Showing posts with label 3rd party data providers. Show all posts
Showing posts with label 3rd party data providers. Show all posts

Saturday, January 12, 2019

Miscellaneous Facts About Adobe Audience Manager

Happy New Year 2019 to all and Thanks for reading this post. Adobe Audience Manager just like any other data management has its fair share of characteristics that are not commonly known. Unless you've actually spent some working time on AAM, it's unlikely to find these facts readily available in our documentation. In this post, I've aimed to document some of these in a single post. So, let's get started!
1.    The third party Audience Manager demdex cookie is the same across all sites (customers) that have AAM deployed. The reason why it's the same as it allows cross domain tracking of AAM customers and also forms the basis to share data across all AAM customers (2nd party data share). So, if you delete the demdex cookie, it gets refreshed for all AAM customer sites.
2.  Metrics in Audience Manager are based off Cookies/Visitors tied to the UUID (device/browser) or demdex. Customer often ask about replicating Adobe Analytics segments based on Visits in AAM which isn't possible to replicate 1:1 so it's important to understand this nuance.
 3. Server side Forwarded Adobe Analytics data to Audience Manager is billed separately in Audience Manager. Customers often assume that this data is forwarded for free which isn't the case as the same applies to data captured via the client side DIL data collection method in AAM which is billed separately.
4. Audience Manager variables starting with 'c_' are customer defined keys, 'd_' are platform level keys and h_ are typically browser header keys. Let's review of few of these.
o   Following are some keys to filter for the URL and/or referrer.
§  d_referer (not traffic referrer) allows you to filter for the page URL
§  If you have Adobe Analytics forwarding enabled, you can also use c_pageURL.
§  If you want to filter for the traffic referrer and have Analytics data forwarded, you can use c_referrer.
o   If you have a scenario where you capture the same page name across multiple sites (with different Adobe Analytics report suite IDs) and have SSF enabled, you need to use the d_dst_filter field. I've included a screenshot which shows how to filter it using a trait. See how the customer variable starts with 'c_' and platform variable starts with 'd_'.

o   If you want to capture data tied to city or country based off automatic IP address which is collected in AAM, you can use the following Geo platform keys: 
§  d_city 
§  d_country

5.   Given that Adobe Analytics data is now forwarded to AAM via report suites, the Audience Management Module is not required to forward data BUT should ALWAYS be implemented if you want yours users to qualify for segment as without it, you cannot leverage AAM for A/B testing and personalization. The other advantage of the module is that it creates a first party cookie for AAM (covered in #7).

6.  One other confusion that clients have is around the data collection frequency and availability of rule-based traits in AAM. Rule based traits start collecting data in real time since creation even though the data may be take up to 24 hours to show up in the AAM UI. So, if you have a scenario where you want users to qualify for a trait in real-time for personalization, you can rest assured. To validate if you qualified for a trait, you can use Visitor Profile Viewer in AAM and other methods defined here.

7.  UUID demdex cookie (covered in #1) which is usually a third party cookie can be captured as a first party cookie called 'aam_uuid' within the Audience Management module (#5). Once you set the UUID as a first party cookie, you can easily create a data element in Launch by Adobe (shown below) and map it to an Analytics variable.

8.  Customer IDs synced using natural match upon authentication need to be hashed and should not contain any ids that are even borderline PII. A good method to anonymize your user ids is to leverage the SHA256. The other important thing to keep in mind is that you should leverage the same type of user ID across multiple sites and map them to the same AAM data source so that there's no ID collision.

9. Data onboarded via 3rd party data providers such as Acxiom or data onboarders such as LiveRamp upload data to AAM using a unique 'ic' (integration code) which is numeric (example below). In a previous post, I covered how to upload data using key value pairs but an 'ic' can also be used to upload your CRM data.



10. 3rd party ID syncs enabled by AAM consultants shares the AAM UUID with Demand Side Platforms where they store this ID in a match table so that they can target users on their own network using this ID. Adobe also receives a corresponding ID from that system as well so that each system's cookies can be synced with each other. This sync is used to calculate the match rate which is why it's recommended to ask your consultant to turn on these id syncs to get a higher match rate between AAM and your DSP. However, these cookies can be turned off by setting the disableThirdPartyCookies variable to true in the ID Service library.
   
Below is what these id syncs look like in the network tab of your browser (Adobe Ad Cloud) populated the very first time a user visits your site. Also, note that subscribing to a data provider in the Adobe Marketplace automatically turns on an id sync as well.

