How does a content websites make its revenue? The answer is simple and it's the same concept that magazines, radio and newspapers have adopted which is by selling ads. By selling ads, I mean the source (publisher) website displays banner ads of other target websites/businesses (advertisers) on their website based on an advertising deal which I will focus on specifically. These display banner ads are tied to a campaign that the advertisers would run on their end which can either be sending users to a homepage or sending them to conversion funnel. The advertisers measure the performance of these banners based on 3rd party ad serving tools which in most cases the publisher would also be using to track progress on their end. The aim of the publishing website is to get as many users visiting the website so that the likelihood of it making money increases. The publisher typically gets paid based on primilarily 4 deals listed below:
1) CPC (Cost per Click): This metrics specifies that if a visitor clicks on the banner and lands on the advertiser’s website, the publisher of that ad will get a specific price. More the visitors, more the clicks and eventually more revenue. It is measured as CPC (Cost per Click).
2) CPM (Pay per Thousand Impressions): This deal is primarily based on the volume of traffic landing on the website. The publisher will be paid X amount per 1000 Impressions (Page Views) on the page hosting the Web Banner. The deal can range from 50 cent CPM (Cost per Thousand) to $50 depending on the publishing website.
3) CTR (ClickThrough Rate): This metric captures how many times an ad was clicked compared to how many impression were served. The higher the CTR, the more engaging the media content. This metric is typically calculated along with the website or Mobile app conversion rate which is often used as the final success criteria
4) CPA (Cost per Action/Acquisition): This is my favorite. Based on this deal, the publisher will only be paid if a visitor from its website performed a predefined action like converted into a customer by buying from the advertiser. In this case, the publisher will be paid a portion (0-50%) of the cost of the product.
5) CPV (Cost per Visit):Though this is not a very common metric, through this an advertiser is able pay the publisher based on the number of times visitors have visited the page. (A Visit is a session on a website which occurs within a time frame for the same Unique Visitor. The universal web analytics time frame standard set for Visits is 30 minutes but it can be changed).
I can add one more to this list which is MGR (Monthly Gross Revenue): This is more applicable to online Poker business. According to this deal, the publisher will be paid a share of the monthly gross revenue generated by a Poker player.
These banners can be targeted based on country (I.P.), search terms, source of traffic, day parting (Serving Ads during different time periods) etc which is made possible by tools like DoubleClick etc and can be used by both publishers and advertisers to track banner performance at their end. These tools help both parties to track display banners and manage campaigns like advertising deals and landing traffic.
All in all banners are an integral part of the display advertising business model and they are here to stay. Here's my article on different kinds of banners present in the industry today.
Sunday, January 27, 2008
Sunday, January 20, 2008
10 Ways to lower Drop off Rate in a Conversion Funnel
My last article mentioned ways to measure the drop off rate but through this article I’ll try to list ways by which you can reduce the drop off rate. Drop off Rate and Conversion Rate are two sides of the same coin as the below points would relate to both equally. A Conversion Funnel can start from the homepage, a search results page or a campaign specific page. Now let’s look at some of the ways by which we can reduce drop off rate:
1) A/B or Bucket Testing: A/B testing means testing many variants of the Conversion pages (Homepage, Product View etc) by sending a proportion of traffic on each page and eventually determining which page led to the minimum drop off or the highest Conversion. The important factor to keep in mind while conducting A/B test is that one of these pages should be the control (the original page). We can test pages by changing button color, size, text, placement etc or by modifying forms in order to minimize the customer drop off during the Registration process. Eventually by using a unique page name/bucket page name we should be able to determine which page performed the best.
2) Segmentation Tests: These are different than Bucket Test because in Segmentation we are looking to target certain segments of customers/users. We target customers based on their status (New user, not yet registered and Registered Customer). The “not yet registered” customer segment should see the login page so that he can continue the Conversion process where he left it. Similarly new users would see a different page and registered customers see a page only listing products of their choice. We can also segment customers according to their country (I.P.), Campaign Tracker ID, Direct/Indirect source of traffic. Ultimately we want to be able to determine which segment has the lowest Drop off/Highest Conversion rate.
3) Products Out of Stock: This is one of the mistakes that online retailers might make in order to make a customer purchase a product by pretending that the product is in stock when it is not. When the customer actually believes and purchases the item then guess what he gets an error message saying “Payment failed as Product out of stock”. I’m not saying this is a common practice but this scenario is possible and when it does happen it will surely leave a bad mark on that customer and maybe potential customers. So if a specific product is out of stock, then make sure you don’t display it.
