Search Results for: bounce Rate

Are Spiders and Bots your customers?

botnet-100034898-origThose who know what internet bots and spiders are, know that know that spiders and bots visit your site very day and multiple times a day.  For those who don’t know here is the definition of bots according to Wikipedia:
An Internet bot, also known as web robot, WWW robot or simply bot, is a software application that runs automated tasks (scripts) over the Internet. Typically, bots perform tasks that are both simple and structurally repetitive, at a much higher rate than would be possible for a human alone.

According to a recent survey, on an average about 51.8% of the website visitors are bots.

bot-report-2016-infographic

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Source: https://www.incapsula.com/blog/bot-traffic-report-2016.html

One assumption many digital analysts make is that the JavaScript based analytics solutions such as Google Analytics, Adobe etc. either stop bots from executing the script or filter them out before calculating the metrics.  Well, this assumption was true years ago, it was one of the selling points of JavaScript based solutions as compared to log file based solutions.  However, things have changed over past few years, many bots are now capable of running JavaScript and hence polluting your reports.  Likes of Google Analytics and Adobe Analytics will filter out the spiders and bots to an extent but considering the number of new bots that emerge every day, it is not an easy task, neither for them nor for you.  So what do you do?  Since you are not going to get 100% bot free report filter out as much as possible so the effect on your reporting and analysis is minimal.

I recently had a conversation with one of the attendees of my Digital Analytics Association (DAA) workshop at Chicago eMetrics. She told me that she gets a report every week from their digital analyst. When asked, Digital Analyst confirmed that the report does not filter out any activity from spiders and bot becuase he does not have time to remove them. She was wondering if she should worry about it and push to remove the bots from report or just accept it.

What do you think? Do you think the report she is getting is worth anything?

Unless they are selling to spiders and bots, she is not getting an accurate picture of website usage by real customers.

Make sure to ask your analytics team if they are removing bots from reporting. If not, then do not accept the reports till they have done cleanup and are paying attention to it on ongoing basis.

Comments? Questions?

4 KPIs for Measuring Email List Growth

List-AdEmail 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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Digital Marketing and Analytics Jobs

23 Email Marketing Metrics That You Should Know

541529038706138A while 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 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.
  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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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

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

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Digital Marketing Jobs

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

5 Tips for Analyzing and Optimizing Campaigns – Part III

This is part III of my post on Analyzing and Optimizing Campaigns. In part I I talked about why your campaign analysis is probably is wrong. In part II I showed an example of how obsessing over reducing bounce rate might not get you anywhere.

In this post I am going to provide you 5 tips for analyzing and optimizing your campaign. Here those 5 tips:

  1. Optimize Cost of Advertising
    Cost is dependent on how much you pay per click or pay per 1000 impressions (CPC and CPM). You have control over these cost factors. Those who are running Paid Search campaigns should already be familiar with and should be working hard to reduce the cost (CPC). Those dealing with CPM display ads should know that those rates are highly negotiable. Do you research about pricing etc., play with these numbers and see what will yield the optimal result,. Take your analysis and recommendation to your media buying team.
  2. Improve Click-Through-Rate (CTR )
    CTR depends on several factors such placement, creative, unique value proposition, time of the ad, targeting criteria. Analyzes those factors and see where you are falling short and where are the opportunities for improvement. You can pretty much test all of these and improve them.
  3. Reduce Landing Page Bounce Rate
    We looked at improving the Bounce Rate in the last post. You can reduce the bounce rate by optimizing the messages on your ads, better targeting techniques and optimizing your landing page. If your value proposition and messages are aligned on the ads and the landing pages, you will see a reduction in bounce rate. Conduct A/B and MVT on your landing pages to see what works.
  4. Optimize Conversion Funnel
    Make sure the conversion path steps are optimized and any obstacles are removed. Remove any fields that are not needed e.g. if you don’t have a use for phone number then don’t ask fo it. Streamline the process. Conduct A/B and MVT to improve the conversion funnel. Use personalization, if possible.
  5. Improve Average Order Value (AOV)
    Yes, you can influence the amount a customer pays per transaction. Use on-site recommendations to up-sell and cross-sell to drive up the average basket size and the value. Use customer data to figure out what might interest a particular customer and put those in your recommendations. I have also found that some segment of visitors just won’t convert online, they are not comfortable. If you are able to spot those customers on time and engage them via sales call center then not only the chances of conversion will go up but the AOV will go up as well. In my experience, those customers, who deal with a live person, tend to buy more versus those who complete orders online.

Just optimizing for one of the above variables might not yield the desired improvement; optimize all of them to achieve the maximum ROI.

Comments? Questions?

Follow Me on Twitter: @anilbatra
Facebook: https://www.facebook.com/TheAnilBatra

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Bounce Rate Optimization Is Not Always The Cure: Analyzing and Optimizing Campaigns

This is part II of the series on Analyzing and Optimizing Campaigns. I wrote in my previous post that when analyzing campaigns many web analysts just focus on the web analytics data. Some venture to include the cost and impression data of the campaign but they still don’t have a complete view.

In this post I will show you how their lack of complete view results in wrong analysis and wrong conclusions.

Below is the data I used in my last post. This is the type of data most Web Analytics tools provide and hence “Web Analysts” tend to use.

What is missing?

Where is the cost of products and profit margin data? Without that information, you don’t know if this campaign is successful or not. Right?

The sad reality is that many web analysts don’t have access to profit margin data and hence they look at what is available to them and start recommending A/B testing (see my post One Awesome Web Analytics Tip: Think Beyond Web Analytics). And their first target generally is Bounce Rate. Oh… look bounce rate is 50% it is too high, we need to reduce it. Right?

Wait…There is More…

Let’s assume that you are able to get hold of additional data. Now let’s see how the campaign looks if we add that data. Below I have added cost of Goods Sold data (keep in mind there are additional costs in real life).

It is evident now that the campaign is bleeding money. If your business goal is to increase conversions at any cost then you might be ok but if you goal is to increase conversions without losing money then this campaign sucks.

Ok, so what should we do now? If your answer is still bounce rate then you are wrong. Look at the data below, even with a bounce rate of 0% you will never make this a profitable campaign.

So next time get all the data before you jump to the conclusion that all you need to do is reduce “Bounce Rate”. Bounce Rate Optimization looks tempting to tackle but it is not always the cure.

Stay tuned, more coming soon on this subject.

Follow Me on Twitter: @anilbatra
Facebook: https://www.facebook.com/TheAnilBatra

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