23 Email Marketing Metrics That You Should Know

541529038706138While ago I wrote a post on Measuring Online Display Advertising. Continuing the theme, in this post I am describing 23 metrics for measuring email marketing.

  1. Sent: The numbers of emails (generally unique email address) that were sent. This number excludes any suppressions that occurs due to business rules, privacy compliance etc. Your email service provider (ESP) will have these number as a standard metrics in their reports. This is a raw metrics that is used to calculate other email performance metrics and is generally of low value by itself so should not be used as a Key Performance Indicator (KPI).  A trending of this metric overtime can provide you a view into the health of your marketing list.
  2. Delivered is a count of emails that made their way into the recipient inbox.  If an email was rejected by the recipients email provide then it is not counted as delivered. If an email shows up in junk folder, it is still counted as delivered. Your email service provider will have these number as a standard metrics in their reports. This is a raw metrics that is used to calculate other metrics.  A trending of this metric overtime can provide you a view into the health of your marketing list.  Delivery rate (described below) is a better indicator of Delivery issues than the raw number. This metrics by itself is not a KPI but forms a basis for other KPIs.
  3. Delivery Rate – It is calculated as Emails Delivered divided by Emails sent, expressed as a percentage is Email Delivery Rate. Delivery Rate measure the quality of your email list, goal is to have 100% delivery rate, but I can guarantee that it is not going to happen. Any deviation from 100% should be investigated to see what is causing the issues. If there are some hard bounces (see below) then those should be removed promptly. Too many hard bounces can lead to spam triggers and further delivery issues.
  4. Bounce – An email is considered a bounce when it cannot be delivered to the intended email address. There are two types of bounces – Hard Bounce and Soft Bounce. Hard bounce generally means that the email address is wrong or no longer exists. Soft Bounce generally means that the addresses exists but either the inbox is full or is having temporary issues, the message is too large to deliver etc. You should immediately remove Hard Bounces from your email list since they are dead and you will never be able to deliver an email to them. Raw number of bounces should not be used as a KPI.
  5. Bounce Rate – Bounce rate is measured as Bounces divided by emails sent, expressed as a percentage. It is exact opposite of Delivery Rate. (Note: this should not be confused with the Landing Page Bounce Rate)
  6. Total Opens: Total opens measure the number of times your email has been viewed by the recipients. It gets counted when a recipient opens the email. Emails use a small invisible pixel (image) that gets loaded every time an email is viewed, the loading of this invisible pixel is counted as an open. Few things to keep in mind
    1. Any recipient who have disabled the images will not be counted in the open metrics since the invisible pixel won’t be loaded.
    2. Any recipient who has preview pane open will be counted as open as the emails gets loaded in preview pane enough though the person might not actually open it.
    3. Multiple views by same respondent will increase the open count, one for each view (open).
  7. Unique Opens - This measures the number of unique recipients who opened the email. Unlike Total opens, multiple views (opens) by a same recipient will be counted as one unique open.
  8. Total Open Rate – This measure the effectiveness of your subject line and your brand (shown in from column of email) in driving people to open the emails. Email open is the first action by user in their journey to engage with your email. This metrics is calculated as Total Opens divided by Delivered, expressed as percentage.
  9. Total Clicks or Clicks - Total number of clicks on any link in the email is counted in this metric.  Keep in mind that a click does not mean that a person landed on the intended destination of the link hence you will likely see a discrepancy in this metric, as shown by your ESP, and the number shown in your Web Analytics tool. There are multiple factors that could lead to a click but not a visit to the destination. If one recipients clicks on multiple links then each click is counted in this metric.
