TechBytes With Kevin Dean, President of Marketing Services at Experian

Tell us about your role at Experian and the team/technology you handle.

Many brands strive to have more relevant conversations with their customers – and data and technology are core components to achieving that objective. As president of Experian’s Marketing Services, much of my focus is ensuring brands have the necessary data, linkage, audience activation and measurement capabilities to better understand their customers and create an improved customer experience across all marketing channels.

What makes Experian’s Marketing Intelligence so powerful?

With hundreds of customer touchpoints across online and offline channels, identity resolution has become the foundation of all marketing and advertising efforts. And accurate customer identities can only be built on quality data. The combination of our datasets and use of advanced technology can help brands bridge the gap between online and offline customer interactions to more accurately identify customers, create relevant messaging and optimize future campaigns.

How did you find the gaps and opportunities in Identity Resolution? How does it help to build a unique customer profile?

First, and foremost, identity resolution is built on quality data and advanced linkage capabilities. Every customers’ path to purchase varies by transaction. For instance, a customer may see a commercial for a new pair of shoes and begin researching the product on their mobile phone. Before the customer can purchase the pair of shoes on their smartphone, they’re distracted by a text. Later that week, the customer finishes the purchase on their laptop at home.

With so many different digital touchpoints, brands need to connect the dots to better understand which campaign elements were most effective and which truly influenced purchase behavior. This level of insight can help brands optimize future campaigns and ensure relevant messages are delivered across the most effective marketing channels.

In 2019, how would you define Customer Analytics? How do these analytics fit into Customer Experience and Personalization efforts?

We often look at customer analytics and identity resolution as two sides of the same coin. It’s imperative for brands to connect the dots across online and offline data points – most times it requires a combination of first- and third-party data.

For brands to be successful and relevant, they need to gain a more complete understanding of their customers, as well as what channels are most effective. Does the customer prefer outdoor activities or movies? Is the customer more engaged on their smartphone? The more a brand understands about the customer, the more likely they can create messages that resonate with them.

How do you connect every customer data with Marketing Automation and Targeting tools?  

We continue to invest in data, and constantly look to expand our network of data and media partners to help brands connect disparate datasets to create a single customer identity. But beyond our current products and capabilities, our research and development group, Experian DataLabs, constantly use breakthrough experiments to test new Machine Learning and Artificial Intelligence techniques to help brands better connect customer identities.

What does your product and solutions roadmap look like for Mobile Marketing and Omnichannel Customer identification?

With such a strong focus on identity and linkage, we are continuously exploring new data sets and advanced technology, such as Machine Learning and Artificial Intelligence, to help brands crate a more holistic view into their customers.

What technologies in AI/Machine Learning have you deployed, or plan to deploy in the coming?

Advanced technology, such as Machine Learning and Artificial Intelligence can open the door for marketers to use data more effectively and gain a deeper insight into their customers – particularly customer preferences. We are constantly exploring new data sets and experiment with Machine Learning and Artificial Intelligence techniques to better connect disparate datasets and create more accurate customer identities.