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4 Data Ownership Questions You Should Ask: Creating a Culture of Analytics

June 17, 2013 By Leave a Comment

These days most of the marketing solutions are provided as a service. These solutions send emails on your behalf, server ads on your site , serve your ads on other sites/networks, collect your web Analytics data, collect your social media data, collect usage of customer on social media platforms, trade your cookies etc. You get the idea.

As a result, most of your marketing data resides with 3rd party vendors and outside your company’s environment.  In some case you might have an explicit agreement with the company that allows you to have ownership of your data (e.g. Omniture, ExactTarget etc.) while in other cases you might implicitly assume that you have the ownership of data (e.g. Google Analytics, Facebook etc.).  Either way the data resides with someone else.  This lack of direct ownership of your data could potentially pose a threat to your data driven culture.  I am not saying that all of sudden you will lose all your data (though that is also possible) but there is a potential risk.

Source: http://mimiandeunice.com/2011/01/06/ownership/

In order to ensure that you are in control of the situation, you need to carefully evaluate your “Data Ownership” risks and have a well thought out plan to mitigate the risk. Here are few question you need to ask

  1. What if the vendor(s) gets bought by one of your competitors?
  2. What if one of the free tools all of a sudden disables your account because of some violation (perceived or actual) of their policy? (See What I Learned When Facebook Disabled My Account)
  3. What if the vendor has a data breach?
  4. What if you want to move to another vendor?
    1. What will happen to your historical data?
    2. Will you have access to all you historical data? For how long?
    3. Will you be able to port your data into your inhouse system?
    4. Will you be able to port your data into new vendor system?
    5. What will be the cost of porting your data?
Filed Under: Culture of Analytics

3 Techniques for Expanding your Email Reach

May 31, 2013 By Leave a Comment

“Email-Marketing” image is copyright by ePublicist and made available under a Attribution-NoDerivs 2.0 Generic license. Source: http://www.flickr.com/photos/epublicist/8585152039/sizes/l/in/photostream/

Email marketers are facing a tough time with growing emails remaining unopened and unsubscribes. Acquiring new subscribers using old techniques is expensive. Below 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.

  1. Add social sharing in your emails – Let your loyal email subscribers help you. Add easy social sharing links/buttons to help them tweet, share on Facebook, linked in etc. If they like something in your email they will share it with their followers and friends. This will not only spread your messages but also will provide you with new subscribers.
  2. Segment differently – If you are doing segmentation to send emails, it is possible that you might be able grow the list of people in your segment by thinking beyond your current segmentation criteria. For example if you are sending a particular emails to who have listed their title as “Web Analyst”, you can extend the list by looking for subscribers who have not listed themselves as “Web Analyst” but exhibited behavior that looks like “web analysts” e.g. downloaded a whitepaper on tag management.
  3. Find Look Alike Using 3rd Party Data – You can go beyond emails and use 3rd parties to find “Look Alikes” of your loyal subscribers/customers. Find you loyal email subscribers/customers based on email opens/clicks/conversion and use their cookies to find more people like them using 3rd party cookie matching solutions such as BlueKai, i-Behavior etc. (Make sure not to cross the privacy lines when using these services).

I would love to hear about other techniques that you might be using.

Related posts

  1. Are You Depleting Your Email List?
  2. Number One Email Marketing Mistake
  3. 7 Ways to Create Relevancy in Emails

Analytics Jobs

 

Books that I am reading or have read recently

  1. You Should Test That: Conversion Optimization for More Leads, Sales and Profit or The Art and Science of Optimized Marketing
  2. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
  3. Data Points: Visualization That Means Something
Filed Under: email marketing

Do Number of Likes and Followers Matter?

May 21, 2013 By Leave a Comment

This is a one of those questions that keep coming up during conferences, the classes I teach at University of Washington, client conversations etc.

The default answer by most of the people is along the lines of “Oh they don’t …. It is the quality…. What really matters is the impact on revenue/cost… “ and so on.

I do not deny that ultimately the impact of business in terms of revenue/cost is what matters but saying that Likes/Followers don’t matter is flat out wrong.  It is equivalent to saying Visits to your site do not matter, potential customers in your store do not matter, subscribers of your email list do not matter etc.

Likes/Followers are the foundation that is required to make your social media efforts successful. Without Likes you don’t have anybody to put your messages in front of.  Without them you have nobody to amplify your message and help attract others like them.

