Why there is an unspecified line item while checking Page Report in Adobe Analytics

To understand why there is an unspecified line item while checking the Analytics report with Occurrences metric, we need to understand the following definitions and scenarios.

Occurrences higher than Instances: This outcome is expected for conversion variables, as occurrences also includes the number of times the variable was defined (instances).

Instances higher than Occurrences: This outcome is not possible in reporting, as all instances are recorded as occurrences as well.

Occurrences vs. Instances : Occurrences count hits where a dimension item was set or persisted. Instances do not include hits where a dimension item persists.

Occurrences vs. Page views : Occurrences include all hit types, including page view tracking calls ( t() ) and link tracking calls ( tl() ).

The page views metric only includes page view tracking calls, and excludes link tracking calls.

While running page report(OOB) report with metric Occurrences , it is expected to get Unspecified line item because of s.tl() call which happened during the visitor journey even if the s.pageName variable is set explicitly. To overcome this it is recommended to create a custom analytics variable (prop/eVar) to capture page name into it.

Note: Subrelation is synonymous with conversion report breakdown.

Configure free CloudFlare CDN for your website | Protect your website from security threads

As the new buzz is that CloudFlare entered into Web Analytics space by announcing Free Web Analytics – Even for Non-Customers but today we will be discussing on how to get Free SSL certificate for your website with CloudFlare. Full end to end encryption with free https

Before making it secure it looks like as below:

Check the video below which show the step by step process of adding free CDN for your website from cloudflare. Additionally you will also get SSL certificate for your domain if you follow this steps.

Link : Managing Cloudflare Origin CA certificates

After making it secure it looks like as below :

Comparison Between Adobe Analytics and Customer Journey Analytics

Adobe Analytics has long been the undisputed leader in the world of Web Analytics and is still a marquee product for analyzing web and mobile app data. Just like any enterprise level product, it does come with its share of challenges.
So, is there a solution that can make these challenges go away?

YES there is and the solution to these challenges is Customer Journey Analytics. Customer Journey Analytics or CJA is an enterprise-wide analytics product that is built on Adobe Experience Platform. CJA allows us to join different data sources (online & offline) to give a complete view of our customers in real-time across channels. Please note that CJA is considered an add-on to Adobe Analytics, also available for Non-Platform (AEP) customers, and works natively with Adobe Experience Platform.

In this article, I’ll compare Adobe Analytics with CJA based on a set of standard capabilities that are common between the two solutions and highlight some of the differences.

Adobe Analytics

In this section, I’ve listed the various capabilities of Adobe Analytics and added a high level writeup explaining each of these separately. I’ve done the same for Customer Journey Analytics.

1.    Data Capture

  • Primarily takes place based on the AppMeasurement library (client-side-web), Mobile SDK (mobile app), Data insertion API and Bulk Data Insertion API (server-side).

2.   Data Usage

  • Data is stored in Report Suites usually setup to receive data globally or individually based on the requirement.
  • Virtual Report Suites (VRS) can be created to “split” data based on web/mobile, region or Business group and can be setup based on custom session timeouts, expiration and time zones.

3.   Reporting and Analysis

  • Data is visualized in Analysis Workspace or the legacy UI.
  • Workspace panel includes Freeform, Cohort, Fallout etc. options available to visualize data.
  • Calculated metrics can be created, and marketing channels can be used for further analysis.
  • Robust data export capabilities (PDF, CSV etc. formats) as well as access to raw data feeds.
  • Ability to setup alerts in case of anomalies.

4.   Identity

  • Primarily based on cookies for client-side web tagging.
  • Based on ECID for mobile app (tied to each installed instance of the app).
  • Customer IDs converted to ECID for server-side implementations in general.
  • Device graph data can be accessed via the People metric or leveraged via Cross-Device Analytics.

5.   Segmentation

  • Segmentation built into Analysis Workspace
  • Visitor, Visit and Hit segment containers available.
  • Sequential segmentation and exclusion capabilities available to users.