4) Detailed Product Description: One of the reasons why sites like Amazon and Dell are pioneers in Online Shopping is because they make sure they provide the in depth coverage of the product. The users should also be made well adept with the specs of the product before they enter the cart with detailed textual description along with pictures. Sometimes including user comments also help.
5) Hyperlinks to Popups: While in the Conversion Funnel, a user might be distracted to click on a link/button that he finds appealing and this is the time when most customers leave the page. So in order to minimize that point of drop off, try to create links that open a new browser window/popup in order to retain the users on that page. It is however a highly debatable point because we need to be able to measure the links which lead to the customer exiting from the Funnel (Exit links). So I would suggest you to include links to Terms and Conditions, Privacy Policy, Product Specs and others in the form of popups so that you do not loose the customer in case he doesn’t go back in the Conversion process.
6) Trust: If your company is a public company/Fortune 500 company, always mention it on the Conversion funnel pages. In case of other companies, be sure to display a secure page icon (Verisign) on the encryption pages in order to generate a sense of trust for the customers. Having a privacy policy and terms of conditions page is also very important. A clearly defined Privacy Policy goes a long way in making the user feel secure before making a payment.
7) Shopping Cart Indicator: It is very important for visualize the Shopping Cart through a Step indicator on Conversion Cycle pages. As soon as the user selects a product you need to make him feel as if he’s entering a Shopping Cart and also listing what step it is so that he knows exactly where to go next.
8) Simple Registration Process: Try to make the registration process as simple as possible and try to minimize asking questions about PII (Personally Identifiable Information). Make sure the spellings are correct in the Registration process as it can really leave a bad taste for the user experience. Include as much predefined information as possible to reduce the amount of information the user has to fill in. For e.g. If a user has selected UK as the country then if possible auto populate the City, County, Country Code in the drop downs/text boxes and let the user select from that list rather than him entering it manually. Also radio buttons can work better then drop downs in most scenarios especially if there are only 2 choices.
9) Search Functionality: It is usually not advisable to include a search text box in between the Registration process but having it would only make things better. I say this because if a user wants to search for any information then he might want to exit the cart and go back to the Homepage. But if you have a search box which displays results in the form of a popup then you reduce your chances of jeopardizing your Funnel process by retaining the user on that page.
10) Web Analytics Tool to Measure KPIs: Finally the most important step is proper configuring of your Web Analytics tool to measure relevant KPIs or metrics. The Web Analytics code implementation according to the pages is of pivotal importance which hold true for Bucket Testing or Segmentation. The KPIs/metrics that might be of up most importance in case of the Conversion cycle can be Drop off Rate, Conversion Rate, Time spent on page, Exit Rate and Click Tracking.
These were just some of the ways that can help you maximize your ROI in terms of Conversion as there might be a lot more. I hope you like this article and if possible, let me know your thoughts about it.
1) A/B or Bucket Testing: A/B testing means testing many variants of the Conversion pages (Homepage, Product View etc) by sending a proportion of traffic on each page and eventually determining which page led to the minimum drop off or the highest Conversion. The important factor to keep in mind while conducting A/B test is that one of these pages should be the control (the original page). We can test pages by changing button color, size, text, placement etc or by modifying forms in order to minimize the customer drop off during the Registration process. Eventually by using a unique page name/bucket page name we should be able to determine which page performed the best.
2) Segmentation Tests: These are different than Bucket Test because in Segmentation we are looking to target certain segments of customers/users. We target customers based on their status (New user, not yet registered and Registered Customer). The “not yet registered” customer segment should see the login page so that he can continue the Conversion process where he left it. Similarly new users would see a different page and registered customers see a page only listing products of their choice. We can also segment customers according to their country (I.P.), Campaign Tracker ID, Direct/Indirect source of traffic. Ultimately we want to be able to determine which segment has the lowest Drop off/Highest Conversion rate.
3) Products Out of Stock: This is one of the mistakes that online retailers might make in order to make a customer purchase a product by pretending that the product is in stock when it is not. When the customer actually believes and purchases the item then guess what he gets an error message saying “Payment failed as Product out of stock”. I’m not saying this is a common practice but this scenario is possible and when it does happen it will surely leave a bad mark on that customer and maybe potential customers. So if a specific product is out of stock, then make sure you don’t display it.