  10. Unique Clicks – Unique Click counts the number of unique recipients who clicked on one or more clicks. Unlike Total Clicks, Unique clicks counts each person only once, no matter how many links that person clicks.
  11. Click to Open Rate – It measures how effective your newsletter content is in driving people to take actions. It is calculated as Unique Clicks divided by Unique Opens, expressed as a percentage.
  12. Total Click Through Rate – It is calculated as Clicks divided by Delivered, expressed as a percentage. If a person clicks on 2 links then the number of clicks will be 2. Considering that one person (email recipient) can click multiple links in the email, this number can potentially go over 100%.
  13. Unique Click Through Rate – It is calculated as Unique Clicks divided by Delivered, expressed as a percentage. Even if one person clicks on multiple links, only one click is counted in this calculation. Keep in mind that if someone talks about Click through Rate then they are referring to this metrics. This is also used for industry benchmarking by various vendors.
  14. Email Conversions – Email Conversion is defined as the count of action that you want the visitors to take when they arrive as a direct result of a click on the email. Some examples of conversions are – purchase, download a whitepaper, sign up for an event etc.
  15. Conversion Rate – It is calculated as Number of Email Conversions divided by Delivered, expressed as a percentage. Some vendors use the sent metrics as denominators and in some organizations I have seen the Unique clicks (visits in the Web Analytics tools) used as the denominators. (also see, 21 Metrics to Measure Online Display Advertising)
  16. Unsubscribes – Number of emails recipients who chose to unsubscribe from your future mailings. This number is available in your ESPs report.
  17. Unsubscribe Rate – Unsubscribes Rate is calculated as Unsubscribes divided by Delivered and is expressed as a percentage. It measure the effeteness 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.
  18. Email Complaint or Spam Complaint – Number of email subscribers who have marked your emails as Spam. This number is readily available in most of the ESP. SPAM complains can totally kill your email marketing so this number should be watched closely and steps should be taken to ensure that you have users permission to market and are sending the relevant messages at the right frequency. This number should be available from your ESP
  19. Email Complaint Rate/Spam Complaint Rate Number of emails complaints divided by total emails delivered, express as a percentage.
  20. List Growth Rate – Measures, how fast your email list is growing, it is the net results of new subscribers minus the unsubscribes and email/spam complaints. You have to make sure that your list continues to grow rather go in negative direction. Growth (new subscribers – unsubscribes- email complaints) divided by total list size is your growth rate. Your email marketing program depends on List Growth so watch this number closely and take actions to actively grow your email list.
  21. Forward Rate/Share RateThis measures the emails forwarded (shared) by your recipients to their friends/contacts. It is calculated as number of forwards divided by number of emails delivered and is expressed as a percentage. It provides a view into the effectiveness of your email in not only engaging your recipients but also driving new subscribers, people who become of your brand as a results of receiving emails from their friends. This number is available in some ESPs.
  22. RevenueThis measures the Revenue generated as a direct results of email. Several version of Revenue as a KPI are
    1. Revenue Per Sent – Revenue attributed directly to the email divided by number of emails sent. This is also sometimes expressed in terms of Revenue Per 1000 (RPM).
    2. Revenue Per Click – Revenue attributed directly to the email divided by number of unique clicks.
    3. Revenue Per Open ­ – Revenue attributed directly to the email divided by number of unique opens.Revenue numbers won’t be available in your ESP but can be tracked in Web Analytics tools for online sales.
  23. CPM – CPM stand for Cost Per Mile (1000 in Latin). This is generally used when you rent/buy emails list from third parties. It is the cost of renting 1000 email address and is calculated as (Cost/Emails)*1000. This rate should be provided to you by the vendor from whom you are renting the list. If not provided then you can use the above calculations.

