Why Content Marketing Success Depends on Diverse Data

Without diverse data sources, content marketing only sees part of the target audience. Knowing what data to use how to apply it to content marketing is a critical success factor.

Vin Vashishta | Originally Published: May 20th, 2015

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Diversity. It is good for hiring and good for perspectives. It is also a key to content marketing done right. The first rule of marketing analytics is customers do not go to the same place to learn about brands so brands cannot go to one place to learn about customers. No place is that rule more important than in content marketing.

Breaking Through the Silos

Data silos between groups in the same company are a well know pitfall but silos can be built around a single data source as well. The two most common analytics silos I see are social media and the company website. The pitfalls of social media analytics are well studied. Company website analytics fall into much the same category. Both sources provide rich datasets but not rich insights into customers. To understand why we need to explore how data becomes insights.

Data becomes an insight when we can recognize a pattern and explain its significance. The reliability of those patterns is only as complete as the dataset they are based on. Data from sources like Twitter, Facebook and website behavioral analytics feels like a complete data set because there are high volumes of people with diverse backgrounds being represented. However, that is not the same as a data set which represents the target market. Analytics driven marketing efforts are blind to the needs and preferences of customers it does not have data on.

Stepping Out of The Data Comfort Zone

For content marketing, that means entire segments of interest are going unserved. Topics are being overlooked and sites customers frequent on their path to purchase are being ignored. That is why a complete picture of the target market is so important to content marketing. The first and second information sources a marketing team turns to are usually within a brand’s comfort zone. This is where incremental insights can be discovered and that is a great place to start. The real gold lies outside a brand’s comfort zone in data sources that describe customers the brand has not gotten to know very well.

What is the right mix of data sources? The answer to that question is driven by the customer journey. Some of the best data comes from examining customer journeys that do not lead to the business’s brand. These journeys never touch a brand’s social media presence or website, so they push marketing analytics teams outside the brand’s comfort zone.

Follow the Customer Without Being Creepy

Following the customer and discovering these new data sources is a bit of a forensic effort. Data brokers and 3rd parties that provide onboarding data services are invaluable in this process. It is also time to start talking with customers and asking questions at every possible interaction. Every customer interaction point is an opportunity to capture data or lose it. By providing customers with easy ways to give feedback and very selectively asking for feedback, brands take advantage of those opportunities.

Here’s where companies can make choices that paint them as creepy stalkers or overbearing. Customers expect brands to use their data to provide a personalized experience. Customers also expect brands to keep a respectful distance in the process. There is a lot of grey area here. My rules are simple:

  • Do not get too close. If a customer feels like they are being followed or tracked, the brand has crossed the line.
  • Stay transparent. Responsible brands gather data to provide better products and more relevant marketing. Why hide that?
  • Do what the customer asks. If a customer shares their individual preferences and a brand does not follow through, there is a loss of trust.
  • Be responsible and ethical. What would the customer think about how the brand gathers data and what it does with that data? Customers will eventually learn the answer to that question. The gains of grey areas are not worth the backlash.
  • Keep data gathering out of the customer’s way. Data gathering gets overbearing when the purpose of interactions shifts away from satisfying customer needs. Data gathering should always be secondary to customer satisfaction.

  • Disney owns customer feedback in a way few brands surpass. Their surveys are infrequent and only ask the questions they need to create an amazing customer experience. The questions are thoughtful and aim to understand a guest’s individual preferences. After a guest answers the survey, Disney does what the guest has asked. From communication content to frequency, the brand tailors their marketing to make a guest feel like they are listening. That builds an amazing amount of trust and good will which leads to loyalty.

    Using All That Data to Create Amazing Content

    Once all that data is gathered, it is time to ask the most important question in analytics, “Why?” Why are customers going to a site? Why do they trust one review over another? Why do they choose to interact with the brand or a competitor’s brand? All this data gathering revolves around getting to know customers well enough to craft content that is less like a sales pitch to a stranger and more like a conversation with a friend. That means it is time to let the data science team turn data into insights so the marketing team can do what it does best. Start conversations that make personal connections, turning a researcher into a buyer and, longer term, a loyal customer.

    One of the best data driven content marketing efforts I have seen is Starwood’s W hotel brand. Their content and videos are masterful. However, they did not start out with the goal of creating engaging content. Their path to content marketing started with a desire to know their customers so they could best serve their needs. Data gathering and diverse data sources were a part of that but did not become the focus. That is key to succeeding with content marketing or any kind of marketing for that matter. Analytics must be drivers of marketing decisions without becoming the focus of those decisions.

    W’s marketing team redefined how the industry understood a new type of luxury traveler. Rather than staying in their data comfort zone, they talked to travelers who were not visiting their properties. They discovered a large segment of the market with completely misunderstood needs.

    Incorporating those needs into their marketing efforts allowed W to tell customers through their content marketing, “We listened and have built our brand around what you want.” They understand their customers are at a W property for an experience and they use content to get people excited about that experience. They understand the luxury traveler wants personalization and they create content showcasing the property’s ability to deliver what the customer expects.

    There is a big difference between brands that stay in their data comfort zone and those that venture out with diverse data sources. As customer expectations for personalization continue to rise, that divide will grow and become more obvious. Brands that are not making the extra effort will find it difficult to compete.