Sunday, May 05, 2013

Are You Depleting Your Email List?

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
Posted by Anil Batra at 10:02 PM Links to this post
Labels:

Sunday, March 24, 2013

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

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
Posted by Anil Batra at 10:20 PM Links to this post

Monday, January 28, 2013

Number One Email Marketing Mistake

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
Posted by Anil Batra at 9:57 PM Links to this post

Wednesday, October 03, 2012

5 Tips to Improve Marketing Campaigns

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
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Digital Marketing Jobs
Posted by Anil Batra at 1:07 PM Links to this post

Thursday, July 05, 2012

Standard Definitions of Metrics: Creating a Culture of Analytics


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
Posted by Anil Batra at 11:28 AM Links to this post

Wednesday, March 07, 2012

Finding (Not Provided) Keywords in Google Analytics

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.

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.
To leave a comment please visit my new blog at http://anilbatra.com/analytics/2012/03/finding-not-provided-keywords-in-google-analytics/

——————————————————————————————————————-
Digital Analytics & Marketing Jobs
Posted by Anil Batra at 4:22 PM Links to this post
Labels:

Monday, March 05, 2012

Digital Analytics Association

This morning, Web Analytics Association announced that it is changing its name from Web Analytics Association to Digital Analytics Association.

Why the change?

All of those who have been working in this industry for few years know that the term “Web Analytics” does not reflect the actual work we do. As I wrote in my last post “Move Web Analytics Data Out Of Silo”, “Web Analytics” purpose was to report on one channel “your website”. Nowadays the story is different, customers interact with your brand in so many way, your website is just one small part of the whole “web” ecosystem. The work most of the web analysts do today involve more than web. Web Analysts today analyze many “digital” channels such as social, mobile and email along with web. Many are starting to deal with other digital channels such as “Set top boxes”. So definitely “Digital” is a better term to describe the work that web analytics groups undertake.

I like the evolution of “Web Analytics Association” to “Digital Analytics Association”.

What’s next?

Many forward thinking organizations have been doing “Digital Analytics” for quite some time. I am not just taking about providing an integrated view of Digital Data on one spreadsheet/dashboard, I am talking about connecting the dots of customers interaction in various channels and using the integrated data to optimize customer journey and campaigns.

These organizations are diving into the next step in this direction i.e. “multichannel” analytics. Many “web analytics” companies are already developing products to move the organization from “Web” to “digital” to “multichannel” analytics and optimization. (Full disclaimer: I work for iJento which is a multichannel analytics company. Many of our clients are already beyond “Digital Analytics” and have moved into the next phase of evolution e.g. “Multichannel Analytics”)

So will Web Analytics Association (WAA) Digital Analytics Association (DAA) be called Multichannel Analytics Association (MCAA or MAA) in future? I think so but for now I like “Digital Analytics Association”.


What do you think?

(Note: I am an ex-Board Member of WAA DAA)

——————————————————————————————————————-
Web Analytics Jobs


Posted by Anil Batra at 12:58 PM Links to this post
Labels:
Subscribe to: Posts (Atom)