6.   Data Limitations

  • Limited to 200 eVars/props and 1000 events.
  • UI limited to 500K unique rows of data per month (Low Traffic).

7.   Data Classifications

  • Classifications subject to the same restrictions as the UI in terms of only classifying the top 500K rows.

8.  Historical Data Ingestion

  • Historical data sent in but out of order hits can affect the sequence of events and attribution of eVars and marketing channels.

9.   User Permissions

  • User permissions are granted via the Admin Console at a more granular level for report suites etc. at a product profile level.

10. Data Latency

  • Data can take up to 2 hours to be fully available in Adobe Analytics.

Customer Journey Analytics

Customer Journey Analytics (CJA) represents an upward paradigm shift. Clickstream data is no longer THE data source, it’s ONE OF MANY data sources. CJA makes it possible to link, define, process, join, visualize, and analyze any type of standardized data.


In this section, I’ve put CJA through the same set of capabilities as I did for Adobe Analytics. Please note that there are some features that CJA lacks compared to Adobe Analytics which the product team is working on to add support for.

1.Data Capture

  • Data needs to be conformed to Adobe Experience Platform’s XDM schema to bring in any type of data.
  • Web SDK is used for real-time data streaming and streaming API will be available for sending data server-side.

2.Data Usage

  • Data is stored in datasets created within Adobe Experience Platform and added to CJA as Connections.
  • Data Views are similar to VRS which also allow us to define data based on the type of datasets being analyzed as well as setting custom session timeouts, expiration and defining separate time zones.

3.Reporting and Analysis

  • Data in CJA is visualized in Analysis Workspace.
  • Workspace panel includes Freeform, Cohort, Fallout etc. options available to visualize data.
  • Calculated metrics can be created for further analysis, but marketing channel support is not available yet, but support is planned.
  • No current ability to export data in CJA (Workspace) but support is planned. However, Query Service and Data Access API provides the ability to export data.
  • No current ability to setup alerts but support is planned.

4.Identity

  • Tied directly to the Namespace defined within Adobe Experience Platform.
  • Custom namespaces can be defined.
  • ID can be based on anything be it cookies, CRM id, Loyalty ID or Phone number.
  • Data in the device graph is NOT available yet but support is planned.

5.Segmentation

  • Filters built into Analysis Workspace.
  • Person, Session and Event segment containers available.
  • Leverages the same standard segmentation UI/features as Adobe Analytics.

6.Data Limitations

  • Unlimited number of rows and unique values.
  • Unlimited metrics and dimensions and data in eVars/props is available in XDM format within CJA.

7.Data Classifications

  • Lookup Datasets created in Platform are not subject to any volume restrictions in terms of volume but there is a 1 GB limit which isn’t “enforced”.

8.Historical Data Ingestion

  • Any missing historical data can be uploaded into Adobe Experience Platform and then leveraged in CJA including support for out of order hits for a person.

9.User Permissions

  • Permissions are assigned at the admin level to all users by default, but support is planned to add more granular access at the data view level.

10.Data Latency

  • Data isn’t available in near real-time can be take up to 2 hours, but real-time support is being looked into.

Customer Journey Analytics (CJA) allows you to analyze your customer’s journey across channels using any data available to you in Adobe Experience Platform, leveraging the power of Analysis Workspace for rapid insights. Learn more at adobe.ly/aacja

