There’s No “Magic Pill” When it Comes to Data
Three questions publishers should ask before embarking on a data strategy
Like just about every type of business today, publishers want to be able to take advantage of robust data and advanced technology to make better decisions, validate product offerings and drive more revenue.
It’s a worthy objective, to be sure, but there’s no “magic pill” that will immediately transform raw data into value. Just as losing weight demands a lasting commitment to healthy eating and exercise, becoming a data-driven organization requires careful planning, strong in-house talent and the right technology partners. Expecting results overnight is unrealistic.
Here are three questions publishers need to ask themselves before embarking on a data optimization strategy, with a focus on long-term gain rather short-term fantasies:
What kind of publisher are you? Your data strategy, first and foremost, depends on your overall business strategy. And the definition of “publisher” can be quite broad. Data analytics requirements—both from a resources and technology perspective—will be different depending on whether you are a news and entertainment site, a commerce site, a niche research site, a website supporting a primarily brick-and-mortar business, or a portal.
What are your core and non-core sources of revenue? Advertising sales? Product and service sales? Subscriptions? You may even drive revenue from the sale of data. These questions are key to determining the best data analytics strategy and technology solutions to deploy. For example, if data analytics and research on your traffic supports your core business model, you might require more advanced tech and a DMP that supports third-party and offline data. Lower feature-set DMPs and sell-side DSP technology may be a better choice for strategies focused on monetization of users or advertising only.
What are the risks and the rewards? Consideration must be given to how a data initiative will impact the overall business both from a revenue perspective and from user experience perspective. For example, it might not make sense for a $60 billion commerce site to sell user data for only a few million in incremental revenue. Privacy and data security are also a growing concern for consumers, so it’s important to assess how the use of audience and customer data will be perceived and how sensitive data will be protected.