4) Detailed Product Description: One of the reasons why sites like Amazon and Dell are pioneers in Online Shopping is because they make sure they provide the in depth coverage of the product. The users should also be made well adept with the specs of the product before they enter the cart with detailed textual description along with pictures. Sometimes including user comments also help.
5) Hyperlinks to Popups: While in the Conversion Funnel, a user might be distracted to click on a link/button that he finds appealing and this is the time when most customers leave the page. So in order to minimize that point of drop off, try to create links that open a new browser window/popup in order to retain the users on that page. It is however a highly debatable point because we need to be able to measure the links which lead to the customer exiting from the Funnel (Exit links). So I would suggest you to include links to Terms and Conditions, Privacy Policy, Product Specs and others in the form of popups so that you do not loose the customer in case he doesn’t go back in the Conversion process.
6) Trust: If your company is a public company/Fortune 500 company, always mention it on the Conversion funnel pages. In case of other companies, be sure to display a secure page icon (Verisign) on the encryption pages in order to generate a sense of trust for the customers. Having a privacy policy and terms of conditions page is also very important. A clearly defined Privacy Policy goes a long way in making the user feel secure before making a payment.
7) Shopping Cart Indicator: It is very important for visualize the Shopping Cart through a Step indicator on Conversion Cycle pages. As soon as the user selects a product you need to make him feel as if he’s entering a Shopping Cart and also listing what step it is so that he knows exactly where to go next.
8) Simple Registration Process: Try to make the registration process as simple as possible and try to minimize asking questions about PII (Personally Identifiable Information). Make sure the spellings are correct in the Registration process as it can really leave a bad taste for the user experience. Include as much predefined information as possible to reduce the amount of information the user has to fill in. For e.g. If a user has selected UK as the country then if possible auto populate the City, County, Country Code in the drop downs/text boxes and let the user select from that list rather than him entering it manually. Also radio buttons can work better then drop downs in most scenarios especially if there are only 2 choices.
9) Search Functionality: It is usually not advisable to include a search text box in between the Registration process but having it would only make things better. I say this because if a user wants to search for any information then he might want to exit the cart and go back to the Homepage. But if you have a search box which displays results in the form of a popup then you reduce your chances of jeopardizing your Funnel process by retaining the user on that page.
10) Web Analytics Tool to Measure KPIs: Finally the most important step is proper configuring of your Web Analytics tool to measure relevant KPIs or metrics. The Web Analytics code implementation according to the pages is of pivotal importance which hold true for Bucket Testing or Segmentation. The KPIs/metrics that might be of up most importance in case of the Conversion cycle can be Drop off Rate, Conversion Rate, Time spent on page, Exit Rate and Click Tracking.
These were just some of the ways that can help you maximize your ROI in terms of Conversion as there might be a lot more. I hope you like this article and if possible, let me know your thoughts about it.
Sunday, January 13, 2008
Funnel Drop Off/Abandonment Rate
Drop Off or Abandonment Rate measures the number of visits/visitors who left a conversion process (funnel) without completing it. Any process with 2 or more actions on the site can be considered a conversion process but what you define as a conversion depends on the purpose of your site and your business objective.
Before I continue, I want to mention that Drop Off Rate is the opposite of Conversion Rate. Conversation Rate is typically calculated as (Visits of the Last Conversion Step)/Visits of the First Conversion Step) X 100. Some of the commonly used conversion funnels are eCommerce shopping carts, registration forms or lead forms.
Abandonment Rate helps identify the steps in the funnel that are causing users to drop off. Conducting analysis of those steps will help us take necessary steps to minimize the drop offs and optimize the conversions.
There are 2 ways to calculate Drop Off Rate and each of them provide the data in slightly different ways. Both of them are correct ways to calculate and are commonly expressed as a percentage:
1) Drop off/Abandonment rate = ((Visits of the Last Conversion Step-Visits of First Conversion Step)/Visits of the First Conversion Step) X 100. Let’s assume that we want to use Product as the first step of the conversion process and that step gets 10,000 visits. But of those 10,000 only 7,000 continued to the next step of adding the product to shopping cart. Then in the next step only 2000 out of total 10,000 that started the process continue to Registration form and finally 1,200 out of 10,000 got to the final confirmation page. This means we saw 30% abandonment between Step 1 and Step 2 ie. ((7,000 -10,000))/10000)*100. Abandonment was 80% from Step 1 to Step 3 ((2,000 – 10,000)/10,000)*100. Final abandonment rate was 88% ((1,200 – 10,000)/10,000)*100. Though this calculation gives us a good idea of final drop off rate and conversion, it can be a little misleading.
