Anudit Vikram
SVP of Audience Solutions, Dun and Bradstreet

GDPR is now perceived as a very positive development for data management, even as it continues to force marketing and advertising teams to count their ducks before attempting to coax customers and online visitors into sharing their private data. That’s encouraging and marketing teams would eventually get a hang of staying within the GDPR boundaries. Anudit Vikram,  SVP of Audience Solutions at Dun and Bradstreet, spoke to us about the direct implications of GDPR and how Dun and Bradstreet empower marketing teams to ensure GDPR compliance.

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

I am the Senior Vice President of Audience Solutions, a group which is responsible for activating Dun & Bradstreet data to solve for digital use cases.  Our products and capabilities allow businesses to target ads more effectively, to understand if their ads are reaching the intended audience, to better understand their website visitors, to use web visitor information to tailor the web experience through custom content, and to get more efficient at lead generation through smart form fills.

What is the state of commercial data management in 2018? What does your product roadmap for data management look like?

The market is not as far along as it believes it is in truly integrating across data types and platforms.  Based on a recent study conducted by Forrester on our behalf, marketing organizations are still struggling to use data effectively to drive marketing campaigns and results.  However, those organizations that are effective at doing so are seeing huge gains, with 73 % reporting more rapid sales cycles, 73 % reporting a higher return on marketing spend and 77 % reporting increased customer retention and loyalty.

From a Dun & Bradstreet perspective, the way we will help the state of commercial data is by helping our customers master their data- meaning we will help them cleanse their data, keep it up to date, and standardize it so it can be shared across systems and platforms. At Dun & Bradstreet, we use the Dun & Bradstreet DUNS^Ò Number as a unique, persistent, consistent identifier to tie the data in the systems together. This ensures all departments are looking at the same data sets and interpreting them in the same way.

How can marketers better leverage website data to maximize the value of their auto-fill campaigns?

The biggest hindrance for form fills is the human’s lack of interest in filling forms! Capabilities like D&B Visitor Intelligence, which we have developed, enable marketers to automatically, and in real-time, understand the attributes of a visitor to a web page. This helps shorten the size of the form and results in better fill rates.

How critical is mobile website experience to modern-day marketing and sales?

It’s extremely important- critical I would say. We live in a mobile world and we need to make sure our content is available where and when people want to access it. Mobile web experiences go beyond just ensuring that the website loads correctly on a mobile device. With the proliferation of the number of devices that generate data (computers, laptops, tablets, phones, wearables) and the amount of data available (transactional, social, etc.), managing identity is also becoming a very complex endeavor. This is, again, where a consistent and unique identifier can help tie together the identity of the user across multiple platforms and then serve the consistent experience based on that user’s information. What’s more, this data can then be boiled up to the account level and kept in the account record so all actions taken by people at that account are tracked, regardless of platform.

What impact does GDPR make on website data?

On a whole, I feel GDPR will be good for the industry. The fact that you need clean data and data that is received by consent will help the industry overall. If GDPR is an indication, the industry is going to become more concerned about data and data collection. The process of data collection is going to become more involved with the need for explicit content. Organizations will not be able to simply piggy-back off of tags and collect data for themselves. The few publishers having large user bases gain an inherent advantage, but the large majority of the organizations will have to change the way they have been currently working with data. There aren’t many companies that have enough of their first-party data to run at scale, so the need for third-party data will continue to exist. But we are going to see better controls and better transparency and that will be better for the ecosystem as a whole.

At Dun and Bradstreet, how do your solutions/ products empower marketing teams to ensure GDPR compliance? 

Our customers can be sure that any data collected within our products is legally compliant. This is not anything new for us- we have always followed local, regional, and national laws when it comes to data collection, and we make sure that our data partners do the same. So GDPR for us is really just an evolution rather than a revolution.

We also want to make sure our customers know that the commercial data is completely separate from individual or contact data and different standards apply to commercial data. We think that our customers could still gain a lot of valuable information at the account level without ever obtaining contact data. At some point, of course, they will need to speak with an individual, but there is a lot that can be done at an account level as well.

We anonymize data to comply with all the rules in the digital world. And while we do empower email marketing through the use of our lists, every individual has to be to have opted in. We have processes in place to make sure the data owner we are talking to is compliant.  And then we validate the data we get to make sure it is clean, real, and being used only in the construct in which it is allowed to be used.

How do you work with Data Science and AI/ML to improve your Data Management platform?

The use of Data Science and AI/ML for us is not limited to internal use cases only. Dun & Bradstreet is bringing machine learning, deep learning, and blockchain methodologies into play when it comes to identifying businesses and attributes of businesses. The use of these tools allows us to make sense of the multitude of data sources we work with and derive insights across them. The result is an expanded view of what a business does, for a far more targeted sales and marketing approach.

On the sales and marketing side, there are some very clear data tasks which machine learning can do more quickly. Many of the applications in sales and marketing are geared towards more intelligent decision making in order to move people through the funnel. Marketing automation platforms have been historically rules-based. We’re moving to a system where it can look for what events have the most impact on someone moving through the funnel and can then automatically deliver those things that will drive them through faster. This is starting to get beyond something a single person can write the rules around, so we need machine learning to help look for some patterns. Below are just some of the ways we’re using new technologies to make our processes more efficient and our data more accurate.

• ISP Classification- While we’re in the business of identifying companies, we want to know if the individuals are online on behalf of a company or not.
• Match Acceptance- We do matching all day long and, behind the scenes, there is actually machine learning going on to create that match.

Device Cookie estimation- whenever we are building a new segment for a customer and they want to know what kind of reach they are going to get, we have to do some modeling on our side to get a reasonable estimate.  We look at past segments and what we could deliver and make a reasonable propensity guess on volume we can reach for that customer.

Thanks for chatting with us, Anudit.

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