Here are few more email marketing posts that you will like:

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 15 Things to Test in your Email Campaign
    This post talks about 15 things you can test today.
  6. Targeting Cart Abandonment by Email
    Targeting Cart Abandonment is a great way to drive conversions however, use incentives/offers cautiously.
  7. 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.
  8. 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.
  9. 7 Ways to Create Relevancy in Emails
    7 tried and tested ways of creating relevancy in emails are described in this post.
  10. Relevancy Matters in Email Marketing
    This post shows an example of an email that missed the opportunity to convert.

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9 Reasons Why Your Facebook Post Engagement Is Low

Have you wondered why you are getting a very low engagement on your Facebook posts?  Here are nine common reasons that result in low Facebook post engagement and tips on how to fix them.

  1. You are posting on wrong day and time – You should time your posts according to your audience’s (fans/targets) most active time on social media. If you are posting your messages when majority of your audience is not active then you are not achieving the maximum benefit from your posts. Below is an infograph that is based on analysis conducted by Bridge.com,  which provides general information about the best time for Facebook posts. social-media-timingsHowever, rather than blindly accepting these suggestions, you should use your own data to figure out the best day and time to posts. There are several tools that will allow you to see when your audience is most active. For example, simply Measured provides you stats such as “Top Day For Comments” and “Top Time For Comments”.simply-measured
  2. You are posting too many or too few posts – As shown by the Track Social (image below), the more you post in a day the lower is the engagement. According to SocialBakers.com, if you post fewer then 2 posts a week, you will not engage your audience enough and you will lose engagement. If you post more then 2 per day (as a brand) you also will typically lose engagement. That means the ideal number is between 5 – 10 posts per week as a brand, and as a media company, this is typically 4 – 10× higher, as news are information people engage with all day long. However, you should not just rely on industry data, instead try to look at your own data to figure out the best frequency for your posts. ResponsePostFrequency_Response-Score1

 

 

  1. You are not posting engaging messages – Before preparing your post, think about who are you trying to reach and why will they care about what you are posting. Give them a reason to engage with your posts. If you a grocery store and promote a can of beans at regular price, then do you think you will get any engagement? Give them something to engage about. Give them more than just an image of the product. May be show some urgency on why they should click on the image, watch the video, click on the link, share or comment. Think about other ways to prompt then to take actions – Is there a limited time offer? Is this a limited edition product? Is this fresh crop? Here is an example of two post by PCC Market in Redmond:no-urgency-general-product

 

This post had just 22 likes even tough the page has 45,800 fans. Why is that? Likely because there is nothing for fans to get engaged with?

shows-urgency

This post on the other hand a lot higher engagement (though it can still be improved). There is a sense of urgency here “Seasons First Catch of fresh halibut” and there is link to halibut recipes (a call to action, see below).  Also, it is possible that PCC has more halibut lovers than mushroom lovers. The key is to understand your audience and give them something relevant and engaging.

  1. There is no call to action or links – Call to actions prompts audience to engage. Ask and you shall receive. Ask them to click on a link, like a photo, participate in the giveaway are some of the examples to get you fans/followers to take action. The post of mushrooms above has no call to action. What is PCC expecting from the fans? Just posting a picture is not going to work, provide a call to action.
  2. You don’t have the right fans/followers – This generally happens when you pay to acquire fans. People who do not like your page organically are less like to be engaged with your posts. Also, paid Fans not always genuine, according to Huffington Post, you might be getting fake users to like your pages.
  3. You are relying on organic reach – Organic reach has been declining in Facebook. According to Oglvy report, the organic reach was about 6% for pages less than 500K fans and 2% for pages with over 500K fans. This reach is a lot lower today. Lower reach results in lower engagement. This means that if you want your fans to see your post then you will have to pay Facebook to put your post in front of them.Organic-Reach-Chart
  4. You are targeting the wrong people – As you decide to promote your post by using paid ads on Facebook, you might be trying to maximize reach (within you budget) and in doing so might be reaching people who are not likely interested in your brand/product/post. In this case the impressions of your paid post are increasing but you are not getting any clicks/like/comments/share.
  5. Your content looks too much like an “Ad” – You are pushing ads for your brand and products and your posts look too much like advertisements. People are ad blind, according to Techcrunch article,  6 in 10 people totally ignore the ads. Do not just push ads, follow tip on this page and make people engage with your post.
  6. You are not using video – Photos used to be the king of engagement on Facebook, now pretty much everybody is using them. According to analysis done by Quintly, videos generate more engagement followed by photos. engagement-by-type

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Other Social Media posts that you might have missed:

Three Tips for Choosing the Colors for Data Visualization

colorsColors can add to your data visualization and make the story stand out or they can distract the audience from the main message. It all depends on what colors you chose and how you use them. In this post, I am listing three things to keep in mind when creating your next data visualization. I am not guiding you specifically on what colors (hue, value and chroma) to use but three things to keep in mind when selecting the colors:

