I don’t know if it’s just me, but all these global startups seem to go crazy about collecting and leveraging data for their go-to-market. More and more enterprises start to wonder why and if they miss a boat? Well, there’s one reason behind it which I call the "90% revolution“ and – spoiler alert – it will probably change the way we go-to-market forever.
Let’s say your company has a 10% market share. In the offline past, your IT systems could only operate with your own first party data mainly collected from customer transactions (so, 10%). In the digital era though, customers use dozens of 3rd party systems, mobile and social, to discover, research, buy and use products in real-time.
Now, the anonymous data sets behind these buying signals become accessible as advertising and marketing technology converges. And here comes the "90% revolution“: if third party data for nearly all of the market buying signals becomes available as a service, doesn’t operating sales and marketing with the old 10% in-house data only feel like "flying blind“?
In other words, is Data the New Marketing?
Let’s cut through the hype with three real-life use cases:
First, why not start with significantly decreasing your Ad Spend without negative impact. How? By real-time filtering your existing customer data from paid search or display advertising, you avoid double-spending to reach contacts you already know. Think of it, it’s amazing how often returning customers click on Google paid-search just for ease of use. And besides saving money you also look less creepy not addressing loyal customers as prospects on all channels. Btw, this "classic“ use case alone creates an immediate ROI for most customers of the Oracle Data Management Platform (DMP).
Another use-case is called Look-Alike modeling. It means to match your own best customer data with 3rd party data sets in the audience who digitally "look alike“. If these anonymous prospects then visit your websites or see your advertising, you can customize any communication in real-time to drive conversion. This use case demonstrates modern marketing is all about context in every customer interaction – data is just the tool.
Intent data is my favorite use case, as it helps transforming advertising from "shouting“ to "listening“. How? Think of all the interactions on eCommerce, financial, retail or travel sites indicating our intent to buy something. Like searching, reading blogs, product comparison, loan calculators, etc. By adding up single cookie ID signals to meaningful intent data sets, companies can now address prospects in a highly relevant context – while the individual always stays anonymous.
For best practices when it comes to data, download the Modern Marketing Essentials Guide to Data Management. This guide uncovers tips like the customer ID Graph concept to help marketers define marketing and communication goals with a data audit, be more strategic with the information you’re collecting and accessing and a lot more.