There's no denying that content marketing is a growing trend. A survey by the Content Marketing Institute revealed that 70 percent of B2B marketers are creating more content than they did just one year ago. Unfortunately, their research also revealed that 58 percent of marketers don't feel they are effective at content marketing, and measurement is a key area where marketers are struggling. In order to drive results, marketers must understand how data science can be used to drive user engagement in the digital age.
New technologies and the evolving media landscape are changing the way consumers discover and purchase products. According to Forrester Research, a buyer might be 66-90 percent of the way through their purchasing journey before even contacting a vendor. Forbes also reports that only 1 percent of Millennials say advertisements build trust in a brand, while 33 percent say they rely on blogs before making a purchase. While marketers agree that the key to navigating this new landscape is consumer insights and data, how to use data for content marketing success is still unclear to many. Here are four key ways marketers should be applying data science in order boost content results.
Joining the (right) conversations
To get consumer attention, marketers need to understand what's important to their audience. What are consumers talking about, and where do they share information? By researching, brands can identify what themes are getting the most traction amongst their audience and which topics are most relevant to their consumers' needs. Brands can then use this insight to create targeted content that can guide conversations and influence purchasing decisions.
There are many ways to anecdotally gather this data via Twitter, LinkedIn, blogs, and social media monitoring tools. However, organizing information, ranking trends, and identifying opportunities can become a daunting task given the volume and pace of these conversations. Managing this avalanche of data requires either a data science team or platform.
With data science, brands can utilize algorithms to analyze thousands of sources every day. Data mining can be used to separate facts from opinions, define trending issues in particular market segments, and surface the most influential themes for any given topic. Most importantly, data science can identify opinions that generate truly high impact reactions by being quoted in top publications and shared by influencers, instead of those that simply generate raw engagements such as "likes", "retweets", or "shares" from the general populace. All this information is key to developing a proper content marketing strategy.
In any given industry there are a number of personas driving conversations, including buyers, sellers, journalists, and brand enthusiasts. Each persona brings a unique perspective, reputation, and voice to the discussion. The most successful marketing campaigns work with influencers to attract new audiences and build trust amongst consumers by sharing articles, guest-posting, and leveraging existing networks.
But how do brands learn which voices will be most relevant to their product and service, and how should brands engage these influencers? While influencer lists can be compiled manually, data science can provide a true competitive edge here. Data science allows marketers to compile a long tail list of influencers instead of simply gathering the top few, and at the same time can identify influencer sentiments, distinguish between organizations and individual influencers, and separate bursting influencers from those with an earned history of influence. All this allows marketers to align with the right voices and extend the reach of their brand story.
Distributing engaging content
Having the right people talk about a product or service won't mean much if a brand isn't making smart decisions about how to share, amplify, and promote their content. Simply publishing a whitepaper or blog post isn't enough to make an impact. Marketers need to be Tweeting, publishing, Instagramming, Pinning, and Snapchatting to be heard amongst all of the noise. To get the right traffic to their content, marketers need to promote every asset through targeted organic appearances on the channels their audiences use daily.
Choosing the right channels to promote content is essential to ensuring brands don't miss a great opportunity. Data science again can be used to identify patterns: which outlets are best suited for their audience, where influencers are most likely to comment, where to drive discussion, and which public relations opportunities can be leveraged.
Tracking the impact of your brand
Data is not only useful for planning and executing content, but also for tracking the impact of your brand. Many content marketers track KPIs such as clicks, pageviews, downloads, likes, follows, and shares to evaluate the effectiveness of their content. However, these metrics can't measure the aggregate impact of an entire program. To accurately measure the effectiveness of content, marketers need tools that will provide predictive modelling that can give them insight into past performance as well as future behaviour. It's about moving beyond multi-channel attribution modeling, and data science also allows marketers to analyze specific market segments and can apply analytics to measure the brand's share of global attention. These algorithms help brands establish a more complete picture of their influence in the marketplace.
Navigating the future
In our "always on" culture, getting audience attention is becoming more and more difficult, and disruptive ads are proving ineffective. In this new media landscape, many organizations are turning to content marketing. However, many marketers still find it challenging to consistently produce engaging content.
How do marketers address this challenge? As social media and content marketing influencer Jeff Bullas states in a recent blog post, "data is going to be your secret weapon...knowing more about your customer than they know about themselves is marketing power." Embracing this approach allows marketers to solidify the foundation of content creation and ensures that brands can be heard above the noise.
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