One of the challenges facing content creators is how to create consistent, meaningful content. All of us experience spammy weekly (or daily) emails of irrelevant content, and perhaps wonder if some of our content is received so unfavorably. Keeping content fresh and relevant for readers can be difficult.
One way that some businesses create compelling content is to anonymize and aggregate some of their customer data. Using owned data, businesses can identify unique trends and insights about their current customers that may be helpful or insightful for similar businesses.
The key phrase is “similar businesses.” One of the biggest issues with this type of analysis is representative sampling, the statistical concept that conclusions made about a group of people included in an analysis are broadly applicable. For most businesses, a sample of your customer data wouldn’t be widely applicable to all businesses. It may apply to similar businesses, though. The better that you can identify or disclose how your data applies to readers, the more useful they will find this. Here is a primer that is pretty straightforward.
In this post, we show three examples of businesses who have anonymized and aggregated their data to create useful, engaging, and unique content. Each is representative of a special case: a large business with representative data, a large business with localized data, and a smaller business with localized data. What I hope to demonstrate is that businesses can use this tactic for content creation agnostic of size or situation.
Kaiser Permanente is an interesting case study to include in a piece about content creation and marketing. The genesis of this piece was NPR Morning Edition’s discussion of how Kaiser Permanente and Geisinger Health System use electronic medical records to aggregate patient data to identify trends. Kaiser Permanente has been collecting and researching patient data since the 197o’s – some of their more notable publications are around the Women’s Health Initiative and identification of “toxic stress” contributing to health and education outcomes in adolescent patient populations. Kaiser aggregates and anonymizes their data, mines it for interesting insights, and publishes it for doctors, researchers, and patients. The benefits that they have relative to other content creators is that they often can draw conclusions about representative populations. In other words, there so many patients in Kaiser Permanente’s datasets that their conclusions (if the research is sound) often applicability to the general population. Not many businesses can do that with their data.
Kaiser aggregates and anonymizes their data, mines it for interesting insights, and publishes it for doctors, researchers, and patients. The benefits that they have relative to other content creators is that they often can draw conclusions about representative populations. In other words, there so many patients in Kaiser Permanente’s datasets that their conclusions (if the research is sound) often applies to the general population. Not many businesses can do that with their data.
NPR says that Kaiser also asks its patients to fill out additional 30-question questionnaires, which is a great example for content workers as well. If you ask additional questions, you remove the limit of only using the information that you have if your customers are willing to provide more. However, if you are going to make conclusions about data that you glean from the additional details, you may want to understand volunteer bias.
Every November or early December, you may read granular details about how retailers perform on Black Friday and Cyber Monday. The odds are that Adobe generated some of the source data for these articles and posts. Although the conclusions from these reports are sometimes generalized as representative of all retailers, Adobe’s source data comes from customers of their marketing cloud. Despite Adobe’s name recognition and scale, their information is specific to their clients and not to all businesses.
Adobe is straightforward about their customers being the source of their data and conclusions, and despite this, however, their customers may not be a broadly applicable group. So, the value of the Adobe data is for current or potential users of their marketing suite to glean insights about their business from the content that Adobe publishes.
What content marketers and creators should learn from Adobe’s example is that you don’t have to have a representative sampling of all businesses. Disclosing the population of people or businesses that the gleaned data is both ethical and helpful for readers to understand how your data may apply to them.
Vugo is an advertising platform used by rideshare drivers to make additional income when driving for Uber or Lyft. According to the most recently released numbers, less than a tenth of one percent of all rideshare drivers use Vugo. Vugo is an excellent idea, but few of the hundred of thousands of potential customers are aware of it. It’s a smart upstart company whose clients are unlikely to be representative of all rideshare drivers, presumably due to lack of awareness across customer demographics and geography.
For this small business to generate awareness (targeting rideshare drivers who are Vugo’s primary customers), Vugo came up with some statistics about their current clients, published their findings, and created an infographic to highlight key figures. Despite that their customers aren’t representative of all rideshare drivers, they were able to mine their customer data to create content pieces that may be of interest to their target customers.
Vugo is an example of a small company that can extract and share its customer information to create useful content. The data is (presumably) small, and it represents a small minority of rideshare drivers, but is still compelling to prospective and current clients.
Creating consistent, interest-generating content is challenging. Content marketers and communications professionals often rely on many different types of content to keep things interesting for clients and prospects. Although most companies don’t have the breadth of data that Kaiser Permanente uses to help improve health outcomes, by ethically disclosing the sensed population of your customer data you can create interesting and useful data-driven content for your publics.
(Image Credit: Pixabay)
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