IDCapabilityAdobe AnalyticsCustomer Journey Analytics
1Data CaptureData is captured using the App Measurement library(client-side-web), Mobile SDK (mobile app), Data insertion API and Bulk Data Insertion API (server
side)
• Data needs to be conformed to Adobe Experience Platform’s XDM schema to bring in any type of data.
• Web SDK is used for real-time data streaming and streaming API will
soon be available for server-side.
2Data Usage• Data is stored in Report Suites usually set up to receive
data globally or individually based on the requirement.
• Virtual Report Suites (VRS) can be created to “split” data based on web/mobile, region, or Business group and can be set up based on custom session timeouts and all timezones.
• Data is stored in datasets created within Adobe Experience Platform and added to CJA as Connections.
• Data Views are similar to VRS which also allow us to define data based on the type of datasets being analyzed as well as setting custom session timeouts and defining separate time zones.
3Reporting and Analysis• Data is visualized in Analysis Workspace or the legacy UI.
• Workspace panel includes Freeform, Cohort, Fallout etc. options available to visualize data.
• Calculated metrics can be created, and marketing channels can be used for further analysis.
• Robust data export capabilities (PDF, CSV etc. formats) as well as access to raw data feeds.
• Ability to setup alerts in case of anomalies.
• Data in CJA is visualized in Analysis Workspace.
• Workspace panel includes Freeform, Cohort, Fallout etc. options available to visualize data.
• Calculated metrics can be created for further analysis, but marketing channel support is not available yet, but support is planned.
• No current ability to export data in CJA (Workspace) but support is planned. However, Query Service and Data Access API provides the ability to export data.
• No current ability to setup alerts but support is planned.
4Identity• Primarily based on cookies for client-side web tagging.
• Based on ECID for mobile app (tied to each installed Platform. instance of the app).
• Customer IDs converted to ECID for server-side number, implementations in general.
• Device Graph data can be accessed via the People metric leveraged via Cross-Device Analytics
• Tied directly to the Namespace defined within Adobe Experience Platform
• ID can be based on anything be it cookies, CRM id, Loyalty ID or Phone
• Custom namespaces can be defined.
• Data in the device graph is NOT available yet but support is planned.
5Segmentation• Built in Analysis Workspace
• Hit, Visits and Visitor Containers available
• Sequential segmentation and exclusion capabilities available to users.
• Filters built into Analysis Workspace
• Person, Session and Event segment containers available
• Leverages the same standard segmentation UI/features as Adobe available to users.
6Data Limitations• Limited to 200 eVars/props and 1000 events.
• UI limited to 500K unique rows of data per month(Low Traffic)
• Unlimited metrics and dimensions and data in eVars/props is available in XDM format within CJA.
• Unlimited number of rows and unique values.
7Data Classifications• Classifications subject to the same restrictions as the UI in terms of only classifying the top 500K rows.• Lookup Datasets created in Platform are not subject to any restrictions in terms of volume.
8Historical Data Ingestion• Historical data sent in but out of order hits can affect the sequence of events and attribution of eVars and marketing channels.• Any “missing” historical data can be uploaded in Adobe Experience Platform and then leveraged in CJA including support for out of order hits for a person.
9User Permissions• User permissions are granted via the Admin Console at a more granular level for report suites etc. at a product profile level.• Permissions are assigned at the admin level to all users by default, but support is planned to add more granular access at the data view level.
10Data Latency• Data can take up to 2 hours to be fully available in Adobe Analytics.• Data isn’t available in near real-time can be take up to 2 hours, but real time support is being looked into.

Hope this article provided you with some more information and context to figure out some similarities and differences between Adobe Analytics and Customer Journey Analytics. The key points to consider would be to see if you analyze large amount of dimensional data (exceeding 500K unique rows per month), often analyze customer data across multiple channels, need to add missing historical “hit level” data after the fact or connect offline data with online with the aim to get a single view of the customer, then you should seriously consider CJA.

Difference Between Google Analytics and Adobe Analytics

It is one of the common question while opting the Web Analytics tool and doing the comparison is very common and first action done by business owners.

