Nick Mason, CEO of Turtl, explains how finding the right metrics and ensuring deep personalisation can enhance a content strategy.
Financial services marketers have always faced an uphill battle when engaging their audience, whether it’s translating industry jargon into something digestible by consumers, or driving engagement with key stakeholders pressed for time. As tough macroeconomic conditions and geopolitical tensions continue, the pressure is on FS marketers to make every piece of content deliver against business outcomes.
A recent study by Turtl revealed that only 42% of marketers rate their strategy as ‘very successful’. Those who felt they were successful in their content marketing strategies attributed this success to using data and analytics. For marketers in the FS space who wish to embrace a data-driven approach and make their content count, here are three data-led best practices.
Measure the right metrics
If you’re running an email campaign, it doesn’t matter how many page clicks your content receives if no one reads it. This is why we’re seeing novel approaches in embracing the metrics that matter such as reader engagement and read time. Just last month, The Guardian announced that alongside the traditional ‘Most viewed’ recommendations, they would now be recommending content that has been ‘Deeply read’, i.e. the articles that readers are spending the most time with.
Ultimately, there is no single metric out there to measure the success of content. Instead, marketers should be assessing which metrics are relevant to specific objectives. As Seth Godin once said, “don’t measure anything unless the data helps you make a better decision or change your actions.”
Align the metrics to your funnel. E.g. awareness, consideration, conversion, retention, and advocacy stages. Awareness could include how many new visitors your content is attracting or media coverage. Consideration would include data on returning visitors, form completions or time spent reading. Conversion could include requests for more information, or subscriptions to a new financial product, while retention metrics could look at email open rate, visit frequency and customer lifetime value. Finally, advocacy could include referrals, cross-sells, testimonials or case study performance.
Whatever the stage of the funnel, first party intent data can be integral in helping marketers understand who to target, what to say and when to say it.
Data-driven personalisation
The effectiveness of personalisation is widely acknowledged, yet our research showed that data isn’t being used to its fullest extent when personalising content. While 75% of businesses think they’re excellent at personalisation, just 48% of customers agree. More specifically, 100% of financial marketers saw benefits through personalising their content, yet only 10% personalise consistently. With many marketers using superficial personalisation such as addressing customers by name.
While basic personalisation might make use of light CRM data, there’s also an opportunity to use analytics to drive deep personalisation – and we know this can increase engagement by up to 84%. For example, if you give users the ability to self-select content that matters most to them – it’s worth monitoring the impact of this on user engagement. By understanding these analytics, you can automatically surface what each reader is most interested in to further inform personalisation.
If you see engagement metrics like dwell time decrease on long-form content it’s highlighting that users aren’t reading all of the content. Consider experimenting with video, or breaking documents up into skippable sections so the reader can choose to consume what interests them most. It’s also a good idea to survey people directly to find out more about their interests and use this information in the future.
In-depth analytics data can be used to inform the next step in the journey rather than as a one-off. For example, if a reader recently consumed a blog post on cyber security, it makes sense to target them with a whitepaper on the same topic. This kind of tactic then becomes a program of activity that includes sales outreach. Sales teams can also be alerted to key topics that prospects have read and be better prepared when they contact them.
Benchmarking your efforts
Once you’ve identified which performance metric is most relevant to your campaign, it’s worth looking back at past efforts to see how they’ve performed historically. With this insight, you have a benchmark to devise content KPIs and improvement targets. Too often businesses publish content without going back to review and refine based on the data of how that content is performing. Establish benchmarks on what good looks like using relevant metrics, then assess performance after a set period of time. Once you have this, it’s then possible to make changes to improve performance and repeat that cycle.
Consider how content performs compared to industry benchmarks and analyse what you can do to stand out from the crowd. Successful businesses also understand the role that behavioural psychology can play in marketing. Measuring how well you’ve incorporated these tactics could offer another metric. The majority (52%) of successful content marketers use insights into reader intent and page dwell time.
It’s equally important to establish methodologies for applying your data to see real value from it. For example, the content might perform badly on social media but attract substantial organic traffic. Be wary of superficial metrics. A report that was opened by five people who spent at least 30 mins interacting with the content and happened to be senior decision makers is far more valuable than a report opened by 2,000 who skimmed the content in five minutes and don’t sign off budgets.
CRMs are able to present the bigger data picture through integrations but there is still some way to go when it comes to teams connecting their entire MarTech stack. Marketers need to combine data from different sources to fully appreciate how their content strategy is performing.
In summary, our data shows that very successful content marketers are more than twice as likely to take a strongly data-led approach to their B2B content marketing. Implementing these three data-led best practices will lead to better results across the board.
