Putting Big Data to Work for Marketing

We pulled our Marketing data together into a Data Lake in just 60 days. Finally, we can connect all the dots.Big Data technology is a perfect fit to answer questions like “which programs work?” and provide account views for Account-Based Marketing.

There is plenty of technology out there and many businesses feel they are “just one app away from greatness.” Most of these apps are only good for one thing: they take a siloed and partial view and they don’t integrate naturally with anything else. The result is like looking through 15 straws to make sense of the objects in the pool below. Although we, at Informatica, didn’t quite feel we were “one more marketing app away,” we did know that we couldn’t win the war with a siloed view of data.

The analytics available in many of the available marketing apps have gotten quite good, yet most marketers still struggle with answers to questions like:

  1. Which channels are driving the most net-new names that eventually convert into customers and revenue?

2.   Who are all the members of a buying team we need to influence to have the deal go our way?

3.  What is the value of the different marketing touches that eventually lead to not just an opportunity or pipeline, but revenue, both booked and banked?

It is easy to understand impressions, click-through rates, conversion rates, and cost-per-lead for paid media. But, particularly in B2B, when you run your trusted Salesforce pipeline report and filter for paid media as the lead source, often the resulting number looks disappointingly small.

How it works?

Basically, these are the steps we took over 60 days:

  • Brought together data from various marketing apps—Marketo, Salesforce, Adobe Analytics, Lattice predictive lead scores, Demandbase demographics for user’s IP addresses, RioSeo social sharing data, and LinkedIn—into one centralized marketing data lake (Hadoop) using Informatica Big Data Management
    Used Tableau to build a single view of all the integrated data
  • Created a data pipeline to deliver fast results to queries
  • Developed use cases in an agile approach as we created the marketing data lake
  • Designed a means of continually monitoring data quality and integrity

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