Master first-party data for omni-channel excellence

In today’s world, companies need to show that their products and services are not only of good quality and offer value for money but also personally relevant to consumers at any moment of the day. Access to first-party data is required if you want to provide excellent experiences.

However, getting access to all relevant first-party data of quality means collecting and using data in the brightest possible way. Let’s find out how this can be done and what it brings.

What is first-party data?

First-party data is information about a company's customers that is collected and owned by that same company. This can include a wealth of details, such as purchase history, loyalty status, on- and offline behaviour as part of the customer journeys, preferences, and so on.

It's distinct from zero-party data, which customers explicitly provide about themselves through surveys, preferences, and wishlists.

All relevant data coming from these sources is linked by establishing a unique identifier, for instance, and transformed to define and share audiences with the channels.

Beyond a unified customer view, a well-defined and identified list of use cases helps realize better business outcomes to monetize on the data. Some use cases are covered later in this article.

Challenges using first-party data

Web browsers that restrict ad trackers and stricter privacy laws are making marketers can’t rely on third-party data anymore. This is why they must fall back on first-party data, collected straight from their customers. However, getting the right strategy and technological infrastructure in place to activate the power of first-party data seems to be a struggle for many companies. Even though most organizations have access to technical capabilities, they lack strategy and execution.

Another obstacle to using first-party data is internal silos. Many companies are not leveraging the full capabilities of first-party data in their marketing efforts. Their collections are not integrated and the data ends up in siloed systems and is not made available for broader use. Caution is also an issue.

In some companies, the management is afraid that personalized communications could hurt privacy-sensitive customers.

So how to put first-party data to use?

To achieve business value, there are two tracks; organizational and technical as shown in the image below.

I will explore some aspects of the image. The first organizational step in getting the most out of your first-party data is developing a data strategy that supports a broader business objective and identifying the data you have.

A clear data strategy explains how business objectives are supported by organizing data, processes, and people. The strategy also clearly identifies which data is needed to reach different business goals. Alignment with the IT strategy is essential because data is always related to IT.

A technical step is the collection of the data. Data will be collected, transformed, cleansed, stored, and combined from multiple first-party resources into a view required to support the selected use cases. Ensuring good-quality data is essential at this stage.

The next step is to use the data in the stages of the customer journey and ensure a two-way value exchange between the company and the customer.

The functions of a CDP

Only companies that invest in state-of-the-art automation systems like CDPs are consistently able to link all of their data and use them for automated activation. In this blog I’ve written you can discover the 3 best practices for designing and implementing a CDP.

There are many companies that collect offline interactions, such as calls coming from customer service centres, which include utterances of satisfaction, frustration or unresolved problems, but they are not connecting this data to other data sources or using this data to tailor their messages in digital channels.

If they would invest in the development of a CDP they would be able to create a 360 customer view and deliver better-tailored messages in all their digital channels resulting in better sales numbers.

First party use cases related to maturity

Use cases may extend beyond marketing to support customer strategy, experience, and service functions. We see that marketers differ in the maturity of their use of first-party data.

Companies that move up the maturity ladder on their way to becoming truly omnichannel, are able to manage and deliver personalized customer journeys by:

• Combining multiple online and even offline data sources and linking these to a global customer identifier
• Augmenting existing first-party data with third-party and other data, such as advertising cost and sales data
• Enhancing their first-party data with predictions from AI-powered models that support the different marketing activation activities

Using first-party data in CDP

In order to use the full potential of your first-party data, you need Customer Data Platform functionalities. Data is pulled from multiple sources, cleansed and combined to create a customer profile and is accessible to other systems that help you to get insights or make predictions. Below you find an example use case:

In the image above you can see data coming from different sources. When the first party is collected and normalized, modelling can be applied. Different types of modelling for bidding and audience activation such as conversion models, engagement models and models that predict the customer lifetime value are applied using the Google AI Platform. The sessions are scored and the models are being retrained automatically so different kinds of audience and bidding strategies can be applied. 

First-party data might also be used to up-or cross-sell, to predict churn or to predict conversion intent. Customers can be segmented based on frequency and depth of visits and the elapsed time since the last visit. First-party data can also be used in a more advanced way, for example by predicting future consumer trends. 

Do you want to become a data-driven company too?

If you feel like your organization is not using the full potential of first-party data and you need advice about data strategy and marketing automation, schedule a meeting with us. Crystalloids is a Google Cloud Platform specialist building headless modular CDP’s. We are fond of data architecture and data modelling, and we know a lot about it. If you want to know more about modern, unified data analytics platforms on the Google Cloud Platform you can also download our whitepaper.