Sunday, April 22, 2018

Key Adobe Audience Manager Metrics and Ratios

Each reporting system has its own methodology for calculating metrics and a Data Management Platform is no different. When I first learnt Audience Manager, one of concepts that took me a while to understand was how Audience Manager calculates its metrics and this post is intended to cover how it's done.

To begin, it's important to understand that all key metric calculation in Audience Manger is based off devices and cookies so AAM doesn't taken into account raw hits into its calculation. Below is a summary of how each of these are calculated taking into consideration the following visuals.


Trait Metrics

AAM traits are the most granular data points or signals that are populated in Audience Manager. They represent unique visitors that are calculated based off cookies or devices. Please note that by default, a trait may count the same person multiple times if that person qualified for a segment across multiple devices.


Unique Trait Realization: This is the total number of visitors that qualified for a trait on the specified time frame (1 day, 7 days, lifetime etc). This is the typically the preferred metric for gauging active visitors. An example of a trait can be visitors to a particular URL or visitors who completed a purchase. In the screenshot above, 18,981 visitors qualified for this trait during the last day and 2,791,994 visitors have qualified for this trait since it was created. 

Total Trait Population: This is the running total number of visitors that are part of this trait since creation based on the specified time frame. In this example, a total 2,539,320 visitors were part of this trait as of yesterday and 2,590,249 visitors were part of this trait in the last 7 days. The reason why the lifetime count of visitors (2,775,871) for this metric is less than that of Unique Trait Realization (2,791,994), is because this metric starts getting calculated after a gap of 24 hours compared to UTR. Please note that the TTP gets refreshed every 120 (expiration) so any user who is seen after 120 days is counted again in the TTP calculation.


Segment Metrics
Segments are built from a combination of individual traits and are shared as audiences to outgoing destinations for activation. If multiple traits mapped to a single segment have the same cookie or device, they are deduplicated at the segment level. Segments can either contain multiple traits or can contain an overlap between two separate traits among other conditional logic.


Real-time Segment Population: This the total number of users who qualified for a trait(s) based on the specified time frame. Similar to UTR, this number will change everyday based on how many users qualified for this segment. In this example above, 54,377 users qualified for this segment during the last day.


Total Segment Population: This is the overall segment population which were part of this segment based on the specified time frame. In this example, there were 4,633,044 unique visitors that were captured across multiple traits which is why the overall volume of segments is more than that of traits.


Destination Metrics & Ratios

Destinations allow segments to be mapped and shared with various outbound partners or DSPs for activated. The following metrics and ratios fluctuate everyday based on how many users have a match between Audience Manager and the DSP.




For this example, I've used an older screenshot with dummy data as I didn't want to use an example from an actual client. Please note that the following screenshot doesn't reflect what the UI looks currently and some metric names will not match entirely so my apologies.

Addressable Audience Match Rate: This is the percentage of visitors that have a device match/sync between the customer's Audience Manager instance and 3rd party partner to be activated on. It is the calculated as ratio of (Customer Addressable Audience [676,173,551]/Customer Total Audience [1,428,072,915]). The higher the match rate, the more the visitors that can be targeted in the DSP and in this example, it's 47%. To increase match rates between AAM and the DSP, the Adobe consultant turns on an ID sync in the backend. Some causes of low match rate are explained here.


Customer Addressable Audience (Devices): This is the total number of visitors that have a device match/sync between the customer's Audience Manager instance and 3rd party partner. The Customer Addressable Audience count shown in the screenshot is 676,173,551 visitors for the last day.


Customer Total Audience: This is the total number of devices that are active in the customer's Audience Manager instance. In this example, the total active devices are 1,428,072,915 which will fluctuate daily.


Audience Manager's Addressable Audience (Lifetime): This is the total number of devices that are active across all Audience Manager customers. Please note that this number will always be more than Customer Total Audience for a particular client account unlike the screenshot above which contains dummy data.


Segment Addressable Audience (Devices): The total number of users who have an active ID sync  for the specific AAM instance localized for a mapped segment. Unlike in the screenshot, this number will vary by each mapped segment which is 123,456,789 for the example.


Segment Match Rate: This is the percentage of Segment Addressable Audience/Total Segment Population. This match rate is more reflective of how many users can be targeted than the Addressable Audience Match Rate.


Profile Merge Rule Metrics & Ratios
Profile Merge Rules or PMRs uniquely identify a user across browsers or devices that allows marketers to deliver a consistent message to their customers. This is made possible by capturing the user's hashed authenticated ID across devices.