If you are posting random stuff that has nothing to do with your business then you will attract random fans and followers.  If you talk about stuff in your particular industry/vertical etc. then you will attract Fans/Follower who care about what you are saying.   If you are attracting the right types of Fans/Followers/Like then number of Like/Followers does matter.  You want more of them.

 

Related Posts

 

Analytics Jobs

 

Books that I am reading or have read recently

  1. You Should Test That: Conversion Optimization for More Leads, Sales and Profit or The Art and Science of Optimized Marketing
  2. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
  3. Data Points: Visualization That Means Something
Filed Under: social media analytics

Are You Depleting Your Email List?

May 6, 2013 By Leave a Comment

In all the effort to drives conversions marketers often forget to measure “Unsubscribe” metrics and their impact on the email marketing.  As I mentioned in my post “Number One Email Marketing Mistake”, 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.

Getting an unsubscribe is easy, however getting more people to subscribe is very difficult and expensive. Email marketers need to have a long term view and protect the subscribers they have. They need to treat reducing the unsubscribes as critical, if not more, as driving people to subscribe.

I have come across some cases where the list situation is so bad that the unsubscribes will completely wipe out the marketers ability to do emailing marketing in next few year.   In order to ensure that you have a viable list, you need to closely watch and analyze the unsubscribe and subscribe metrics, few metrics that you should look at are:

  1. Total Unsubscribes/Total Email List in your database– This will help you understand what % of emails you can actually email to.
  2. Percent Unsubscribes/Email Sent – This will help you figure out if you need to adjust your email frequency.
  3. New Unsubscribes/New Subscribes – This ratio if greater than 1 than you are heading for trouble. Lower than 1 indicates that the direction is good though you need other numbers to understand the full impact.

In addition you should look at you ability to grow the list and see how soon you will hit the growth plateau. Once you hit the growth plateau, reducing the unsubscribes becomes even more critical.

Related Post: 7 Ways to Create Relevancy in Emails

 

Filed Under: email marketing

Tell a Story with the Data: Creating a Culture of Analytics

March 25, 2013 By Leave a Comment

Many organizations fail to create a culture of analytics, not because they don’t understand the value of analytics, but because the analysts fail to craft a good and relevant story with the data.  We have all seen reports filled with pretty charts, graphs and numbers.  After going through all the data if the audience doesn’t have a clear understanding of what the reports are telling and what they should do with those charts and graphs then the analyst has failed in his/her job, no matter how pretty the reports are.

Let’s face it, numbers are interesting for a while but a lot of numbers without a story leaves audience either unsatisfied or bored.  However a well-crafted story with data weaved in can keep your audience involved. It is still the data presentation but with a solid story that ties the data back to the business objective.

Data Analysts need to become better story tellers if they want to build a culture of analytics at their organization. Here are some of the elements of a good data story

  1. What are we observing
  2. Why does it matter
  3. How does it look compared to past performance, competitor, baseline, goals etc.
  4. Are we going to be able to achieve the goals
  5. What is effective and what is not
  6. What can we do today
  7. What did we learn that we can apply in future

Anything that is not relevant to the goals/objective of the business/stakeholder should be removed from the story (move detailed data to the appendix).  The KPIs should form the foundation of the data story.

Focus on the story rather than the tables of endless data and you will find that the people are willing to listen.

Other posts in the series

Filed Under: Culture of Analytics

Number One Email Marketing Mistake

January 29, 2013 By Leave a Comment

Number one mistake marketers make with email marketing is to send “Irrelevant” messages to their customers. It is not because they don’t understand that sending relevant messages drive higher conversions. It because they think that email messages are “Free” and incremental cost of sending messages to “non-target” customers is Zero. They hope that, by sending emails to everybody, some of the “non-target” customers will respond to their message thus causing overall conversions to go up.

However, this is a big mistake because what they don’t realize is that ultimately they will lose the privilege to this “Free” marketing.  Here is how you can see this unfolding and ways you can measure the impact

  1. In the beginning, engagement with the “irrelevant” email starts to slow down. People still open emails with a hope (if brand is one that they trust) that they might find something relevant to them.  This issue will be evident in your declining (or low) click-through rate.
  2. Then when people get tired of opening irrelevant emails, they start to rely on subject lines to see if there is anything relevant for them. This issue will become evident in declining (or really low) open rates of emails.
  3. Over time, all the irrelevance ultimately annoys people. Nobody wants a clutter of irrelevant emails.  Next step they take is to remove themselves from them madness.  You will see this manifest itself in higher or constantly going up unsubscribe rate.
  4. All this madness will ultimately lead to SPAM complaints.  As these grow the domain will be blacklisted and with it will go the privilage of “Free” marketing.