  1. Use conventional colors:  Generally red color means negative or a bad value and green means positive or a good value.  Choosing the default colors as presented by your visualization tool might not convey this meaning in all the cases.  Say, for example in Tableau, when you choose the default “Red-Green Diverging” color from the pallet, the red represents the smallest number while green represents the largest number, and it changes from red to green for the values in between. This generally works fine.  Where this becomes an issue is when smaller numbers are actually better than the larger numbers. For example, when you are showing Cost Per Click, lower is better so it should be Green while higher numbers are bad, hence they should be Red. Leaving the default will show low CPC as red, while higher CPC will be green, this will convey the wrong message to someone who is just glancing at the visual. To fix this issue in this case, all you have to do is just check the box, titled “Reversed” to reverse the colors, now Red will be used for higher value.
  2. Don’t use too many colors: Using too many colors can distract the consumer of the visualization from the main message. Minimize the number of colors you use in your visualization. (See guidelines for selecting colors section in “Expert Color Choices for Presenting Data” paper by Maureen Stone)
  3. Draw attention to the main message:  Make sure the color combinations you chose enables you to make the main message to stand out. For example, white on black will stand out while grey on black might be lost.

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5 Data Quality Issues To Watch Out For

mapWe all know that wrong data leads to wrong analysis and hence can cost a lot of money.   In this post I am highlighting 5 issues that lead to wrong data and hence wrong analysis.  Make sure you take care of these issues before spending any time on analyzing and putting your presentation together.

  1. Manual entry by end users – When you rely on the end users/customer to enter the data in the free form you will get lot of variations of the data. For example, when you ask them to enter the city, you can get variations such as Redmond, Redmond WA.  Redmond (Seattle), Remond etc.  Doing any analysis on the city level will pose an issues since you have several variation of the same city. Unless you have thoroughly cleaned and accounted for every possible variation you will not have the right analysis. In order to avoid such issues, wherever possible provide the choices via drop down or auto-fill rather than letting users type in the answers.
  2. Manual entry by someone in the organization – Though this is more controlled than letting end users enter the data, you still have issues similar to number 1 above.
  3. Excel sheets (calculations) – This becomes an issue when you have lot of calculated columns and some of them are dependent on the other calculated columns and sheets.  One simple mistake can cascade to multiple columns and can mess up all your analysis.  Whenever possible, do not rely on calculated columns (prepared by someone else) in excel sheet, just use the raw data and do your own calculations so that you can stand behind them.
  4. Data Imports, connections and processing – In most companies the data resides in various places – databases, excel sheets, flat files Hadoop, 3rd parties etc. For you to get a 360 views you will need to collect and combine the data for all the sources. The data corruption can occur at several places including but not limited to mapping wrong keys, missing some key data, writing wrong queries, importing partial data etc.  You should always verify the data that you are getting and make sure that it is clean and complete. Since there are several owners of the data this is not always an easy task, particularly in the large organizations.  There is not much that you can do on daily basis to verify the quality of the data, but make sure you understand the underlying data sources and have good understanding of the process that is used to combine the data.  Make sure that you in loop on any changes that are being made to the data sources and the process. You can not afford for your raw material (data) to be of a low quality.
  5. Visualization tools – You expect these tools to work, don’t you? However be careful and double check your calculations before you present your data.  I recently had two issues that made me believe that there are many of you who will run into these issues and might present the wrong analysis.
    • When you use averages makes sure that you are using the right columns.  Average of an average is not the same as average by summing the values in individual rows.  Recently I ran into a situation where CPM (Cost Per Thousand Impressions) was already calculated in the excel sheet (see Issue no. 3 above).  When that data was brought over in Tableau, the analyst, in an effort to find average CPM, used the calculated column to compute average CPM.  Everything looked good on the surface but it was wrong since it calculated average of an average.
    • When using a map make sure you use the correct values of Longitude and Latitude. I saw an example where the map showed up perfectly, however a quick quality check showed that the average value for a state was more than the individual values of all cities in that state, which is not possible.  On further investigation we found that the issue was with the way Longitude and Latitude were used to render that map. Once the issue was fixed, everything worked fine.