I hope you found this post helpful and feel free to share any other misc facts that you learnt about Audience Manager.
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Sunday, January 21, 2018

Data Management Platform Use Cases

Marketers hope to get the best return for each campaign they run but is getting that return really that simple? Unfortunately, it’s not as there are a lot of factors that come into play for planning and executing these campaigns such as identifying/finding the target audience, communication channel, budget, technology platform and expected outcome to name a few. Luckily, there are tools out there to support marketers activate towards an outcome, measure performance and optimize continuously. One such tool that helps them is a Data Management Platform.
In my last post, I gave an overview of a Data Management Platform. In this article, I’ll go through some typical marketing scenarios that are realized using a DMP.

Frequency Capping: Marketers use this feature to set a cap on how many impressions should users be exposed to for a particular campaign. The idea behind this is to not show the same campaign to users if they’ve seen it multiple times. As an example, the screenshot below taken from Adobe's DMP that shows a report where conversions start to drop once users see the same ad more than 2 times. The advantage of this feature is to save marketing dollars and not pay extra for potentially wasted impressions as users tend to convert in the first 2 interactions as per this report.
Source: https://marketing.adobe.com/resources/help/en_US/aam/optimal-frequency.html


Prospecting or Lookalike Audiences: Prospecting allows marketers to reach out to new audiences who wouldn’t have visited their site. This is where a DMP's connection to the 3rd party marketplace allows marketers to evaluate new audiences and overlap them with their 1st party data. This feature is called lookalike modeling where marketers pick a baseline 1st party attribute (such as users who bought something) and run that against 3 party audiences to see which new 3rd party audiences exhibit the same behavior. Once these audiences are identified, marketers can purchase these audiences at a premium and factor this cost as part of their marketing budget and look to further increase their overall CTR and conversion rate.

Media Suppression: Media suppression or exclusion in the marketing world allow marketers to not display an ad to certain group of people who need to be excluded. Simple examples of exclusions can be at a geographic level or channel level that can be executed directly in the Demand Side Platform (DSP). A DMP however, is able to fulfill other use cases where a marketer would want to exclude users who already purchased something on their site or might have submitted a lead. In this case, marketers can build an exclusion audience in the DMP comprising of 1st party onsite behavioral data and share it out with a DSP for execution.

Content Personalization: Personalization in simplest terms means serving up content tailor-made for customers based on their browsing patterns. A few examples of personalization, which are accomplished using a DMP are as follows:
    • Combine 1st party CRM data to gather demographic and past purchase information about a user and serve them discount offers to buy something again.
    • Personalize content based on product pages that users have visited in the past and deliver similar content to encourage them to go deeper into the purchase funnel. An integration between site analytics and an A/B Testing tool is required but a DMP can be used to find additional prospects that can be combined with 1st party site data.
    • Other simpler examples are serving personalized content based on city, weather, time of day so the opportunities are endless depending on your site.

Visitor Retargeting: Retargeting (if done right) is a form of advertising in which you  follow visitors across the web who've visited your site but haven't converted. A retail site (shall remain unnamed) continued to retarget me even though I had bought from them. This tells me that the retailer doesn't share 1st party purchase data with their retargeting platform and should probably invest in a DMP. In terms of the technology, a client website has pixels that set a cookie on the user's browser -> that is shared with a retargeting partner who -> is able to show them ads across the web -> to bring them back to the original website. There are many retargeting use cases that marketers can execute on but I'm going to cover the most common ones which can be executed using a DMP:
    • Retarget users who added an item to their cart but didn't purchase. In this, first party data around cart add is shared with the retargeting platform via a DMP.
    • Retarget users who opened an email but did not convert. In this, data from the email captured in the DMP integrated with other data sources is sent over to the retargeting partner.

Test multiple creatives and DSPs: DMPs also have the capability to test out multiple creatives or DSPs. The way it works (in Adobe Audience Manager as an example) is that a single segment is broken into mutually exclusive groups and then split into multiple subsets depending on the number of creatives or DSPs a marketer wants to test. The result of this is that the DMP will tell you which creative or DSP performed the best localized to its baseline segment picked as part of the test. As a next step, marketers can swap out underperforming ads and DSPs, pick the one that works and then repeat this process moving forward.

Cross device targeting: It's common knowledge that consumers browse the web using multiple devices but how do we tie them together? DMPs can connect users browsing the web across multiple devices by using their authenticated profile. Once a user has visited a web property in an authenticated manner, the DMP is still able to identify that person even if the user visits the property as unauthenticated. A common scenario where this feature is leveraged is where a user may not have purchased something on desktop and sees an ad for the same product on their mobile app. The DMP in this case, collects 1st party data both from the desktop site and mobile app and shares that with the DSP for targeting. Here's a visual from Adobe's cross device tool called Profile Merge Rules.
Source: https://marketing.adobe.com/resources/help/en_US/aam/profile-link-intro.html

We covered many aspects of digital marketing as individual use cases but in reality, they need to execute in tandem to get the most value from a DMP. Retargeting users and personalizing the website to show similar ad copy content is a great example of these done in tandem. Successful execution of these use cases will allow companies to reap the benefits of what a DMP has to offer as the possibilities are endless. Are you leveraging your DMP to act on these use cases? 

