Digital Marketing in a Cookie-less World

As you may know, Apple, Google, and many others have finally responded to users' concerns regarding privacy and decided to move away from the use of third-party and first-party cookies. Until recently, cookies were often created and stored without the user's permission. The advent of GDPR and CCPA has resulted in most responsible sites now asking for permission to use cookies. Whereas cookies made implicit assumptions about a user's permission to store their preferences and sell to them based on their known buying habits, a cookie-less world requires that permission be granted more explicitly. Therefore companies need new strategies in order to respond to this new cookie-free environment.

The keys to succeeding with digital marketing in a cookie-less world will be comprised of three pillars: customer acquisition, customer engagement, and customer retention. The common theme is, you guessed it, the customer. 

Of course, anonymous/pseudonymous personalization will continue to pay off to a limited extent as before. However, in the absence of cookies letting us know that we're working with a known user, we must convert anonymous users into customers who register themselves on our sites, re-authenticate or log in every time they visit, and never cease being customers (i.e. never return to being anonymous users again).

1. Customer Acquisition

Customer acquisition strategies will help us convert anonymous users into known users who can be targeted more meaningfully. Once a user registers, typically by supplying their email address and choosing a password, they become a customer or at least a lead (i.e. a potential customer). Some users may not register right away instead choosing to use OAuth and one of their social media accounts (Google, Twitter, Facebook, etc.) as a proxy to tell us a little bit about who they are (name, email, etc.). 

Once we know who they are, we can create an account for them and can start storing their user preferences, browsing habits, buying patterns, etc. in order to customize their user experience during each subsequent customer journey. This customization of a user's experience is also known as personalization or optimization.

2. Customer Engagement

When a user arrives at one of our properties (web site, mobile app, physical store, etc.), in the absence of cookies the only way for us to know that the user is a known user is for them to re-authenticate or log in. Customer engagement strategies are designed and intended to give known users incentives to re-authenticate (ideally with OAuth or similar one-click methods) frequently so that their personalized experiences can continue to be optimized based on an ever-growing set of omnichannel data points stitched together into a 360 view of the customer. 

This 360 view of the customer is typically stored in what has come to be known as a Customer Data Platform (CDP) which can be built using Adobe's AEP Realtime-CDP and their Experience Data Model (XDM) or another equivalent system. A CDP collates all of the user's interactions on every channel (email, SMS, web, mobile, in-store, etc.) into one rich profile that is then used to inform the personalization decisions for every step in that user's current and subsequent user journies. 

A major component of this pillar is AI/ML-driven strategies on digging through big data to find the most relevant insights and trends, including leveraging custom models, to help with 1:1 personalization, i.e. a unique user experience tailored individually to each and every user.  

3. Customer Retention 

The cookie-less strategy described above only works as long as the user remains a customer, i.e. a known user. If the user deletes their account or otherwise fails to re-authenticate, we've lost them as a customer or an engaged customer. That user is then back to being an unknown or anonymous user. 

We can target anonymous users based on publicly known data points such as their IP address which might indicate something about their geography or their last few interactions on the property during the current user session which might give us a thin sliver of insight into their interests. However, targeting an anonymous user is a far cry from our enhanced ability to personalize the experience for a known user (customer) about whom we have months or perhaps years or even decades of data on which to base our optimizations. 

That is how sites like Amazon know that even though you usually shop for books, you do occasionally also look for apparel and electronics. Therefore, when Amazon shows you a list of products you might be interested in, it uses complex data science algorithms to determine which books, apparel, electronics, or other products to show you to maximize your user experience and makes you feel like a highly valued customer.