Google Analytics

  • Easy Client-Side Implementation using JavaScript
  • Customizable Intuitive dashboards
  • Data sharing is not very easy with other users
  • Works well with data analysis languages like R and Python.
  • CRM integration not possible
  • Free tool for the first 10 million hits, post that about $150,000 (for over 1 billion hits).
  • No dedicated customer support team
  • Free Version is available

    Adobe Analytics (formerly known as SiteCatalyst – Omniture)
  • Implementation is easy but requires some technical assistance and little programming knowledge.
  • Server Side and Client-side implementation is possible
  • Less intuitive in reporting
  • Much easier to share with other users.
  • Highly customizable
  • Market Leader
  • Third-party integration is available through various options
  • 24×7 Dedicated customer support.
  • CRM integration allowed
  • No free version is available
  • Each server call is charged

Google Analytics is good if you don’t have a large analytics and tech team, Adobe works mainly in large digital-first / e-commerce companies with dedicated analytics and tech teams. Adobe Analytics is for serious business and long term business as it is part of Adobe Experience Cloud. Adobe Analytics has a market share of 39% in Housewares/Home Furnishings, 36% in Food/Drug, 39% in Books/Music/ Video, and 41% in Mass Merchants.

How To Get NewRepeat Visitor in Adobe Analytics Easily

There are 2 methods to get this:

NewRepeat can be captured through segment or through plugin

With the help of Segment:

Basically we are looking at the visit number of the visitors: if a visitor has at least one visit with a visit number higher than 1 (2 or higher) the visitor is segmented as “returning visitor”. All others are segmented as new visitors. Be aware that this is not depending on the timeframe you are looking at rather segmenting the visitors in their whole history i.e it would be dependent on ECID cookie…which is set for 2 years

With the help of Plugin:

Using plugin you can set your own cookie and set it according to your own time, which is generally 30 days, but can be anything as per the business vertical requirement.

What tools/services Digital Analytics Professionals often use?

While tools/services one uses depend on the need and several other factors. I will share a few popular ones often used by Digital Analytics professionals.

  • Web/App Analytics – Google Analytics, Adobe Analytics, GA(App+Web, Firebase)
  • Dynamic Tag Management – Google Tag Manager, Adobe Launch, Tealium, Ensighten
  • Analysis – Excel, SAS
  • Debugging dataLayer – DataLayer Checker, GA Debugger, FB pixel helper
  • Reporting & Visualization – Google Data Studio, Tableau, PowerBI, Tibco Spotfire
  • Product/Event Analytics – Mixpanel, GA(App+Web)
  • Engagement/Marketing Automation – WebEngage, MoEngage
  • App Attribution – Appsflyer, Branch
  • Session Recording – Hotjar, Full Story
  • Marketing warehouse – Google Bigquery
  • Email – Mailchimp, Sendgrid / SES
  • CRM – Hubspot, Salesforce
  • CDP – Segment

To dig deeper into data/Tech

  • API Testing – Postman
  • Data Lake – S3, GCS
  • Data Warehouse – Postgres, Redshift
  • ETL – AWS Glue
  • Querying S3 data lake – Amazon Athena
  • VCS – Git
  • Executing code – Jupyter Notebook(Python), R Studio(R)
  • Hosting Notebooks – Google Colab
  • SQL Client – Dbeaver (connect/query DWH)
  • Editor – VS Code, Sublime T3

In the future, I will share more example, Feel free to comment that which tool you use and why.

How To Handle FPC for Multiple Domain in Adobe Analytics

No matter how many domains a company has they can use the same tracking server for all the domain which is third party cookie implementation.

But if you want the cookies to be created on the domain and want First Party Cookie Implementation then there can be two approaches to handle the situation.

Suppose : They you have 10+ different domain

Option 1:

Where we have to configure 10+ separate tracking server values for respective domains.

Option 2:

Tracking server secure value like smetrics.abc.com for all the 10+ domains – in this case, except for the main domain, the rest would become the friendly third party implementation.

