Identifying Opportunities in a Cookie-less World

In Part 1 of this series, we explored the disruption and impact that impending policies around the restricted use or removal of third-party cookies are poised to bring to the digital advertising and marketing industry. As we stand at the cusp of this change, it is important to embrace a new paradigm.

This article will discuss where opportunities lie, aiming to minimize disruption in personalization & optimization, ad experiences, data partnerships, and visitor analytics.

Personalization & Optimization

1. Personalization: Building first party data and maintaining a unified online domain

The significance of first party data has never been more evident. It is more accurate and more actionable. By harnessing tools like machine learning, different in-session algorithms can be built tailoring real time experiences for individual customers.

A pivotal facet of this approach is its device agnostic nature, increasing its effectiveness. Moreover, maintaining a single domain consolidates first party data, enabling seamless authentication and persistent identification throughout the user’s website journey.

Augmenting first-party data with people-centric identifiers, such user IDs or email address (or hashed values) is a way to reach personalization goals.

2. Optimization: Crafting Probabilistic experience Journeys

Leveraging geographic, demographic, and behavioral data collected from first-party sources can help in building customer segments. These segments can be analyzed to determine who is mostly likely to purchase, drop, or go inactive.

Experiences can be tailored based on the behavior shown and segment attribution to optimize conversion in likely buyers.

Ad Experiences & Marketing

1. Contextual Advertising: a Paradigm Shift

In the absence of historical third-party cookie data contextual advertising emerges as a strong alternative. By evaluating the current context and user actions, advertisers can analyze webpage or app content to deliver relevant ads. For instance, the topic or keywords on a landing page can inform ad delivery, aligned with the user’s immediate interests and behavior.

2. Synergy of First Party Data, Offline Data & Machine Learning:

Combining user specific identifiers (like ID, email ID/hashed email ID, phone number) captured via first party behavioral data with offline CRM records and harnessing the power of Machine learning & segmentation can yield dynamic ad experiences. These experiences adapt to user preferences, grounded in real-time & offline data analysis.

3. Forging Second Party Relationships: Unleashing Collective Potential

Establishing Second party relationships involves the reciprocal sharing of first party data through a mutual/contractual agreement (by dropping a container on the partner’s website or by exchanging files).

Particularly beneficial when businesses share overlapping customer bases, this approach facilitates enhanced segmentation delivering more relevant ad experiences. Consider scenarios where credit cards companies can collaborate with entities in the electronics, travel, and retail sectors.

Visitor Analytics

One privacy-friendly method, “Server-Side Tracking”,  can be utilized to track user behavior. This method entails the tracking and storage of user behavior at the server level, eliminating the use of cookies.

Leading analytics tools like Adobe Analytics (Google Analytics & many more) offer Data insertion APIs that enable server-side tracking. Data collected in XML format is directly sent to Adobe servers, where it can be read and activated for various platforms. A unique ID is given to every new visitor based a combination of user agent, IP address, and other points.

Key capabilities include:

• Event tracking data- Clicks, Page Views, Form Submissions, Video Milestones
• API based data tracking & insertion- Tracking data for behavior on third party platforms

Conclusion

Embracing a new paradigm, characterized by server-side tracking, switching to first-party data collection, soliciting consent for data collection, and fostering second-party partnerships lays the foundation for navigating a digital world in the third-party cookie less era.

What’s next?

Stayed tuned for our next article: “Cookies less Visitor Data Collection”.

How is AEP Helping Businesses?

The digital world is moving towards cloud, server side, cookie-less tracking with limitations & law restrictions in interest of ITP, GDPR, CCPA. With many products & service providers available, it is becoming important to understand what different players in the market are offering.

This article will help in understanding what AEP is and how its’ different offerings can benefit businesses in different practical scenarios.

Adobe Experience Platform has endless offerings for different business requirements. In this article, we want to help you understand -What’s in it for you?

