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Marketing Analytics :: Sergei, CIO

Marketing Analytics :: Sergei, CIO 2017-08-09T19:33:41+00:00

Sergei’s top needs for a Marketing and Sales platform are:

  • Deliver reliable IT services to support sales
  • Define uses cases for predictive analytics to support marketing, sales, and CRM
  • Ensure systems provide robust value with scalability, interoperability, and data integrity

Why he needs help:   Sergei was trained as a computer scientist and has built his career on creating stable systems for storing operational data with high reliability and low cost. But now departments outside of IT are demanding a seat at the table as they are the main generators of profit for the company. But the way they use data – to run campaigns, evaluate results, build predictive models, and assign lead flows – are all new and not necessarily accommodated by the data structures currently in place.

How Beyond the Arc supports CIOs like Sergei:

  • We can translate marketing and sales needs into use cases
  • We show how data flows are not always linear so IT can plan appropriately
  • We help IT understand special data staging and data history needs that predictive analytics uses to support marketing and sales

I know what a good technology platform needs to support general operations. But now it needs to satisfy more flexible and ambiguous needs of marketing and sales. I think requirements should be well defined in advance, but marketing and sales people say their processes change quickly and evolve through iteration. I need new information to see how this paradigm works without negatively impacting the performance and stability of our operational systems.

Our take on marketing technology platforms

The goal of technology goes beyond simple execution of sales and delivery of services. Modern marketing and sales systems require broader capabilities including sandbox space for data science experiments, and the ability to administer campaigns that track customers, campaign exposure, and outcomes. Beyond the Arc can help IT organizations bridge knowledge gaps in order to define robust and scalable IT implementations.

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