So if you are one of those who think “Email” marketing is free, it is time for you to stop and reevaluate how you are doing your email marketing. Here are few tips to ensure that you continue to do you “Free” marketing:

  1. Segment your customer base and only send relevant message to them , e.g. if a customer has never bought Women’s products from you then don’t send them an offer for 50% off on Women’s Clothing (See my post about Nordstrom’s email marketing Relevancy Matters in Email Marketing and 7 Ways to Create Relevancy in Emails)
  2. Continuously test your segments to improve your Open Rate, CTR and Conversion Rate and Conversions
  3. Based on your learning, further segment and develop micro segment to further drive relevance and effectiveness
  4. Keep in Mind: Always be Relevant and Always be Testing
Filed Under: email marketing

5 Tips to Improve Marketing Campaigns

October 3, 2012 By Leave a Comment

Marketers spend millions of dollars on digital marketing campaigns every day. Analytics help marketers get the most of out of every dollar spent and drive great benefits for them and their organization. Data collected at each step of the way to conversion can help marketers and their agencies in optimizing each campaign’s performance. Below I’ve outlined five tips on how to use the data to optimize marketing campaigns.

1. Target the Right Customers

For a campaign to have any chance of succeeding it has to reach the right customers. Clearly defining customer segments is a critical component of any campaign. You can use historical data from previous campaigns to determine which customers are more likely to respond to your campaign.

For an in-house email list, you can use attributes that you have available in the database and create a segment of customers with those attributes that have responded in the past. For display advertising, you can use email attributes or on-site behavioral data and use a technology like BlueKai to target and reach segments that look like those who responded in the past. For search advertising, determine the key phrases (words) that clicked with those customers and then use them as your starting point to figure out which keywords/phrases to use.

2. Target the Right Channels

The question marketers often struggle with is where to spend their budget. Which channel (e.g. direct mail, email, display, search, social, affiliate, etc.) or combination of channels is likely to be most effective for that particular campaign? Use historical data to figure the channels that your target segment is more likely to respond to.

Customers use various channels in their journey to becoming a customer. They use those channels differently. Use data (current and historical) to figure what a typical customer’s (your desired segment) journey is and then determine where you should focus your efforts.

3. Develop Creative and Messages that Resonate with Your Customers

If your creative and messages do not work you will notice it immediately in the form of clicks. Use historical data and industry benchmarks to determine the expected outcome in terms of Click Through Rate. If your CTR is way lower, change the content, if CTR is higher, continue doing what you are doing.

4. Developing Engaging Landing Pages

Getting people to click on your ads or emails is a good start but is of no value unless those users take actions on your landing pages. Use the data to determine if users are engaging with the landing page or are they bouncing off without going any further. If the bounce rate is more than expected, take appropriate corrective actions. You should always conduct testing (A/B or Multivariate) to figure out what resonates with your customer and make them go to the next step.

5. Optimize the Conversion Path

The conversion path is the last step in converting a visitor into a customer. The job of the conversion path is to lead the visitor to final conversion. Every step of the path is there to convince the customer and drive her to take the end action, the action that defines the success of the campaign. Use the data collected on the conversion path to determine which steps are losing visitors. Conduct A/B testing and take appropriate actions to improve the steps of the conversion path.

Note: This article was originally published on CMSWire on Sept 20th,  See 5 Tips to Improve Marketing Campaigns Using Data on CMSWire.com

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Digital Marketing Jobs

Filed Under: analytics, online advertising, online marketing

Dealing with Short-Term Memory: Creating a Culture of Analytics

July 17, 2012 By 2 Comments

We all make assumptions from time to time; sometime we state them clearly and sometimes we just assume in our own head. We then operate under those assumptions.  In context of Analytics, one such assumption is that everybody knows what the goals and KPIs are.  We might have defined them on the onset of the program, campaign, beginning of month, quarter, year etc., but once those are defined we start to assume that everybody knows about them and is operating keeping those goals in mind.

