The old saying goes that a vision without a strategy is just a dream. That pretty well sums up the hype surrounding data-driven marketing for years.
Co-authored by Sarah McConville
Back during the earliest days of the web, it seemed as if publishers would be able to transform their businesses using the magic of cookies. But the gold proved elusive. All these years later, we are beginning to see results that are finally impacting editorial programming, marketing, and product development in a significant way.
We were recently asked to give a keynote address to describe some of the early success that Harvard Business Review has had with customer data and analytics. The positive response to the talk prompted us to want to share some of what we are learning more widely in the hopes that we'd hear from others who might want to share their lessons learned as well.
So please feel free email us directly (you can find our addresses in our bios at the bottom of the page).
Harvard Business Review makes for a solid case study on this front for a couple of reasons. For one thing, we are squarely focused on paying subscribers, unlike other publishers that make their money primarily from advertising. We're also creating a range of products, such as books, e-tools, and editorial collections under one brand and marketing them directly to the consumer. This allows us to capture a rich range of audience demographics, buying patterns, as well as web behaviours that other publishers might not get.
Theory of the case
Our understanding of the consumer comes from a number of sources.
The data alone from our website does not give us the complete story about why people like, love, or hate Harvard Business Review or HBR.org. Here's an idea of some of our other sources of customer insights:
- Speaking with our customers at live events
- Conducting user-tests and focus groups
- Analyzing buying patterns
- Surveying our 10,000 member HBR Advisory Group
- Launching lean versions of new products and getting feedback
- Polling our social media community
The responses from these various sources are then interwoven with what we learn from our data and analytics. The ultimate business objective for us is to reduce the costs of customer acquisition while improving retention rates by creating a much deeper relationship with our customers. We want customers to have a deep sense that we know what they need from HBR. Our belief is that a more efficient marketing engine allows us to allocate more dollars towards improving upon the subscription offer, which then produces greater engagement and in turn better data for us to deepen the relationship with our customers. Like any strategy, this is just a theory, but we're beginning to validate our hunches.
Segmentation, conjoint, and lean product development
Some years back we began working on segmenting our audience, focusing on top leaders and those who aspire to significant leadership positions.
It was clear enough that fresh and powerful management ideas backed by solid research lie at the heart of our value. But there also seemed to be a yearning for tools to put these ideas into practice. Here's where things became a bit trickier. The question was, What kind of tools? Did people want spreadsheets? Interactive videos? Or what?
This is where the conjoint analysis comes into play. Through this analysis we could test a number of different offerings to begin to get a sense of the elements that might increase willingness to pay.
The conjoint, which consists of around 2,500 subscribers and past customers, showed us that along with content in the magazine, HBR.org, and our mobile site, HBR readers would also value an enhanced subscription that included simple customizable tools in familiar formats (spreadsheets, checklists, etc.), downloadable elements to help them express key takeaways from articles (a Visual Library of HBR infographics and articles translated to power point), as well as personal areas on HBR.org to manage content and easily find what they've read (custom folders, reading lists, save and share functionality).
Then we began to create lean prototypes of these ideas - the essentials for what the customer might want. We were following a path of viable, desirable, feasible development--meaning, we looked at ideas that were economically viable, desirable to the consumer, and technologically feasible.
The Visual Library is a good example of something that seemed to meet the needs of the audience and passed the viable, desirable, feasible test. The Visual Library (pictured above) is essentially an online searchable catalog of more than 100 of our most popular images that you can download for your own use in your company. And we're adding to it every month going forward.
Proving the theory
The early results show real potential. On day one of its launch, the Visual Library was among the highest trafficked page on HBR.org after the homepage and it doubled subscriber registration levels indicating how eager our subscribers were to access this content.
But this example is just part of a process. The goal is to continue to design and develop new elements that continue to work for our subscribers. It will take us time to get this cycle down pat, but we're on our way.
We hope to hear your stories and look forward to learning more together - and maybe we can make the dream of data driven marketing a reality for all of us.
Josh Macht is executive VP and group publisher of Harvard Business Review
Sarah McConville is VP of marketing for Harvard Business Review and publisher of Harvard Business Review Press