Once upon a time, in the not-so-distant past, content marketers put most of their energy into creating copy crammed with the best search keywords at the lowest possible price. However, Google found that businesses were writing pages of (often meaningless) content purely to please web crawlers, rather than human beings.
As a result, the search engine encouraged marketers to change their ways. Content now needs to be valuable, relevant and compelling – satisfying the people who are consuming it and encouraging them to take action. But is it really possible to please all of the people all of the time?
Yes, this is where data comes in. It is staggering how much data being generated online has increased over such a relatively short time. Search interactions provide insight into intent while interests can be uncovered from social media interactions. Both generate significant volumes of data that can ultimately provide valuable insights for content marketers.
Search data is one of the best indicators of user intent online and if you understand the user’s intentions, then you can adapt your content to suit their needs. It is, therefore, one of the most crucial pieces of information in helping inform a content strategy.
Essentially, then, an important aspect of search data analysis is the art of detecting a need. By looking at website analytics and investigating which keywords are driving traffic, content marketers can uncover potential opportunities to create content that the audience really wants and needs.
User intent can determine your content marketing success, but it’s important to keep this customer-centric approach in mind at all times: write for the user, not for the search engine. Even though higher quality traffic comes from long-tail keywords, you should still remember to focus more on producing helpful and relevant information relating to these major keywords, than the exact keyword phrases themselves.
Data generated from people’s insatiable appetite for social media over the past decade has provided a treasure trove of insights for content marketers. Social signals include: the profile of the user and their interests; what they are sharing, ‘liking’ and commenting on (earned media activity); hashtags, which enable marketers to track specific topics that can help with their overall social content strategy; and a user’s online contacts, which can dramatically increase a brand’s exposure.
It can also help your brand’s bottom line. In a recent study, social data and sharing tool ShareThis revealed that products which had had positive reviews shared online saw a 9.5% lift in purchase incidence.
Social data was one of the data sets Virgin used to help inform its website’s content strategy. By looking into what its users follow on social platforms together with the views and interests they express, Virgin was able to build up a picture of its audience’s needs, motivations, emotions, frustrations and goals.
Further analysis around the performance of Virgin’s content on social media enabled the brand to make informed decisions around the content and placement on the new virgin.com site. (Source: @beyond).
Virgin’s analysis of social data to improve the user experience is smart and a fairly simple thing to do. Somewhat surprisingly, however, it’s an approach used very little by brands.
Blending search and social data
In order to stay ahead of the ever-evolving game, marketers need to be able to strategically pair search and social signal data. The insights available in these data sets enable marketers to get a better understanding of their customers at different stages of the customer decision journey.
Knowing what’s going on in the customer’s mind at each stage helps the marketer produce relevant and valuable content designed to move the customer through the journey.
Predictive content marketing
So what does the future hold for data and content marketing? As technology and innovation evolves at an ever faster rate, this opens up more and more possibilities for marketers to tap into big marketing data in order to dial up performance. With marketers having constant access to data, providing insight into people’s digital footprints and behaviour, the next evolution will be the real-time production of personalised, targeted content.
Predictive content marketing promises to use data as the raw material to ensure the right content is always being delivered to the right person in the right place at the right time.
However, there is a challenge and brands will need to tread a very thin line. Getting closer to people with valuable, relevant content should be a win-win, but people should not feel as if their personal data, or privacy, has been exploited in the process.