Total Devices: T
his is the total number of devices where a hashed authenticated user ID was captured in the last 60 days. In this example, the total number of devices is 3.69 Million.

Total Person: This is the number of unique users where a hashed authenticated user ID was captured across multiple devices. In this example, the number of unique users is 3.32 Million which is less than the total number of devices.

Average devices per Person: This is the ratio of Total Devices/Total People. In this example, an average user logs in across 1.1 devices which rounds up to a single device. Marketers can use this ratio to determine the total number of devices a user logs into.


Active People: This is the number of unique users where a hashed authenticated user ID was captured across multiple devices. It's the same metric as Total Person which is 3.32 Million.


Cross Device: The total number of Cross Device IDs stored for the selected Authenticated Profile since creation. It's basically the total devices in an Audience Manager Instance. In this example, it's 6,711,719. FYI, these are users captured in the last 120 days which is why they're higher than Total Devices.


Active People %: It is a ratio of Active People divided by Cross Device. In this example, it's 50%.


Some of these metrics are already explained in the official Adobe documentation in different places but I've attempted to structure and put them in one post based on my own understanding.

Sunday, April 8, 2018

Characteristics of a Successful Consultant

A few people outside of my field have often asked me about what I do professionally. My general response to them is that I work on solving enterprise client problems in the digital analytics space. I know this a general answer and can apply to different roles but this post aims to uncover what roles I (consultant) usually perform and what are some traits a consultant needs to have to do well.

So, let's start with a question. Why do companies bring in consultants? 

  • They bring in consultants to provide them with the necessary expertise on skills that they don't have
  • Identify problems that they may not be aware of
  • Bring about change as a consultant will provide recommendations impartially. This is an important one as a good consultant isn't scared of the repercussions if the recommendation is for the benefit of the customer.  

Now that we've discussed about the demand for consultants, let's take a look at some of the traits that make a successful consultant:

Passionate about Client Service: In my opinion, this is the most important trait for any consultant to have. Whether a company is B2B, B2C or both, it's the client that every business services. As they say, client is king so consultants needs to understand customer goals, expectations, and vision by listening and asking good questions. Once consultants know that, they should strive to become advocates on behalf of their clients to accomplish these goals.

Dispassionate in Providing Recommendations: As discussed above, companies bring in consultants to have them impartially give their recommendations without any fear. A good consultant knows how to tailor the message in such a way that logically explains WHY the recommendation is good for them and if they can add some sort of a ROI to it, even better!

Think Strategically AND Act Tactically: Good consultants need to be strategic (long-term) and tactical (short-term) in their thinking. A good consultant is able to perform day to day activities while working towards the larger vision by defining processes that will benefit the customer in the long run.

Know the Audience: As with analytics, it's essential to tailor analysis according to the audience. Same applies with consultants when communicating with our stakeholders where they should be able to deliver tedious details to C level executives at a high level and go into the weeds with technical stakeholders.

Set Clear Expectations: Consultants are often asked to step into projects where expectations are generally unclear and they need to make sense of the craziness. A good consultant is able to navigate the choppy waters and logically define what success looks like. In such scenarios, consultants need to have the confidence to tactfully push back on unexpected asks and work on what will make the most sense for the success of the client and project.

Master a Skill and Yet Be Broad: Good consultants not only master a particular skill but are also well rounded professionals. In my case, my primary expertise is in Adobe Analytics (along with Google Analytics) but I also work on projects requiring tag management/little bit of programming (JavaScript, Tealium, DTM, Launch and Ensighten) and data management (Adobe Audience Manager) support. The good thing about having multiple skills is that you open up additional opportunities for yourself and set yourselves apart from others.

Wear Multiple Hats: Consultants know that no two projects are going to be the same and a lot of projects won't have any kind of structure. In such cases, consultants may need to play the role of a project manager to create a simple project plan, gather business requirements, create architectural designs, write code, QA the output and finally communicate the recommendations to the stakeholders.

Be Personable and Build Relationships: While working on tough and tedious projects, it's easy to get focussed into the weeds and not engage with your customer personally. It's always a good idea to take a step back and connect with your customers on a personal level as these relationships can last a long time and you want to leave a lasting impression on them whether you're on or off the project.

There some other traits that consultants should have aside from the ones mentioned above such as: 
  • Be proactive
  • Establish themselves as experts
  • Be willing to train other and share knowledge
  • Be prepared to step out of their comfort zones
  • Push themselves to get stuff done
I'm sure there are other traits that are not listed here and I'll appreciate your comments based on your own experience.