True Data-Driven Decision Making Requires Smart, Honest Data Collection Strategies

May 21, 2014
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ImageData-driven decision making is getting a lot of recent press. As big data platforms gain more and more notoriety, the prospect to strategize based on predictive algorithms or even just increased customer intelligence is becoming a reality. 

ImageData-driven decision making is getting a lot of recent press. As big data platforms gain more and more notoriety, the prospect to strategize based on predictive algorithms or even just increased customer intelligence is becoming a reality. 

Champions of business strategy long for the days in which emotional attachments so common amongst passionate employees or founders will be those of a bygone era. In its place, actual success metrics would drive decisions that ultimately lead to increased ROI. Less emotion, less pride, if you will, and businesses can thrive based on the numbers. And today, this isn’t a point of contention — at least not among those who are paying close attention to the business space. 

After all, The New York Times hired a data scientist not to improve their data journalism, but to create predictive algorithms that will increase their customer subscription and retention rates. AirBnb, as well, used data science to grow the once startup’s valuation to $10 billion. And Facebook stands to be the leader in the data brokerage game, given that the social media company owns more user identity data than any other company on the planet. 

Yes, the business pendulum is finally swinging in the direction of data-driven decision making, and it’s a good change of pace for us all. With it will come the rise of truly unique digital experiences, the death of annoying or irrelevant digital ads and the creation of an Internet of Things, in which much of what we interact with, interacts right back. In essence, the Internet is becoming a living, breathing, albeit extremely personified, entity. In fact, it knows more about you than you may know even about yourself. 

And this is where data rights come in to play. See, data-driven decision making is impossible without data. That may seem like an obvious statement, but data collection is no winner take all game. It is as nuanced as it is necessary for a true data revolution to take place — and doing it the right way is the only way to protect your privacy, your brand and, ultimately, your overall success. 

The goal, here, is to democratize data, making it useful for all who encounter it — whether that be for companies to increase revenue or for end-users who benefit from a customized digital experience that makes both their online and offline lives that much more convenient, relevant and enjoyable. 

Given that Facebook does house the world’s most dense user identity data, and that this data will be useful to all companies, across every single industry from healthcare to publishing and sports to travel, data collection best practices must start here. Whether your site is using social login or not, though to turn your users into subscribers it should be, the collection of your first-party identity data is crucial. But, you don’t need to know absolutely everything about your audience in order to make smart, effective data-driven decisions for your company. In fact, allowing your users to maintain an amount of privacy is key, as is your data usage transparency — both issues extensively covered by the White House’s 2014 data report

In general, B.E.L.L. permissions are an industry best practice. With these, you are asking your users for birth date, email address, likes and location. All Facebook logins automatically access public profile information, most often including name, gender and profile picture (though users have ultimate say on what is or is not public information for their own profile). 

Birthday

With a user’s birthday, you will be able to look at and segment your audience across age groups for digital customization, relevant sponsorship and customer relationship management purposes. 

Email Address

Collecting a user’s email address gives you the ability to communicate directly with that user. You can segment the audience based on any facet (e.g. bikers, people who live in LA, are male) and directly download the corresponding email addresses to send out a newsletter or promotion.

Likes

When collecting a user’s likes, you begin to understand the interests, brand affinities and activities your audience prefers. With this information, you can easily segment your audience based on what brand of coffee they prefer, for example. How powerful is this? Immensely. After all, it gives your company the power of an agency — allowing you to reach out to relevant advertisers, partners and sponsors with higher rates and proof of interest.

Location

With location data, you can view and segment your audience based on very accurate, self-reported and detailed geographic data. Data platforms like Umbel will sort and map your user’s location on multiple facets, including MSA‘s and international views, making it more reliable than GeoIP lookups or traditional zip code-based methods.

In all, think of your first-party Facebook data collection as a tiered login. Beginning with anonymous login, companies can decide to add or ask for data point permissions as needed. If you are going to ask for permissions, though, they should be first and foremost relevant to the user experience. B.E.L.L. provides the most useful set of permissions to help with overarching content or business strategy and delivery while at the same time providing the least amount of friction to the user, with the least amount of drop off in logins. 

Data collection best practices remain an important, if not vital part, of your data-driven decision making policies. Without maintaining user trust via collection transparency and security, even the most resilient data-driven decision making strategy will fall short.