Home Data-Driven Thinking Mastering Content Distribution in a Cross-Channel World

Mastering Content Distribution in a Cross-Channel World

SHARE:

“Data Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Pete Sheinbaum, CEO of LinkSmart, which provides text-linking optimization solutions for web publishers.

Today’s consumer expects a lot from her digital devices. A busy parent looking for Mario Batali’s latest linguini recipe may do a little Googling at lunch from the desktop, forward the recipe and shopping list to a smartphone for the supermarket trip, and then read/watch the “how-to” in the kitchen on an iPad while whipping up the meal in real time.

Within this common scenario sits a matrix of consumption data unique to each publisher. When analyzed and understood, this data can maximize content engagement. First, a warning: If you simply repurpose content across different devices and applications, you will quickly find yourself and your brand left in the dust. Instead, the place to start is with information you already have, but may have overlooked.

Analyzing how people consume content and interact with different platforms can tell you a lot. Publishers must invest in a strategy to decode how traffic patterns differ across multiple devices, locations, and times of day. Each of these metrics provides valuable insight on how to adjust application and distribution strategies for optimal performance; every visitor announces how he or she accesses your sites and apps, so don’t overlook them. However, integrating all this as a publisher can feel like trying to boil the ocean.

To optimize engagement in this cross-channel world, it’s easier to take it step by step. First, consider the end goal of your user and the multiple devices she will use to accomplish that goal. A recent Google study found 90 percent of people move between devices to achieve a task, using an average of three different screen combinations each day. Google further breaks this down by defining two types of multi-screen use: sequential usage refers to moving from one device to another at different times to accomplish a task, and simultaneous usage means using more than one device at the same time for either a related or unrelated activity. In the digital world, not all devices are created equal. Therefore, as a publisher, it’s not only critical to optimize your content for the individual device, but also to make the end-to-end experience from device to device as seamless as possible.

Secondly, consider your audiences’ unique usage patterns across time of day and week. comScore released a study detailing the types of devices and times of week that people consume their news: Computers are most heavily used during work hours, tablet usage peaks during bedtime, and smartphone usage is interspersed throughout the day. While this pattern may seem common and intuitive across multiple verticals, it’s best to understand your unique audience by using a tool like Google Analytics and filtering by the hour. How and what users consume over time does vary and understanding these individual use cases is critical for maximum engagement and creating a seamless experience.

Lastly, it’s not just what content, or on what device, but the location where users consume media that matters. Interactions with a brand’s content extends from the home to the office and back. Publishers looking to extend their relationship with users must build meaningful experiences tailored to these different locations. While a multitude of mobile apps try to incorporate location-based targeting, a large gap remains between what’s perceived and what actually happens in the user experience. As an article in AdExchanger highlighted last month, publishers and marketers can be taking actionable steps toward improving this experience. From understanding users’ proximity to restaurants and shopping malls to using this information to trigger push notifications, a more connected experience will benefit both the consumer and the brand.

The ability to capture visitors by creating appealing applications and content that caters to different devices, as well as time of day and location, can mean the difference between keeping and losing a user. So while an integrated and tightly woven content strategy may require some meaningful investment, it’s always cheaper to keep a customer coming back than it is to recruit a new one.

Follow Pete Sheinbaum (@sheinbaum), LinkSmart (@linksmart) and AdExchanger (@adexchanger) on Twitter.

Tagged in:

Must Read

Single continuous line drawing robot riding pencil rocket flying in the sky. Tech education and creativity. Future technology development. Artificial intelligence. One line design vector illustration

Q3: Omnicom’s Media Business Is Growing, But Is It Agent-Proof?

If AI agents can plan and buy media, who needs a holding company? Good question. It came up during Omnicom’s Q3 earnings on Thursday.

Netflix Touts New Measurement Capabilities As It Struggles With “Modest” Engagement Growth

Netflix’s revenue grew 12% YOY to $12.9 billion in Q3, which it maintains is in line with its forecast. Its ads business, however, is lagging slightly compared with expectations, causing Netflix to tweak its forecast for the rest of the year.

Apple Publishes Its Plan To Wipe Out Web Tracking

Apple is coming for identity resolution. WebKit’s latest tracking crackdown targets the infrastructure behind post-cookie IDs – and switching to a first-party setup won’t necessarily spare vendors.

Privacy! Commerce! Connected TV! Read all about it. Subscribe to AdExchanger Newsletters

AI Slop Sites Are On The Rise. Is Ad Tech Ready For Its New MFA Challenge?

Advertising supply chain intelligence company DecryptAds uncovered more than 2,100 AI-generated recipe sites that are monetized with programmatic ads and feature fabricated author profiles.

How Australian Home Lender Lendi Measures The Invisible Work Of AI

Most brands and businesses are trying to figure out how to improve their metrics when it comes to AI – and also what those metrics even are.

AI Startup Minerva Built An Agentic CDP, But Don’t Call It That

Minerva wants to turn fragmented customer data into something marketers can use, with AI agents doing the work behind the scenes.