Note: If you are existing user of Adobe experience cloud products like Adobe Analytics, Adobe Target or Adobe Audience Manager- this chapter will be very useful for you to build in understanding.

Overview

AEP is a platform evolved within Adobe where different services are integrated along with data-lake (based on Microsoft Azure) to build or optimize customer experiences in real time by capturing, processing, and centralizing data.

Before we jump on actual topic, few terms & tools to get familiar with(Adobe explained):-

• Customer Journey Analytics (CJA): Customer Journey Analytics is an Analytics capability that lets you use the power of Analysis Workspace with data from Adobe Experience Platform. Customer Journey Analytics expands the scope of Adobe Analytics by offering easy to use cross-channel capabilities and removing limitations in previous versions of Adobe Analytics(eg unlimited variables & events, historical data alternations, cross –report suite data analysis)
• Journey Orchestrator: Journey Orchestration is a service built on Adobe Experience Platform that allows you tailor individual journeys for every customer based on their previous behaviours and preferences
• Journey Optimizer (JO/AJO): Adobe Journey Optimizer, built on Adobe Experience Platform, allows Customer to orchestrate omnichannel Journeys, determine the next best action to take for their customers and deliver contextualized Offers that are personalized and optimized in-the-moment powered by real-time decisioning and intelligent insights.

Your Current Tools

1. If you are an existing user of Adobe Analytics (Or any web analytics tool)– Customer Journey Analytics is an analytics capability that lets you use the power of Analysis Workspace with data from AEP. The tool enables pulling data from AEP’s big data lake and conducting custom analysis with flexible specifications for historical data. Analysis of data coming from different report suites/properties is possible with CJA (Customer Journey Analytics). Additionally, online data can be coupled with data from any of the other marketing sources. To summarize, AEP+CJA can be your Analytics 2.0
2. If you are an existing user for Adobe Target (Or any Optimization/Personalization tool) – AEP can make your work even more interesting and more targeted with the functionality from Journey Optimizer. This is combination of Journey Orchestrator (taking your customer to ideal path/event) and offer decisioning engine (building dynamic offers with creative assets).
3. If you are an existing user for Adobe Audience Manager (Or any DMP (Data Management Platform) tool)– There is a lot more to do with the offering of “Real Time CDP” (Customer Data Platform). This platform can create segments from profiles and other data and tie it to another Ad tech. It also offers B2B, B2P and B2C versions which can be utilized as desired – professional data or checkout funnel/cart data.
4. If you are Data scientist or an Evangelist – This is an ultimate boon for you. It brings the functionality of the cloud-based “Query Service” tool where PL/SQL querying can be done with all the data available in data-lake. Additionally, you can use “Intelligent Services” which bring the power of AI and ML to churn, analyse, and predict conversion data for your customers at ANY granular level. Other BI tools e.g., Power BI and Tableau can be integrated with AEP data-lake.
5. Build Customer Profiles and Enable Identity Graphs- Tired of maintaining different Ids for different systems for the same customer? This brings the functionality of tying customer profile data from different sources so that you need not go to different places to see it. Know your true customer number and plan personalized projections using Identity Graphs. This provides both real time and replay customer stitching options.
6. Enable Event forwarding/Server-side forwarding- Send your data to any third party tool from a single collection point. Data can be collected once and sent to EDGE service where it can be forwarded to any tool. This reduces the dependence on 3^rd party cookies  and helps transition toward a cookie-less world.
7. Standardize and Integrate customer experience data by data labeling. By adhering to XDM standards, all customer experience data can be incorporated into a common representation that can deliver insights in a faster, more integrated way. Policies like GDPR, CCPA or any other regional data protection laws can be adhered to.

Building Relationships

In essence, AEP should be seen as a platform that provides integrated functionality of different tools that can also work in real-time to build rich customer profiles on which businesses can take relevant actions.

Looking for more insights in this direction? Get in touch with us! We here at Perficient can help you achieve your business goals.