I would love to hear from you if you have encountered these or any other sources of data quality issues.

One costly email mistake that you can easily fix

Are you loosing your email subscribers right after they are signing up? If yes then you might be making a similar mistake that I encountered recently. Here is what happened to me:

I submitted my info on coolinfographics.com to download a free chapter of the book. After I filled the form, I got a message that I will get an email with a link to the download.  I eagerly waited for the email to arrive. As soon as I got the email, I opened it and quickly clicked on a very prominent and long link. I was expecting to see a page where I will either be able to download the chapter or my download will automatically start. Instead I got the following message:

unsubscribe-1

What???? What just happened?

Turns out that the long prominent link in this email was not the link to download the sample chapter, instead it was an Unsubscribe link.  So I accidentally unsubscribed from the mailing list I subscribed only few minutes ago.  I am sure, I am not the only one who has done that. I wonder how many subscribers is this site is losing due the design of this email?

unsubscribe-2

Here are two mistakes in this email

  1. The unsubscribe link is bigger and more prominent than the actual download link (main Call to Action).  My eyes directly went to the long link and without even thinking twice, I clicked on it.
  2. Transactional Emails do not require you to have an unsubscribe link (See http://www.spamresource.com/2009/12/is-unsubscribe-link-required.html). Since this is a transactional email so you don’t need give an option to unsubscribe.  You can argue that it is a best practice to provide an Unsubscribe link. Sure if you want to provide an option then make it a small in font and length.

Fixing the problem:

Simple solution is to remove the attention from Unsubscribe link and make the main Call to Action (Link to Download) stand out, see below for a revised version:

 unsubscribe-3What do you think? Questions? Comments?

BTW: If you are interested in data visualization then go ahead and check the sample chapter or buy the Cool Infographics: Effective Communication with Data Visualization and Design at Amazon.

5 Reasons Why Your Display Advertising Is Not Working

Image Source: goldspotmedia.com

Image Source: goldspotmedia.com

Are you one of those advertiser, who is struggling to understand why your Display Advertising is not providing the desired results?  If answer is yes, then this post is for you. Below are 4 most common reasons why your display advertising might not be working.

  1. Ad Views: According to a study by Sticky,  77% of ads are never seen by people. Even when the ad is considered viewable, meaning it is within viewing area, only 55% ads are actually viewable. Which results in a very lower click through rate, the average banner CTR is about 0 .1% and declining.
  2. Spider and Bot Ad Clicks:  Spider and bots, instead of humans, make up a significant amount of clicks on the ads. All these spiders do is click on an ad, land on your site and then leave causing millions of dollars in fraudulent clicks.  As a result you will either see a very high bounce rate on your pages and/or mismatch in the clicks reported by ad network and visits reported by your Web Analytics solution.  In 2012, a start-up reported that about 80% of their clicks from Facebook ads were by spiders. Another study found that 20% -90% of clicks on some sites were via spiders. I also showed an example of a bot in my post, 4 Reason Why Your Bounce Rate Might Be Wrong
  3. Fat Finger: Over 35% of the ad clicks on Mobile are by accident, again causing high Bounce Rate.
  4. Mismatched Landing Experience:  Make it a seamless and consistent experience from your banner to conversion. Users don’t have time so make it right the moment they land on your site. For example, If a banner ad promotes “Free Trial” then make sure landing page make it easy for user to sign up for the free trial. Don’t expect the users to click through to your site to find where the “Free Trail” page is.  Mismatched landing page and ad experience leads to High Bounce Rate and Low Conversion Rate.
  5. Site Speed: Slow site speed breaks visitors flow from a display ad to your site. If it takes too long for the page to load then the visitor will be gone before she sees the full page. In this case you will see clicks but not visits and high bounce rate. Fractions of seconds can make a huge difference in the performance of your advertising.

21 Metrics to Measure Online Display Advertising

In this post I am listing the 21 metrics to measure the success of your display advertising.  Most of these are also applicable, with some variation, to other forms of advertising such as Paid Search, Social Media Ads, Print and email. I will cover these other channels and mediums in the future posts.

