With just 6 months left before Google Chrome eliminates support for third-party cookies, many companies are still in the dark as to how they will effectively connect with visitors and customers without the data they currently get from systems that depend on third-party cookies.
What will they use to inform online advertising campaigns and how will they have to adapt their prospecting strategies?
Historically, companies have purchased demographic and intent customer data from social and advertising platforms in order to get deeper insights into their customer base. Third-party cookie data has been the core mechanism to collect this data across platforms. The disappearance of third-party cookies is having a significant impact on the type and quality of that customer data. While this change is driven by privacy concerns and in general is acknowledged to be a positive step for customers, many companies are wondering how they will be able to understand more about their visitors and customers.
While losing any form of customer data is not ideal, it’s important to consider the quality and value of that information. Demographic data is a dated way of segmenting customers and provides only highly generalised assumptions about their behavior. The value provided through third-party cookies has been customer intent. With historic browsing data, it made it easier to serve up relevant information when visitors came to a website based on their previous activity. But things are not as bad as they seem. While broader browsing data will no longer be available through third-party cookies, what is still available and very relevant to marketing efforts is the behavioral data that can be gathered when visitors are interacting on a website. And gaining access to that information does not require third-party cookies.
There’s a powerful, yet underutilized data set websites already have, that companies seem to have forgotten about.
By tracking in real time how long visitors are spending on certain pages, what products they’re browsing, and linking that to data on what products have they purchased previously, companies gather behavioral data. This data informs how visitors are progressing through the website and signals intent. It’s an opportunity to connect with customers. When customers leave a page, or abandon a cart, it’s an indication that they’re experiencing a level of frustration, which means there’s friction that needs to be addressed in the customer journey. It’s an opportunity to improve the customer journey and experience.
This type of information is significantly more relevant to optimizing the digital customer experience (CX) than what demographic data provides. Having a person’s age and where they’re from doesn’t tell you what anxieties or points of friction they may experience on a website, but their actions and responses definitely do.
As a result, there is a trend to move towards newer mechanisms of understanding online customer behavior such as frustration scoring or propensity measures, as well as historical transactional data. Knowing what products a customer has bought previously indicates a specific interest and can also inform cross sell and upsell opportunities. But how they interact in the moment, and which products they respond to while browsing, gives an even better indication as to what their primary interests are right now. Given the rapid pace that customer preferences change, this information is far more valuable. Having the ability to track these online behaviors and gain insights quickly enables companies to respond faster to changing customer needs and interests.
For decades, marketing activities have been focused on getting visitors to a website. Advertising efforts were all about targeting certain market segments and demographics played an important part. Times have changed, and the current reality is that returns on ad spend are diminishing and becoming much harder to achieve. Plus marketing messages no longer carry the weight they used to. Customers are far more interested in hearing about the experiences of others through social media and various platforms and then comparing that against their own online experiences.
This means there’s far more value in focusing on the data that will improve their online experience, once they’re on your website rather than the data used to get people to visit the website
For example: if a visitor spends a few minutes on a particular page, but doesn’t progress any further in the customer journey, you should want to know why. What needs to change on that page to get them to respond? What will re-engage them? Is it the design or layout, or how information is presented, or in what order, or the content itself, or a combination of several elements? All of these elements have the potential to make an impact, but you won’t know which ones to implement unless you have the ability to experiment with lots of different ideas.
Behavioral data shows more than just intent, which makes optimizing CX less of a guessing game. It can be used to target optimization strategies to achieve specific measurable outcomes. By using ideation at AI scale, behavioral data becomes the starting point for experimentation, where hundreds and thousands of ideas can be served up to improve CX. As different visitors respond to ideas that resonate with them, it creates a much clearer picture of what customers want and what they value.
With AI-driven optimization, you’re able to increase the velocity and scale of experimentation to optimize the digital CX for each unique website visitor. Providing relevance, value and leading them further along the customer journey. That’s something third-party cookies have never been able to do—we shouldn’t spend too much time mourning their demise.