Data-driven Marketing Spells the End of One-Size-Fits-All
Delivering personalized experiences to customers is a top priority of marketers. In fact, a recent study by PWC’s Digital Services Group revealed that 94% of senior-level executives believe delivering personalization is critical to reaching customers. The emergence of digital has presented organizations with more challenges and opportunities than ever before and businesses today understand that personalization drives results.
An important shift
The shift to personalized experiences alters the relationship between businesses and consumers. A consumer buying a smart connected product is no longer taking the final step in the purchase process, but is instead taking the first step in building a relationship with a business. Take something as simple as a watch: 10 or 15 years ago, an individual looking to purchase a new watch would have done some research and then bought one of the products available at the time in the market.
Today, if you buy a smart watch, such as the Apple Watch or the Samsung Gear, you are buying a lot more than a wristwatch whose primarily functionality is timekeeping. Smart watches today are essentially wearable computers. Many run apps using mobile operating systems, letting users search the Internet with their voices, track their exercise progress via GPS, or even checkout at the grocery store without a wallet. These are individually tailored, personalized experiences that transform the relationship between a product and a person, from consumption to participation.
Data is the foundation of personalization
Let’s now take a closer look at data-driven personalization. In order to tailor marketing efforts, businesses will need to capitalize on big data. Collecting it is no longer a challenge. Every day, we create 2.5 quintillion bytes of data. The real issue is using this data to deliver contextual, personalized messages. According to McKinsey, organizations that put data-driven personalization at the center of their marketing and sales decisions improve the return on marketing investments by a minimum of 15%.
Personalization adds value to a business by allowing it to reach different consumers with different creative messages, rather than creating a single, one-size-fits-all message that might not resonate with everyone the same way. It lets marketers intelligently tailor advertisements based on consumer demographics, interests, or location, and reach millions of different consumers with information that is individually relevant and interesting.
A good example is Spotify; the app personalizes ads based on consumers’ interests and demographic data. If somebody listens to a “workout” playlist, Spotify might then deliver ads for running shoes or athletic apparel. Another good example of a business that employs this well is Amazon. Their personalized product recommendations are a core component of their consumer experience. They’ve brilliantly leveraged similar product models to present buyers with, like ‘people who bought X product also bought Y product’ or ‘since you bought Y, you might also like Z’. Personalized product recommendations align the right product to the right customer at the right time.
Attribute and event sequence analysis
There are two different computational techniques to achieve this kind of hyper-targeted personalization:
- Attribute analysis breaks down customers into a map detailing a person’s attributes. These attributes determine for instance whether a person is a male or female, how old they are, what city they live in, whether they are employed or unemployed, their marital status, whether they have children, what apps they use the most on their mobiles (think Uber vs. Careem to determine preference) and so on. This kind of analysis has become very easy with the advent of social media platforms such as Facebook, Twitter and Instagram. The data collected is very useful because it enables businesses to create better marketing content and tailored suggestions. For example, if someone describes himself or herself as an avid gamer, businesses can use this to suggest new games and consoles to them.
- The second technique used for hypertargeted personalization is the event sequence analysis. It observes the sequence of events through which people go when they purchase a product or a service. It considers how a consumer logs into a given website (with a username, an email address, through Facebook, etc.), the search terms they’ve used, items that they’ve added to their shopping cart and so on. This data is then stored and used to analyze the decision-making process before a purchase is made. This is called a sequence of events and can be used to create targeted and personalized messages to consumers.
Marketers are learning new ways to leverage the vast amount of consumer information available to them. The above data analysis techniques can be combined with other digital data tools to come up with the right mix of elements and deliver the personalized content today’s consumers demand. However, even with such tools, marketing executives still need to coordinate the necessary internal and external resources to support their data analysis efforts.
Data and analytics are essential tools for the success of hypertargeted marketing efforts and mass personalization. But even the most powerful tools don’t work very well in isolation. Senior management commitment and cross-functional involvement across all channels are equally important for the success of all data analysis efforts. Marketing executives need to be able to support the tech platforms and continuously update consumer data and the advanced analytics models that fuel the decision-making engine.