Data Pioneer Perspective: Erick Watson on Anticipating Buyer Behavior

January 6, 2023

OCTOBER 18, 2017 BY JINGCONG ZHAO

This is part of series where we interview experts and influencers in the data technology space.

We sat down with Erick Watson, the Vice President of Corporate Development at Quantarium. Quantarium is a platform that uses machine learning and artificial intelligence to help provide valuations and make predictions in the real estate industry.

Erick comes from a long background in technology, including A.I. projects at Microsoft Research. Erick is passionate about helping people use data because it’s still widely misunderstood. “It means something different to everyone. It’s an area ripe for consolidation and education and helping people find value.

And from Erick’s perspective, that value is directly tied to our ability to craft great customer experiences by responding to their behavior.

Anticipating Buyer Behavior

It’s the unwritten contract between business and customer: “customers expect us to make more useful decisions” with the data they choose to give us.

The more that the enterprise can anticipate the customer’s needs, the happier the customer will be.

One of the tricks is to link up the customer experience from their first encounter with a brand to the next follow up action, all the way down to a sale.

The first encounters could be through a referral, your website, or a physical mailing, where your messaging is focused on generating awareness.

Then you might start reaching out with calls-to-action that are still relevant to the customer experience, or in other words, to “correlate who’s doing the clicking with who received the pop-up ad. Once you’ve got them on the hook, then it’s even more important to have great customer experience and be as anticipatory as possible.

Being anticipatory means learning as much meaningful data about your customer as possible, and this data often comes in from a wide array of disparate sources, both online and offline, qualitative and quantitative.

“My job is similar to a private investigator. It’s like trying to solve a mystery. The best sources for data happen to be people, so if I can connect with people on Twitter or LinkedIn, that’s the best way to gain information about people.”

Knowing enough is like printing money,” but there are some obstacles to get this data working in a meaningful way.

Making Sense of Data

It’s a challenge of marketers today to tie all of these data points together to create a meaningful picture of their customers.

Unfortunately, not all business even know how to make sense of the data available to them. They struggle to use data effectively for three primary reasons:

  1. Data is complex and comes from many sources
  2. We have to sort through what is and is not meaningful in the data
  3. Once we have the valuable data, we don’t always know how to respond

Most businesses that are still in the early stages of their data maturity rely on disparate data sets: from their customer database, to product usage tracking, to web analytics. The trick to unify this data holistically, in a way that is meaningful.

Most businesses struggle to understand which datasets are business relevant and which are just noise. It takes human intelligence to factor what makes a difference to one business versus another.

Thankfully, technology is helping business people make these decisions.

What’s Next in the World of Data?

There are a lot of new technologies emerging these days, especially in the realm of data management and analytics. It’s important to know “the true utility of these technologies without getting caught up in all the hype.

By understanding where automation is helpful – and where it’s harmful – we can avoid automating just for the sake of automation. However, some technologies are helping businesses solve tangible problems.

For example, Erick sees predictive platforms as one step in this direction, to help marketing, sales, and product leaders alike discover correlations between different buyer behaviors, with an eye towards increasing revenue.

In the past, we had to discover these things reactively, but now we can run more models to tease out predictive behaviors that are having a positive impact on a business’s bottom line.

For more posts in the Socedo Data Pioneer series, check out our conversation with Heine Krog Iversen on Empowering Business Users with Data.


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