Well the truth is that people have short term memory. They do forget and then start to interpret the KPIs, defined based on those goals, in their own way.  As the Analytics head/analyst/manager, it is your job to constantly remind stakeholders of the goals and KPIs.  All it takes in one or two extra slides in your weekly/monthly reports/presentation to remind people about what the goals are and how you are measuring them.

Needs, requirements etc. do change too and when that happens it your job to reassess the goals and KPIs to make sure they are still valid.  If not then you need to bring up the issue in front of all the stakeholders. You need to drive redefining the KPIs.

 

Other posts in the series

 

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Filed Under: Culture of Analytics

Standard Definitions of Metrics: Creating a Culture of Analytics

July 5, 2012 By 1 Comment

Lack of standard definitions for the metrics causes people to report different numbers for supposedly same metrics, leading to confusion and total lack of trust in data.  No trust in data means that nobody is going to use the data to make strategic decisions and there goes all your efforts to create a culture of Analytics.

Having standard definitions is not as easy as it sounds.  It starts from you and your team having a clear understanding on how to calculate various metrics.   Some seemingly simple metrics can be calculated in various different ways and all of those ways might be right but getting one standard way of calculating those removes any confusion and gets everybody on the same page.

Let’s take an example and see how many ways you can calculate “COST”.  How do you calculate cost?

In case of Search Marketing, I am sure you are taking actual amount paid to Google or Bing. Right?  So that is actual media spend. But what about the cost you pay to your agency for running and optimizing those campaigns?  Where do they factor in? If all you are doing is Media cost then what about Display Advertising?  Is your Agency commission part of your cost? This agency is running and optimizing the campaigns so I am sure you are using that all up cost.  What about your internal email lists? What is the cost of that?   What is the cost of Social Media campaigns?  How do you calculate those? To have one definition of Cost you should calculate it in the same way across all media but most likely you have different way of calculating cost for different media/tactic.

Some more examples:

  1.  Conversion Rate? Is it measured in terms of visits, visitors, new visitors, non-customers or customers?
  2. How do you calculate a bounce? Is it page views based? Is it action based? Is it time based?

If your team is not clear on how to do this then how can you expect others in your organization to understand these metrics and trust the data. Creating a culture of Analytics requires trust in data and that trust requires standard definitions.

 

Other posts in the series

Filed Under: Culture of Analytics

Finding (Not Provided) Keywords in Google Analytics

March 8, 2012 By 11 Comments

I rarely write tool specific posts on this blog but since I have recently been asked by a few people about this issue and it affects every web analytics tool, I decided to post it here.

A few months ago, Google, the search engine, started encrypting searches for user who are logged into their Google account while conducting the search. As a result of this encryption, the keyword that the visitors search to arrive to your site is not passed in the referring URL. Web Analytics tools rely on the keywords passed in the referring URL to build the search engine traffic report and in the absence of the keywords there is nothing to report, though they still see that the visits came from Google search. So Google Analytics now marks those visits that do not have a keyword but come from Google with “(not provided)” keyword instead of the actual keyword.

Finding those keywords

Google still tracks all the keywords search by logged in users but just does not pass it in the referrer to the site that the user clicks through to. These keywords are available in the Google Webmaster Tools.  To see the report you will have to register your sites in Google Webmaster Tool. Google Webmaster tools will allows you to see all the keywords that were searched, the number of clicks your site got, the average position of your site for those keywords and the landing pages.

 

If you are not using Google Analytics on your site then you will have to login to Webmaster Tools anytime you want to see those reports.

(All images provided by GAPremium.com – Google Analytics Tips and Tricks)

If you are using Google Analytics then you can connect Google Analytics reports and Google Webmaster tools to get Webmaster reporting within the Google Analytics interface.

However there are three issues with this report when used with Google Analytics (or any another web analytics tool)

  1. You don’t get other metric (e.g. goal conversion) about the visits that arrived from the keywords.
  2. This list of keywords includes not only the keywords marked with “(not provided)” but also the other keywords that you see in Organic traffic report. So you will have to do extra analysis to see which keywords are hidden under “(not provided)”.
  3. If you look at Google Webmaster tool report then you will notice that there are a lot more impressions and clicks than those displayed in the Webmaster report and the Google Analytics report (see below). I was not able to find a reason why Google is only displaying the partial number of keywords, if you know the reason then please let me know.
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Digital Analytics & Marketing Jobs

Filed Under: digital analytics, search
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