2) Drop off/Abandonment rate = ((Visits of the Current Conversion Step-Visits of the Previous Conversion Step)/Visits of the Previous conversion Step) X 100. This calculation takes into account the previous conversion step and the current conversion step. In the Funnel, we see that 7000 visits are measured on the Add to Cart page (Step 2) and only 2000 continue to the Registration form so the calculation based on this formula would be ((2000-7000)/7000)*100 which is -71%.
Based on the above formulas, it looks like the first one seems better in terms of Funnel visualization but personally I like the second formula better. I say this because in the second funnel, we are only considering the respective conversion steps in the calculation and not just Step 1 (Products) because Step 1 is entirely a separate user experience. According to me, the Drop Off Rate should be calculated based on two consecutive conversion steps as they are independent of the user acquaintance on the other pages of a funnel. These 2 pages alone can determine how we can improve the conversion rate at each step as these are not based on the Products page experience. For e.g. The Registration form design and engagement is totally different than what it is on the Products page.
Here's a link to a calculator I built which includes these two calculations for you to use. Please note that the first calculation only takes in the first and last step as it only calculates the drop off rate based on the first and last steps.
Here's a link to a post I wrote to cover some steps on how you can reduce funnel drop off. I hope you like this post and would love to hear your opinion on it.
Before I continue, I want to mention that Drop Off Rate is the opposite of Conversion Rate. Conversation Rate is typically calculated as (Visits of the Last Conversion Step)/Visits of the First Conversion Step) X 100. Some of the commonly used conversion funnels are eCommerce shopping carts, registration forms or lead forms.
Abandonment Rate helps identify the steps in the funnel that are causing users to drop off. Conducting analysis of those steps will help us take necessary steps to minimize the drop offs and optimize the conversions.
There are 2 ways to calculate Drop Off Rate and each of them provide the data in slightly different ways. Both of them are correct ways to calculate and are commonly expressed as a percentage:
1) Drop off/Abandonment rate = ((Visits of the Last Conversion Step-Visits of First Conversion Step)/Visits of the First Conversion Step) X 100. Let’s assume that we want to use Product as the first step of the conversion process and that step gets 10,000 visits. But of those 10,000 only 7,000 continued to the next step of adding the product to shopping cart. Then in the next step only 2000 out of total 10,000 that started the process continue to Registration form and finally 1,200 out of 10,000 got to the final confirmation page. This means we saw 30% abandonment between Step 1 and Step 2 ie. ((7,000 -10,000))/10000)*100. Abandonment was 80% from Step 1 to Step 3 ((2,000 – 10,000)/10,000)*100. Final abandonment rate was 88% ((1,200 – 10,000)/10,000)*100. Though this calculation gives us a good idea of final drop off rate and conversion, it can be a little misleading.
2) Drop off/Abandonment rate = ((Visits of the Current Conversion Step-Visits of the Previous Conversion Step)/Visits of the Previous conversion Step) X 100. This calculation takes into account the previous conversion step and the current conversion step. In the Funnel, we see that 7000 visits are measured on the Add to Cart page (Step 2) and only 2000 continue to the Registration form so the calculation based on this formula would be ((2000-7000)/7000)*100 which is -71%.
Based on the above formulas, it looks like the first one seems better in terms of Funnel visualization but personally I like the second formula better. I say this because in the second funnel, we are only considering the respective conversion steps in the calculation and not just Step 1 (Products) because Step 1 is entirely a separate user experience. According to me, the Drop Off Rate should be calculated based on two consecutive conversion steps as they are independent of the user acquaintance on the other pages of a funnel. These 2 pages alone can determine how we can improve the conversion rate at each step as these are not based on the Products page experience. For e.g. The Registration form design and engagement is totally different than what it is on the Products page. Here's a link to a calculator I built which includes these two calculations for you to use. Please note that the first calculation only takes in the first and last step as it only calculates the drop off rate based on the first and last steps.
Here's a link to a post I wrote to cover some steps on how you can reduce funnel drop off. I hope you like this post and would love to hear your opinion on it.
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