Connecting Online Behaviors with Offline Transactions

Consumers today engage with brands and companies in more ways than ever—via websites, social media, mobile devices, ATMs, RFID tags, in-store traffic, kiosks, call centers, interactive voice response (IVR) systems, and more. All of these interactions have two main things in common. First, they generate massive amounts of rapidly changing and largely unstructured data. Second, most available tools used to analyze large volumes of data trade off the breadth and depth of the analysis with the time it takes to arrive at meaningful business insights.

I am pleased to announce that Adobe Analytics received a perfect score in the recently published The Forrester Wave: Web Analytics Q2, 2014 report offline channels category. According to Forrester, “offline marketing and additional digital channels can be incorporated into (Adobe Analytics digital) data” to “expand the understanding of the customers with total lifetime value or marketing channel preference information.”

As marketers, making the decision to allocate ad spend is no longer as simple as deciding between print, radio, and TV. Now we have an abundance of options: Facebook, Twitter, YouTube, tablets, smartphones, search, email, display, online videos, crowdsourcing, websites, ecommerce, m-commerce, online communities—the list goes on and on. Tools like Adobe Analytics can help you make smart decisions to allocate across all your digital and offline channels.

A key capability of Adobe Analytics is its ability to automatically associate past behavior with attributes collected based on new customer behaviors. Imagine specifically tying a customer ID of a newly acquired customer that visited a site today and mapping it to that user’s past Web behavior that was—until today—associated with an unknown visitor. This retroactive event processing feature allows marketers to tie the customer’s value to marketing campaigns and online content that happened across a broad time span, enabling complex cross-channel attribution analysis.

I recently spoke about the importance for marketers to leverage enterprise Big Data to deliver new, actionable insights about customers at both Adobe Marketing Summit EMEA and the Big Data Innovation Summit. Adobe Analytics’ deep customer analytics capabilities powered by an advanced data workbench enable marketers to correlate transactions and interactions across all channels to gain a more complete, 360degree view of customers. The predictive marketing built into Adobe Analytics allows marketers to identify hidden behaviors and recognize patterns among Big Data, bringing data science into the marketing realm. Advanced capabilities such as audience clustering and propensity modeling enable marketers to better target customers with relevant messages delivered through the best avenues.

These are just a few of the powerful online-offline customer analytics capabilities that Adobe Analytics offers. This is an area of focus for Adobe, and I look forward to sharing future innovations that will help improve overall business performance as we release them.