Mike Cullis in The Drum

Everything you need to know about content marketing episode 2

With content marketing, knowing and targeting your audience is critical. Content marketers must ensure their communications are useful, informative or entertaining to readers and viewers – otherwise they won’t be read, or watched.

Today, the role of data to discern a brand’s audience(s) and a wealth of digital channels are helping marketers realise the power of content – little wonder budgets are growing at an estimated 25 per cent a year, according to the Content Marketing Association (CMA).

But as with any fast-growing trend it can be hard to know how to get the most out of your budgets.

Ben Pheloung, head of sales at PulsePoint, says: “Many brands think they know their audiences, and many actually do. But how many of us truthfully know that consumer outside of our narrow brand world? How do they really act, react and interact with online content beyond the ad spot?”

Brands need to create valuable and meaningful stories for the consumer, hitting the right person at the right time – and in the right environment. They need to be conversational rather than salesy and demonstrate their right to be in the conversation.

For instance, a survey from Kentico Software showed that 74 per cent of the public trusts content from business that aims to educate readers about a particular topic. But including a product pitch within that same article would bring the content’s credibility down by 29 per cent.

Another common pitfall is not knowing how much content to funnel to your intended audience.

Penny Bartram, head of marketing EMEA, Bloomberg Media , says: “With a surge in interest in content marketing, there is the risk that brands will create an abundance of content without thinking about who wants to consume it and how.”

Bloomberg reaches an elusive audience that is time poor, tech-savvy and, she says, hard to reach, so it is crucial to create genuinely relevant and meaningful content to capture attention. Data is key in this.

Bloomberg’s data science team uses proprietary digital data to discern reader behaviour, interests and content consumption patterns. “This is invaluable to our custom content editors to help shape the themes and execution of branded content programmes across our channels,” Bartram adds.

Its team also has access to Bloomberg Intelligence, whose analysis provides in-depth insights and data sets on industries, companies and credit, government, economic and litigation factors that impact decision-making. Using such data it can identify, for example, a topic before it’s trending and work with brands such as UBS, Zurich and Oracle to create content around it.

Yet how many content marketers are making the most of the data available to them or their partners? A recent CMA audit found that although 92 per cent of CMA members used customer data as part of their content marketing strategy, only 40 per cent sourced data from clients.

Mike Cullis, founding partner and managing director of CRM agency Soul, says content marketers can learn from the direct marketing industry. “Data has always been a big part of direct marketing’s understanding of where someone is at key decision-making points,” he says, something further fuelled by artificial intelligence (AI) and machine-learning.

First, says Pheloung, a brand must have an idea of who its audience is, a starting point. When used properly, informed by and analysed by humans, machines can bring insights into human behaviour, who are the most likely to engage with different content types, at what frequency, when and what the most appropriate channels for engagement might be.

With real-time access to on-demand metrics a brand can further refine its content or audience and help better engage with readers or viewers.

Continues Cullis: “Context is all important. Ultimately it allows you to learn what the right content in the right place and at the right time is. Over time that allows us to improve and develop the best content in the best possible places and for the best types of people.”

The data may even throw up a few surprises. Pheloung points to a PulsePoint automotive client that had created a campaign geared towards young families – its target audience. Yet the data showed that the people who were actually booking test drivers were much nearer to retirement age. “Is the content wrong, or your idea of your audience,” he asks. “Or is this a potentially lucrative new avenue you hadn’t considered before?”

Some brands may have many different audiences, such as Adidas. Its portfolio allows it to target everyone from professional sportsmen and women to retro lovers and lifestyle audiences through its collaborations with music stars. Even in its sports heritage it could target, with programmatic technology, almost on a one-to-one basis. Imagine at this summer’s Olympics if it were to create niche content for every sport it had an involvement (and implied authority) in.

Such a hypothetical shows why getting the right content at the right time and in the right environment is such a game-changer for marketers.

Machine-learning, coupled with human insight, helps define and refine audiences and in what context, such as frame of mind or environment.

Yet, having defined your audience, how should brands go about reaching them? The third in the series of Everything You Need to Know About Content Marketing will explore distribution strategies and how to maximise investment.

You can read the full article published on the Drum here.