by  Matt Kollmorgen

Driving Personalized Experiences Through Data

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Organizations undergoing digital transformations understand the importance of putting real people at the center of your experience. But people can be hard to completely understand. We have unique motivators, we can be irrational, and we verbalize our needs poorly—but we are the central component to any experience. Given that people are so difficult to understand, how are forward-thinking companies expected to give us the custom-tailored personalized experiences we demand? The secret to solving this mystery can be found in the data.

Common methods of customer data analysis include analyzing usage patterns like times spent on pages, areas clicked, items viewed, and items purchased, but analyzing these trends is really about trying to sell consumers more product. While knowing this data about a consumer can drive transactional value, it does very little to provide an ongoing value. Tailoring the experience for customers should be much more about providing long-term value and building a relationship, not about single-point transactions.

To drive a deeper understanding, marketers need to supplement the available customer data with additional sources. These would include information such as demographic and lifestyle data, location data, as well as historical data, such as purchase history and previous sites visited. Aligning a customer profile across multiple data sources begins to provide a more dimensional view of the customer. But we can do better. To deliver truly personalized experiences, companies need to go a step further and create consumer profiles that collect data from various touch points across all channels of the customer’s journey.

How? Brand leaders such as Starbucks, Disney, and Netflix are actively engaging in data exchange practices with their loyal customers, directly through their digital experiences and interfaces. And what is even more amazing about this is that consumers are freely and willingly supplying their data for the personalized custom-tailored experiences leading brands offer them in return. For most people, especially the millennial generation, the convenience of not having to wait in long lines, or knowing precisely when event tickets are going on sale, or even being made aware of exclusive happenings or content is well worth providing a little information about yourself. The convenience of saving time and energy in the long-term is enough for many to provide data such as their social media info, mobile phone number, and even payment vehicles, whether it’s a credit card or PayPal.

The Elusive 360-Degree View

Gaining insights from data is no small task. Despite collecting terabytes of data, many organizations are still struggling to understand how to leverage it to solve business problems. According to Marketing Tech, only 10% of marketers across the world have tied together customer data across channels, tools, and databases.

87% of marketers consider data their organization’s most underutilized asset.

Leveraging first-, second-, and third-party data is certainly valuable in helping to understand your consumer’s behavior. However, unless you are actively engaging customers to supply specific data about themselves, then you will never achieve the true 360-degree view that allows you to tailor their experiences. Putting people at the center of your experience means that your attempt to understand them shouldn’t be a one-time practice. People’s needs grow and change over time, and companies should seek to tailor products and services to be in line with these changes. By enabling the customer to be the focal point of the experience, with regards to both digital and physical touch-points, we can interact with them on an entirely new level. Learning how to harness this data can unlock secrets about your customers and enable you to serve up highly tailored and personalized experiences, whether engaging with them in a digital or physical scenario.

Netflix and Data

Netflix began its data journey while they were still shipping DVDs. They sponsored a $1 million prize to the team who could generate the best algorithm for recommending title users would enjoy. At that point they only had four data points to draw from: customer ID, movie ID, rating, and the date that the movie was watched. Though the actual data analysis was pretty rudimentary, the important takeaway is that it became a fundamental business practice, allowing Netflix to become a data-driven organization.

Once Netflix began streaming titles, the amount of data points vastly increased: the time of day movies are watched, the time spent selecting movies, and how often playback was interrupted by being paused or by network limitations. By combining these new measurable data elements with viewer ratings, Netflix started building models to predict the precise scenarios in which customers would enjoy certain titles.

“Happy customers are far more likely to continue their subscriptions” Peter Marr, Smart Data Collective

Today, Netflix’s Data Wizard says “we're close to a future where algorithms know almost everything we want” according to a recent Business Insider article. Netflix’s ultimate goal is to automatically play a video the user will enjoy the instant they open the Netflix app.

Data isn’t just about title recommendations at Netflix either; it is used across every aspect of the business. The success that Netflix saw in their first original series, House of Cards, may have seemed like the result of great storytelling and acting, but was actually a calculated formula based on data. Netflix found that titles featuring the lead, Kevin Spacey, were performing well; that the series’ director, David Fincher, had high scores for people watching his previous titles from beginning to end; and the series was actually based on a British series already on Netflix that had consistently performed well. With the right data and the knowledge of how to leverage it, Netflix was able to create a highly successful series that went on to win multiple Emmy and Golden Globe Awards. Netflix has said the combined effects of personalization and recommendation are worth more than a billion dollars every year.

Enabling Life-Saving Experiences

Another great example of data enabling positive outcomes is the work that Crisis Text Line is doing. Founded on the heels of, CEO Nancy Lublin noticed that people were occasionally texting back about things like being bullied, addiction, and abuse. One was so troublesome that Nancy knew she had to launch a text line for people in pain. (See Nancy Lublin Ted Talk for the full story.)

Crisis Text Line launched in August 2013 and, to date, has received over 33 million texts. They have 50,000 texters each month responded to by over 2,200 crisis counselors, and experience 10 active rescues every day. But in addition to saving lives, there’s a powerful side effect from all of these texters: the data.

Crisis Text Line is really a technology company first. Through the 33 million and growing texts, Crisis Text Line has created the largest mental health data set in the world. This data set is utilized at almost every touch point across the texters’ journey with Crisis Text Line. First, the data is used to categorize the crisis type and severity based on keywords in the text. Some key words will even trigger a “code orange” alert placing the texter at the top of the queue. Data is also used to guide crisis counselors with specific instructions and phrases that have been successful within that specific category of crisis. The data is also used to predict the need for counselor capacity and ensuring “spike teams” are available based on specific days and times, as well as other social factors and events Crisis Text Line has identified by analyzing trends.

“This data is making the world better, because I’m sitting on the world’s first map of real-time crises.” Nancy Lublin, CEO Crisis Text Line

The data that is collected can be viewed at http://www.crisistrend and is also made available to schools, pediatricians, and mental health workers.

Data to Enable Both Digital and Physical Experiences

Data is a key component in the process of understanding your customers. It complements the foundational Experience Design work that is also required, as well as critically important activities including: the development of archetypes and personas, the conducting of customer interviews and ethnographic research, understanding user context and moments of engagement, as well as doing early prototyping to solicit feedback and user validation. Data complements these processes to give a full picture of customers to respective businesses.

Whether you’re looking to determine what products to recommend to someone on your ecommerce site, which products to stock on your shelves, what content to put in front of someone, or even how to talk to your customers, the secret to enabling a valuable experience can be found in the data.

To learn more about how data affects your business, read Matt Kollmorgan’s recent whitepaper, “Transforming Media Experiences with Modern Platforms.”

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