  1. Impressions – It is the number of times your ad is displayed. The number by itself does not hold much value but it is a metric used to calculate other metrics and KPIs. Keep in mind that an impression does not mean that someone actually saw the ad, it just that the ad was shown on a web page/app.
  2. Reach –This is the number of unique people (generally identified by cookies) that were reached by your ad. This number is always lower than the impressions because your ad is generally shown to same person (cookie) multiple times.
  3. Cost – The total cost of running the ad campaigns.  This is calculated differently by different tools and organizations. Some use actual media cost while other use a fully load number that includes the agency cost, creative cost etc. Whichever number you use, be consistent in your approach. If you are going to do comparisons with CPC models such as Paid Search then I suggest using the actual media cost. Most of the publicly available benchmarks are based on actual media cost and are expressed in CPM (explained later in this list).
  4. Engagement Rate or Interaction Rate– This applies to the Rich Media Ads, where a user can interact with the ad without leaving the Ad unit/widget.  Engagement Rate is the percentage of interactions per impression of the ad unit and is calculated as (Number of Interactions/Total Impressions)*100%.
  5. CPM – This is the cost for 1000 Impressions of the ad unit. Display advertising is generally sold on CPM basis. (For more information on CPM, see  Cost of Advertising: CPM, CPC and eCPM Demystified).
  6. Clicks – Number of clicks on an ad unit that lead to a person leaving the ad unit.  Keep in mind that a click does not mean that a person landed on the intended destination of the banner ad click. There are multiple factors that could lead to a click but not a visit to the destination (I won’t cover those here but am happy to discuss over email or a call).
  7. CTR (Click though rate) – It is the number of Clicks generated per impression of a banner ad. This number is expressed as a percentage. CTR = (click/impressions)*100%
  8. CPC – Cost per Clicks is the cost that you pay for each click.  Generally, display advertising is sold by CMP (see above), you can easily convert the cost in to Cost Per Click to compare it against other channels such as paid search. Cost per click is the effective amount you paid to get a click.  It is calculated by dividing the cost with number of clicks.  CPC = Cost/Clicks. Sometime this number is also referred as eCPC (effective Cost per Click).
  9. Visits – As stated above in the definition of clicks, not every click turns into a person landing on your destination (generally your website). Visits measures the clicks that did end up on your site.  (For more definition of visits, please see Page Views, Visitors, Visits and Hits Demystified)
  10. Visitors – Visitors metric goes one step ahead of the visits and calculates the number of people (as identified by cookies) who ended up on your site as a results of the clicks on the banner ads.
  11. Bounce Rate – Is the percentage of visits that left without taking any actions on your site. It is calculated as Number of Visits with one page view /Total number of visits resulting from the display ads. (Bounce Rate Demystified for further explanation).
  12. Engaged Visit Rate – Generally this is opposite of bounce rate (though you can have your own definitions of engagement).  It measure the quality of the visits arriving from your display advertising. You can calculate Engaged Visits as  (100 – Bounce Rate expressed as percentage).
  13. Cost/Engaged Visit – This is effective cost of each engaged visits. It is calculated as total Cost divided by number of engaged visits.
  14. Page Views/Visit – Page views the number of pages on your site viewed by each visit. With a lot interactions happening on one single page, this metrics is losing its value. However, for now, it is still a valuable metric for ad supported sites.
  15. Cost/Page View – As above, this is valuable metrics for ad supported site to figure out the cost of generating on extra page view.
  16. Conversions – Conversion is defined as the count of action that you want the visitors to take when they arrive from you display ads. Some examples of conversions are – purchase, signup for newsletter, download a whitepaper, sign up for an event, Lead from completions etc.
  17. Conversion Rate  – This is the percentage of visits that resulted in the desired conversion actions.  Conversion Rate = Total conversions/visits*100. If you have more than one conversion actions then you should do this calculation for each one of the action as well for all the actions combined.  In case of Leads, you can take it one step further and calculate not only the “Leads Generation Rate” (Online Conversion Rate) but also Lead Conversion Rate, which is, Leads that convert to a customer divided by total leads generated.
  18. Cost per Conversion – This is the Total Cost divided by the number of conversions achieved from visits coming via display ads.
  19. Revenue – This is total revenue that is directly attributed to the visits coming from display advertising. It is pretty straightforward to calculate in eCommerce but gets a little tricky when you have offline conversions.
  20. Revenue per Visit   – Shows the direct revenue achieved per visit originating from the display advertising. It is calculated as Revenue Generated from Display Ads divided by the total Visits.
  21. Revenue per Page – This is useful for ad supported business models. This is sometimes expressed as RPM (Revenue per thousand impressions of ads) = (Total Ad Revenue/Number of page views) * 1000