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Wednesday, January 10, 2018

Overview of a Data Management Platform

I'm a numbers guy so I'll share some statistics. The Data Management Platform (DMP) market is expected to reach ~ USD 3 billion by the end of 2023 with approximately 15% growth during the forecasted period from 2017 – 2023 according to this report. The other statistic from a report published in August 2015 (a lot has improved since then) is that only 50% of companies were using a DMP then. This tells me that there is still a lot of juice to be squeezed when it comes to companies investing in a DMP. So, what is a Data Management Platform?

As per Wikipedia, A data management platform (DMP) is a centralized computing system for collecting, integrating and managing large sets of structured and unstructured data from disparate sources. My definition is slightly different and this is how I define it.

 A data management platform (DMP) allows marketers to integrate multiple data sources such as 1st party (online, email, media, offline/CRM), 2nd party (partner) and 3rd party (provider) data into a centralized system typically leveraged for digital advertising media activation and optimization.
Source: https://upload.wikimedia.org/wikipedia/commons/9/9b/DMP-diagram3.jpg

Now that we got the definition out of the way, let’s look at a few advantages and features that a DMP offers:

  • Integrate and Centralize data: A DMP leverages a common identifier that allows us to integrate multiple data sources. First party data such as client’s own onsite data is captured using a device/cookie ID that can be integrated with campaign media data typically tracked by adding tracking pixels to digital advertising banners. This data can be further integrated with offline CRM where a user ID captured on sign in can be extended by bringing in additional user metadata to the DMP via an offline file. DMP also has the capability to allow marketers to purchase additional 2nd party and 3rd party to bring in new qualified users (cookies/devices) into the DMP.
  • Maximize Marketing Spend: A DMP allows digital marketers, advertisers (most common) and publishers to leverage integrated data across multiple sources and cross device channels. The marketers are able to leverage the platform to take data from multiple sources and share it with outbound platforms called Demand Side Platforms (DSP) such as Adobe Media Optimizer, DoubleClick Bid Manager etc. A DSP allows advertisers to buy media to run retargeting or other campaigns based off data that may be a combination of online first party and provider’s 3rd party data shared out via the DMP. A common use case is to retarget users who've added an item to their shopping cart but left without purchasing. With this, the marketers aim to increase conversions which probably wouldn't have happened.
  • Deliver a Personalized Experience based on Integrated data: Testing and personalization tools such as Adobe Target have the ability to take first party onsite data and offline CRM data from the DMP to run personalization tests. An example use case can be running a personalization campaign comprising of demographic data such as gender, location or income combined with onsite behavior tracked in the DMP and serving an experience customized per visitor.
  • Display consistent Advertising to users across devices: A DMP is also able to stitch users traversing across devices using a hashed email address (most accurate), IP address and location. As users log in, a DMP is able to identify the user across devices as well as on the same device even is the user is not logged as a profile of the visitor is created. This feature allows marketers to deliver a consistent message or retarget the same users across devices, which can be one of the objectives of a campaign.
  • Audience extension via Data Providers: A DMP has partnerships with different 3rd party data providers such as Acxiom, Dun & Bradstreet etc. who sell user demographic, psychographic and other offline behavioral data. These data providers either charge a flat fee or bill based on a CPM. Advertisers can build out test segments in the DMP to see how many new prospects they can get with the 3rd party data set to target more users for their campaigns. As an example, marketers who are planning to run a campaign to sell high-end laptops might want to target technical professionals who are between the ages of 25-35. This data wouldn’t be available in their first party data set so they can purchase this from a data provider and combine it with onsite data in the DMP for a prospecting campaign.
  • Leverage Lookalike Models: Lookalike models or algorithms are used to identify similar audiences from a benchmarked audience segment. An example use case might be to create a lookalike from a base/benchmark segment of users who’ve converted and run the model against a bunch of 3rd party audiences to find new users who exhibit similar conversion behavior.

There are other features that a DMP offers such as testing audiences, overlap reporting, frequency capping reporting etc. but they are supplemental to the main features already covered in this article. I will discuss these in some capacity in the future.  

Based on all the advantages that a DMP offers, it’s imperative for organizations to invest not only in a DMP but also in resources who know how to leverage it properly so that they get the best return on investment.
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