Friendly 3rd-party cookies: Used primarily by organizations with multiple domains that want to use a single visitor ID across all tracked sites. For example, an organization that owns both example.com and example.net could store the cookie on metrics.example.com

As per https://docs.adobe.com/content/help/en/id-service/using/reference/ecid-library-methods.html “the reason for the shift of ECID to CNAME implementations is for persistent visitor identification, not multi-domain tracking”

Option 1 is the best choice here –

It allows for more persistent visitor identification (with option 2, we don’t get a 1st party cookie set server-side)

If there are links that lead for instance from domain X to domain Y, then use appendVisitorIDsTo method for cross-domain tracking

Option 2 doesn’t provide much benefit

First Party Cookie implementation is very much required to mitigate the impact of ITP 2.x

Find a word in a string using JavaScript

To find a word in a string using JavaScript get I will be showing 2 methods to achieve this:

Method 1:

JavaScript String includes() Method

The includes() method determines whether a string contains the characters of a specified string. This method returns true if the string contains the characters, and false if not. Note: The includes() method is case sensitive.

var str = "Hello world, welcome to the ourpcgeek";
var n = str.includes("ourpcgeek");
var str = "Hello world, welcome to the ourpcgeek";
var test= "ourpcgeek";
var n = str.includes(test);

Put the above sample code in console and see the output.

Definition and Usage

The includes() method determines whether a string contains the characters of a specified string.

This method returns true if the string contains the characters, and false if not.

Note: The includes() method is case sensitive.

Click here to see demo

Method 2:

Other method is using RegEx

Following script will find and replace:

var stringToGoIntoTheRegex = "ourpcgeek";
var regex = new RegExp("#" + stringToGoIntoTheRegex + "#", "g");
// at this point, the line above is the same as: var regex = /#ourpcgeek#/g;

var input = "Hello this is #ourpcgeek# some #ourpcgeek# stuff.";
var output = input.replace(regex, "!!");
alert(output); // Hello this is !! some !! stuff.

Following script will find and if there is match then it is show +ve number.

var stringToGoIntoTheRegex = "ourpcgeek";
var regex = new RegExp("#" + stringToGoIntoTheRegex + "#", "g");
// at this point, the line above is the same as: var regex = /#ourpcgeek#/g;

var input = "Hello this is #ourpcgeek# some #ourpcgeek# stuff.";
var output = input.search(regex);
alert(output); // Will show positive no. as there is match and the no. will be the location

Following script will find and if there is no match then it is show -ve number.

var stringToGoIntoTheRegex = "xyz";
var regex = new RegExp("#" + stringToGoIntoTheRegex + "#", "g");
// at this point, the line above is the same as: var regex = /#ourpcgeek#/g;

var input = "Hello this is #ourpcgeek# some #ourpcgeek# stuff.";
var output = input.search(regex);
alert(output); // Will show -ve number as there is no match

In the general case, escape the string before using as regex:
Not every string is a valid regex, though: there are some special characters, like ( or [. To work around this issue, simply escape the string before turning it into a regex. A utility function for that goes in the sample below:

What are Data Collection Steps of Adobe Analytics?

  1. A visitor visits a web page that contains the data collection code.
  2. As the page loads, the data collection code sends an image request (called a web beacon) to Adobe data collection servers. The image request contains the data you want to collect about the visitors’s interaction with your website.
  3. Adobe stores the data in report suites. You can log in to access report suite data and generate reports related to visitor activity on your website.

Data collection is very quick and does not noticeably affect page load times. Collected data includes page views that result from clicking the browser Reload or Back buttons. The Javascript code runs even when the page is retrieved from cache.

Processing Order of Adobe Analytics:

What is Adobe Analytics?

It’s the industry-leading solution for applying real-time analytics and detailed segmentation across all of marketing channels. Use it to discover high-value audiences and power customer intelligence for business.

What Adobe Analytics can do?

Reporting provides insights into your traditional web-based channels as well as evolving channels like mobile, video, and social networking. Some examples of marketing reports include:

  1. How many people visit your site
  2. How many of those visitors are unique visitors (counted only once)
  3. How they came to the site (such as whether they followed a link or came there directly)
  4. What keywords visitors used to search site content
  5. How long visitors stayed on a given page or on the entire site
  6. What links visitors clicked, and when they left the site
  7. Which marketing channels are most effective at generating revenue or conversion events
  8. How much time they spent watching a video
  9. Which browsers and devices they used to visit your site