If 2015 was the year of video marketing, 2016 is primed to be the year for smarter, integrated digital strategy. According to a Gartner survey, marketers no longer see digital as a distinct marketing discipline and marketers are moving to “digitally led business models.” In other words, brands are planning to increase their investment in digital commerce in an effort to make a clearer connection between digital marketing spend back and business revenue.
So what trends will drive digital marketing success in 2016? Brendan O’Kane, CEO and founder of digital marketing platform OtherLevels, points to convergence, “smarter” machine learning and a focus on developing high quality content as the engine behind digital marketing performance this year.
Multimedia Convergence: The mobile revolution has led to consumers engaging in second and in some cases third screen experiences. With 25 percent of consumers using at least three devices to interact with multiple channels on a daily basis, there’s lots of data marketers can use to develop better consumer profiles. The challenge and opportunity is in consolidating data under one platform to take guesswork out of determining which channels to use, which message and what time is best for reaching certain consumers.
Still, O’Kane notes that there will be times when it’s impossible to aggregate all the data. He says marketers need to think beyond email to leverage other opportunities to engage anonymous users.
Social logins help, but many app users do not authenticate naturally. Email addresses are barely useful for identity tracking these days. So if a user does not want to register/authenticate, marketers should continue to engage with customers or users in that channel until a level of value and trust is established.
“Smarter” Machine Learning: Pulling together and sifting through all of the data made available through digital media might seem daunting, but marketers don’t need to become data scientists. Instead, O’Kane says marketers need to improve their machine learning capabilities to develop better consumer profiles.
This gives marketers the ability to interact with their customers on an individual level, improving engagement and increasing the likelihood of retention.
O’Kane also warns against falling into the belief that machine learning is a silver bullet. The real power of machine learning, he says, is in using it to automate daily tasks, develop better consumer insights, and ultimately free up resources to develop better marketing messages.
Content is still King: With resources freed up but automation and machine learning, O’Kane says marketers will be able to focus on what’s really important — developing “truly personal and relevant content that speaks to their customers directly.” Cross-channel strategies require content optimized for each channel and distributed in a multiple formats while maintaining a seamless brand experience. The challenge here is using engagement data to track actions and outcomes to improve personalization over time.
The biggest gap that we see consistently is the inability to attribute outcomes to campaigns at an individual user level. Brands are capable of driving some level of engagement, but because of poor attribution, they cannot track the outcome of that engagement.
Without tracking outcomes, marketers will lack the ability to develop personalized campaigns that speak directly to customers. Ultimately, O’Kane says you can’t force consumers to use a particular channel, so it’s important to meet customers wherever they are.
You might have invested heavily in a fabulous app, but some users simply prefer using the desktop or mobile web. Accept that fact, learn how they behave in that environment (machine learning can help), and engage with them where they are.