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How to Become a Mad Marketing Data Scientist

March 7, 2016 | Chad Koskie | 1 Comment |

If you’re like a lot of marketers, the era of big data probably leaves you a little anxious.

After all, most of us got into this field to do creative things. No one majored in marketing, or took that first marketing job, with high dreams of of adhering to a number of leads or revenue figure they have to associate.

In the past, marketers operated mostly on gut instinct. But over the years, numbers have slowly crept onto the scene—quantitative research, focus groups and analysis became basic tools of the trade.

The next great shift, however, is automation. Arguably, it’s already here. And it requires not just new skills, but a new perspective and that will be a much harder bridge to cross. That said, which skills must marketers master in order to become functional, makeshift data scientists themselves?

Here are what we consider the big three.

Data Collection

Ask yourself: What data is absolutely critical to collect in relation to your prospect base?

This is the information that’s commonly asked on forms – but it doesn’t stop there. Marketers should have a solid data append strategy. Once the buyer fills out a form with basic information how do we add supportive elements to that data profile?

You don’t want to ask for information that will cause friction during the form experience – information like location, firmographic info and business size – these elements are easily gathered from data providers (at LeadMD, we use Datanyze) and will allow you to build a comprehensive profile for each lead.

Use this same strategy with social-sign-in (like LinkedIn) to gather hundreds of data points that can give you insights into the buyer’s preferences. At LeadMD, we hit 4 different data providers and literally dozens of databases each time a lead is created.

Data Standardization

Make sure you’re storing your data in ways that can be summarized and reported upon. From simple tweaks like translating job titles into common values, to utilizing pick lists that provide standard values rather than open text fields, data standardization is as important as data collection.

If you can’t make sense of your data, you’ll never be able to use it to build useful data models required to leverage big data. Another key element of data standardization is field validation and workflow-based population. It’s a bit more complicated, but if you can ensure data collection happens at relevant times in the marketing and sales process you will develop the insights necessary not only for predictive data analytics, but for basic marketing best practices such as persona creation.

Finally, Data Capture Optimization

This rounds out the core marketing functions marketers want to adopt from scientists.

Data capture is best conducted after the lead is passed to sales. This seems counter-intuitive, but stay with me. Think about all of the personal interaction that takes place once the buyer begins interacting with sales – and where is it normally stored?  That’s right – in a notes field. Or, even worse, it says within the mind of the sales rep.

Marketers need to become experts at creating a process that incentivizes the sales team to input critical data into a standard format. This is much larger that simple requiring fields – a required field gets just enough information to move past that hurdle. At LeadMD, we send out an automated survey at the end of each deal (win or lose) to collect as much “in-head” data about the deal possible.

If you create an engine where the data points actually drive the type of supportive messaging and content that marketing can deliver to assist in the sale, then you will get sales to participate in this critical process.

Optimize your data capture process to get insight into sales conversations and you will have the data necessary to repeat those conversations.

In conclusion

While the goals of marketing haven’t changed all that much, the way those goals are measured have presented new challenges to the marketer of tomorrow.

While you may not have dreamed of data science when you got into marketing, there’s no debate that it will become an increasingly large part of your day-to-day flow. It’s up to you to use it!

Have questions? Hit us up on Twitter or a leave a comment below.

1 Comment

  1. Josh Rhodes on May 24, 2017 at 12:21 am

    Hi Chad Koskie ,Great blog.Information like location, firmographic info and business size – these elements are easily gathered from lead generation softwares like Datanyze, AeroLeads etc with Rapportive as it speeds up the work and do a lot more than just verifying emails.Will allow you to build a comprehensive profile for each lead

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