Note: In addition to Clicks, you can also looks at View Through and calculate your other related metrics by view through.  View Through is sum of all the cookies that visited a page that showed your ad on it, and then landed on your site. The assumption, in this calculation, is that you landed on the brands site because of that ad exposure.

 Where can you get these metrics from?

  • Impressions, Reach, Cost, Engagement Rate, Clicks, CTR and CPC data is available from your agency or ad server tool.
  • Visits, Visitors, Page Views, Bounce Rate, Engaged Visit Rate, Conversion, and Conversion Rate are available in your Web Analytics tool.
  • Revenue is available in either your Web Analytics tool or other offline sales database.
  • Cost/Conversion, Cost/Engaged Visits, Cost/Page view and Revenue/page are calculated using data from multiple tools.

Questions/Comments?

4 Reason Why Your Bounce Rate Might Be Wrong

Bounce Rate is generally defined as single page visits. These are the visits that leave the site without going any further than the landing page.  A very common approach to landing page analysis is to start with Bounce Rate and see if it is a problem before diving deeper into the page/site. However, the number that your tool is providing you might be wrong. Relying blindly on the number provide by your Web Analytics tool might lead you into the wrong direction. Below are 4 reasons why your Bounce Rate might be wrong

  1. In Page Actions – If you have certain actions, such as video plays or windows that popup with JavaScript then the chances are that you are not tracking them as valid site interactions. In this case, even though the visitors will take one of the desired actions i.e. watch the video or click on a link to launch the popup window to fill a form etc., your Web Analytics tool will count these visits as single page visit, thus inflating your Bounce Rate.
  2. External Links – If you have a lot of external links on you landing page e.g. “Like Us On Facebook”, “Buy this book on Amazon” etc. then you are purposely taking visitors out of your landing page but you might not be counting these clicks as valid site interactions thus inflating your Bounce Rate, as explained above.
  3. Profile Configuration:  If you build a tracking profile of only select few pages on your site then any views of pages outside those select few are counted as “external links” (see above). For example, if you have 3 pages on your site, home.html, products.html, services.html but your profile only tracks home.html and products.html, then a click to services.html from any of these pages will be counted as an external link and hence counted as bounce if those were the only two page views that happened in the visit.
  4. Spiders and Bots – For a long time Spiders and Bots were not a big issue for JavaScript based Web Analytics solutions, as very few spiders/bots executed JavaScript tags but now more and more of spiders/bots execute JavaScript thus inflating your visits counts. Many of these spiders only execute one page on the site, thus inflating your Bounce Rate as well.  Spiders and Bot seems to be an even bigger problem when major source of your traffic is Banner Advertising (Display Advertising) or Paid Search Ads.  See below for an example of a bot that might be messing up your Bounce Rate.

bot-traffic

 Now that you know that your Bounce Rate might be wrong, do your own calculations and come up with the right number before you start redesigning your Landing Page.  Recently, I came across a situation where all of the above applied. The Web Analytics tool reported that the landing page had over 90% bounce rate, after adjusting for above factors, we ended up in 50%+ range, which is still a little higher than industry average but not as bad as it initially looked (see average bounce rate).  A Bounce Rate of 50% calls for different analysis and actions than a Bounce Rate of 90%.

