in check. Clearing the data means data gaps will emerge causing the gaps in Insights. For example, if all your data team can store is six months’ worth of data then you will be missing out on yearly trends, If all they can store for 1 year then you will be missing out on multi-year trends etc. Your team will need your support in ensuring that you have appropriate budgets approved to ensure that your team can store the required amount for their analysis.
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  1. Data Access – Having all the data collected and stored is half the battle, other half is making sure that the data is accessible by the insights team. Majority of the time the data will be stored in the cloud, Hadoop etc but is not easily available to the analysts who will need it for their analysis. In order to make any sense of the data, the insights team needs to have easy access to the data, not just in little chunks but to the whole set. You analysts might not be well versed with database technologies to make proper connection. They need an easy way to either connect their analysis tool e.g. Tableau, Excel etc. to the data sources so they can pull the required data to conduct analysis. They will need your help in pushing the other teams to make data accessible to them.
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Monday, June 01, 2015

4 KPIs for Measuring Email List Growth

List-Ad

Email list growth is the foundation of email marketing program. Unless you keep care in protecting and growing that list you will end up non functional email marketing program. Recently, I wrote a post on 23 Metrics for Email Marketing Metrics that you should know about, in this post I am taking 3 metrics from that list and adding one more to call out the 4 KPIs (Key Performance Indicators) to measure the email list growth.  Here are the four KPIs:
  1. Email Complaint Rate/Spam Complaint Rate – SPAM complaints can kill your marketing program. This KPIs allows you to see if SPAM complains are becoming an issues, you goal should be to minimize this KPI. Spam complaint rate is measures as the percentage of your email recipients who marked your emails as Spam. Looking at this number campaign by campaign and then aggregated over month will show you if you are annoying your subscribers to a point where they consider your email as spam. This number is readily available in most of the ESP.
  2. Subscribe Rate – This KPI measure the effectiveness of your marketing/content in driving new email subscribers.  Your goal should be to increase this KPI. Subscribe rate is expressed as a percentage and is calculated as New Subscribers divided by visitors who are not already in your list. Most of the Web Analytics tools will provide you this number by tracking the completion of emails subscription page as a goal/conversion. These tools use the total goal conversions divided by total visitors on the site during the specified period to calculate the conversion rate (Subscribe Rate). The default conversion rate calculation by web analytics tool will also count anybody who has already subscribed to your list thus inflating the denominator. In most cases the default calculation will suffice but if you do want to get accurate numbers then you will have to setup your web analytics tool to not count people who are already subscribed.
  3. Unsubscribe Rate – Is the percentage of your emails recipients (subscribers) who chose to unsubscribe from your future mailings. Unsubscribe Rate is calculated as number of unsubscribes divided by email delivered and is expressed as a percentage. It measures the effectiveness of your email marketing strategy and the quality/relevance of your email marketing. If this number continues to rise, you have a problem that should be immediately fixed. The fixes range from adjusting the email frequency to increasing the relevance of the message.
  4. List Growth Rate – This is ultimately the one metric that everything else boils down to. If you have to only show one metric on your dashboard or optimize for one metrics then use this one as it is calculated using the other three that I have listed above.  This KPI measures how fast your email list is growing, it is the net results of new subscribers minus the unsubscribes (including hard bounces) and email/spam complaints. It is calculated as, Growth (new subscribers ) – Loss(unsubscribes + email complaints) divided by total list size of your email list. Your email marketing program depends on List Growth so watch this number closely and take actions to actively grow your email list.
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Here are few more email marketing posts that you will like:
  1. 23 Email Marketing Metrics That You Should Know
    This post lists all the email marketing metrics that you will ever need.
  2. One costly email mistake that you can easily fix
    Growing email list is a hard job. All you Growth hacking goes down the drain when you make a simple mistakes that costs you subscribers that you just gained. This posts you one such mistake and how to fix it.
  3. Email Personalization Not Working? Read This
    This posts explains why the email personalization might not work. The bottom line is that you have update your personalization criteria over time and test it.
  4. 3 Techniques for Expanding your Email Reach
    Email marketers are facing a tough time with growing emails remaining unopened and unsubscribes. Acquiring new subscribers using old techniques is expensive. In this post I have listed 3 techniques that you can use to spread the word of your emails/newsletters beyond the email list that you are sending the emails to.
  5. Are You Depleting Your Email List?
    Email marketers, in order to maximize short term conversions, often bombard irrelevant emails in subscribers inbox However this short term mentality results in erosion of long term viability of their email marketing, due to increase in unsubscribes causing depletion of email lists.
  6. 15 Things to Test in your Email Campaign
    This post talks about 15 things you can test today.
  7. Targeting Cart Abandonment by Email
    Targeting Cart Abandonment is a great way to drive conversions however, use incentives/offers cautiously.
  8. Conversion Tip: Making the Most of the Email Confirmation Thank you Page
    Use your Confirmation page effectively, this posts shows an example of a good page and a not so good page.
  9. Number One Email Marketing Mistake
    Number one mistake marketers make with email marketing is to send “Irrelevant” messages to their customers. Find out why this strategy has a far-reaching impact on your email marketing program.
  10. 7 Ways to Create Relevancy in Emails
    7 tried and tested ways of creating relevancy in emails are described in this post.
  11. Relevancy Matters in Email Marketing
    This post shows an example of an email that missed the opportunity to convert.

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