Content fatigue isn’t a new term in the industry, it has been regularly re-surging since 2015 as customers' attention continues to become an ever-scarce commodity.
The average adult already spends 5.9 hours per day engaging with digital media, but they still don’t have enough time to browse and engage with every piece of content heading their way. And yet, this year 57% of B2C marketers plan to ramp up their content marketing budgets compared to last year. This means even more competition for prospects’ attention online.
To revive the dwindling connection with your audiences, it's time to forget the old rules in the book. Casting a wide generic content net won't land you the big fish. Instead, you need to think about creating granular content mashes to capture different audience segments. This is where data science can play a powerful role to help you dive deep into your customers' needs to deliver exactly what they want.
Build emotional connections with your audience
Personal connections are hard to forge at scale but that’s what customers now demand. 84% say that being treated like a person, not a number, is important to winning their business. They expect brands to become that salient whisperer, helping them make up their mind without being too intrusive.
Content and its relevance are the main tools, building up a connection with your audience. According to Customer Thermometer data, people form strong emotional connections with brands in the following ways:
Knowing what your audience wants and when they want it, and how this should be packaged is the kind of information you can get with data science. By using a mix of descriptive and predictive analytics you can decide what content to produce. Marketers using data-backed target personas gain an enormous advantage; they attract less price sensitive customers, improve brand loyalty and achieve higher engagement and conversions from their content marketing campaigns.
Use advanced segmentation to build a 1:1 rapport
“Content that resonates” may sound like another overused industry buzzword but to capture and sustain your audience's interest, you need to understand who you are speaking to. Users come to your website with different intentions – to browse, compare deals, receive information and so on. By giving them content that speaks to their at-the-moment need, you gain a firmer ground for further interactions.
Data science enables you to spot different behaviour patterns among different audience groups; capture those titbits into a comprehensive profile and then suggest what kind of content will resonate with a specific user depending on:
- Their demographics;
- Brand affinity – prospect, returning customer, expert product/service user;
- Past actions – purchase history, on-site interactions, response to discounts etc.
Beyond that, using a prescriptive analytics platform like Apollo Insights, you can further determine content gaps in your sales funnel; missed topic opportunities and new content types for specific personas.
Deliver hyper-personalised content recommendations
Machine learning, as a subset of data science, enables unprecedented personalisation. What’s even better, ML-powered systems become even more precise with their mind readings overtime as more data enters the system. And that data is getting easier to obtain. According to Salesforce’s State of Marketing 2018 report:
- 79% of customers will share their data in exchange for contextualised engagement.
- 88% will do the same for personalised offers.
For businesses this creates new opportunities for building a 1:1 rapport with their audiences.
NZZ, a Swiss newspaper, recently concluded a beta test of their personalised news app, developed together with Google's News Digital Initiative. They've added several instruments for distributing content based on data:
- Personalised content curation. All-in-one news streams like the personal news companion, personalised newsletters etc. based on either personal or editorial relevance.
- Group-based automatic content curation. Content is curated based on certain interest groups – for instance, users from specific geography.
- Topic-based automatic content curation. Custom content lists and newsletters can be generated by specific topic, depending on the users’ known preferences.
- Context-based automatic content curation. Recommending articles that fit into expected commute time.
The response from their readers was overwhelmingly positive. 84% of beta testers said that the new product added value to them. Among the top benefits, readers further reported quick access to new content, easier discoverability, attractive design and the overall feeling of being better informed.
The good news is that to battle content fatigue through personalisation, you no longer need to develop new products from scratch. Economia media company uses Recombee – a Recommender as Service app that delivers dynamic recommendations for individual users. By switching to AI curation over editorial, the company achieved a 64% lift in conversion rates.
Content fatigue is real, but it doesn’t mean that content marketing is no longer working. On the contrary, consumers today are as receptive as ever to personalised advice and information. It’s the irrelevant, generic content that goes under the radar. By backing up your strategy with data, you are 2X times more likely to connect with your prospects and win over their attention, and ultimately their business.
Chris Pitt is head of marketing at Vertical Leap