Read More Bounce Rate Posts

3 Tips for Expanding Tweet Reach and Engagement

Twitter feeds keep flowing with over 9000 tweets every second (Source: http://www.statisticbrain.com/twitter-statistics/). Unless your followers are constantly watching their twitter stream the chances are that your tweets will not be seen by a lot of them.  Below, I have listed three tips that will ensure that your tweets/content gets noticed and reaches most of your followers.

  1. Tweet Same Content Multiple Times in a Day  – There are a lot of people like me who log into twitter few times a day (or after a gap of few days) and then and do a quick scan of timeline (or search).  They go back few hours in their twitter timeline and if your tweet did not happen to be in the timeline or searches at that time then they never see it.  Keeping this in mind, you need to tweet same content multiple times in a day to make sure your tweets are in the timelines of most of your followers when they login to twitter. In my post “Best Time to Tweet”, I suggested following timeline to tweet (this is just a suggestion and you should figure out your own timeline based on your followers and goals)
    1. Tweet at 9:00 AM PST (If all of your follower are in one time zone then tweet at 9:00 AM in your time zone).
    2. Tweet again the same message at 1:00 PST (4:00 EST) – (you might skip this if your followers are local.
    3. Tweet again the same message at 4:00 PST( If all of your follower are in one time zone then tweet at 4:00 PM in your time zone).

    In addition, I suggest adding another one later in the evening.

  2. Tweet Same Content on Different Days – If you have content that is evergreen then it make sense to tweet it again. Just like above, it might take few tweets over few days/months to get your tweets noticed by your followers. Additionally, tweeting your content again after few days/months will put your content in front of your new followers and those who might have missed it previously.  However, going overboard with such strategy can potentially cause issues with some of you long time and ardent followers as they will see the same message over and over again. I use this strategy to tweet my old blog posts, which results in new retweets and followers. (I do it automatically- more on this in future).
  3. Add Images to your Tweets – Late last year, Twitter started showing full images (instead of a link) in the timeline, just like Facebook does. A study (http://blog.bufferapp.com/the-power-of-twitters-new-expanded-images-and-how-to-make-the-most-of-it) showed that tweets with images got 150% more rewteets than tweets without images.  I suggest, you start including images in your tweets, when it make sense, and do your own tests to see how images affect the engagement with your tweets.

Follow me on twitter at @anilbatra

5 Reasons To Use Google Experiments

Google Experiments is an A/B testing tool that is available within Google Analytics interface.  This post is not about what A/B testing is, why you should conduct A/B tests and what other tools are available but really to make a case for using Google Analytics as your testing platform.  I am not getting paid to write this or have any affiliation with Google. This post is in response to a question I received from a reader of my blog.

  1. Free –There is absolutely no cost for the Tool. You can’t beat Free, it is a great way to start with A/B testing and learn about how testing works. I strongly recommend that you try this tool before moving to more sophisticated paid tools. Additionally, if you are just trying to make a case for Testing within your organization then cost does become a barrier and this tools removes that barrier.
  2. Easy To Setup – Easy to use wizard allows you to choose the pages to test and setup test parameters.
  3. Easy Implementation – Once you are done with setting up (point 2 above) the page(s) you want to test, you have to implement some code on your site.  It may sound daunting but that code is very easy to implement. Google provide you the code after your setup is done and all you have to do is stick that on your pages.  Since you already have Google Analytics installed, you are already half way through. Easy setup makes it easy for you to cross the IT/development team barrier.
  4. Setting up Objective– If you have already defined the Goals in Google Analytics, you can use them as the objective of your test. During your setup you can pick a goal that you have already defined in Google Analytics as your desired optimization objective. If you have not defined them already then you can quickly define them while setting up your test.
  5. Segments – Many tools just gives you the final results based on the data of entire population or based on some predefined segments.  In case of Google Experiments, you can pick Segments that you have defined in Google Analytics and see how each variation is performing for each of your segment. Since not all segments behave in similar fashion this kind of analysis helps you drive even more conversion by understanding which variation of your pages(s) work better for which segments.

Keep in mind that no matter how good your conversions are, there is always a room for improvement and A/B testing helps you with it. As Bryan Eisenberg would say, Always Be Testing.