Definition of Data-Driven Marketing Data-driven marketing is the process by which marketers glean insights and trends by analyzing company-generated or market data, then translating these insights into actionable decisions informed by the numbers. The goal of data-driven marketing is to optimize marketing processes and strategies to cater to changing trends and the unique demands of audiences and consumers by leveraging data to gain deeper insight into what customers want. When brands fully understand the who, what, where, when and why of how consumers are engaging with their marketing efforts, they are able to make better decisions surrounding everything from the timing of advertising in a given medium to the customization of marketing copy to cater to specific audience segments. How Data-Driven Marketing Works The process of data-driven marketing relies on the use of information (in the form of data) in order to drive marketing efforts. Data is collected on every aspect of a user’s engagement from demographics to market-wide metrics and individual interactions, and is then analyzed in order to determine markers of success. These insights are then used to help decide where and how to focus marketing resources, the types of creative that are most effective at maximizing ROI, which customers are most likely to churn, and many other crucial details that can aid marketers in shaping brand growth. Data-driven marketing is gaining in popularity in large part due to its proven ability to maximize ROI. It also helps to maximize the efficiency of marketing efforts by reducing wasteful spend and improving resource allocation, and ultimately empowers brands to deliver a more customer-centric approach to marketing. Gaining a better understanding of a brand’s prospects and their preferences is one of the most effective methods for increasing conversion rates. Examples of Data-Driven Marketing There are thousands of examples of data-driven marketing in use every day if you know where to look. In fact, the majority of the marketing messages we’re exposed to on any given day are driven by data-derived insights. Data-driven marketing has become the new norm thanks to the widespread accessibility of data and analytics tools. One company that has used data-driven marketing to its advantage is Hootsuite. When they noticed both free and paid signups were dropping off, they looked deep into their data pool to determine the features different segments of their user base were relying on most. They then utilized this data to create different usage tiers for the service based on what their customers were actually using the product for. The result? An increase in both free and paid service signups. Another example of successful data-driven marketing in action is Status Page. This company used data to increase conversion rates by 311%. After identifying which stage in the process prospects were being lost, and why, they implemented site changes to make the signup process more appealing and saw tremendous success as a result. Of course, these are just two of the many examples of businesses successfully leveraging data-driven marketing to influence results. Benefits of Data-Driven Marketing Data-driven marketing offers widespread benefits, including not only effectiveness but also ease of implementation thanks to the availability of user-friendly tools that do much of the heavy analytics lifting. Many marketers turn to data-driven marketing to improve audience targeting. With the right data, brands can know exactly who is engaging with their marketing efforts through which channels, and even at what time of day they are active. This can aid brands in laser-focusing their marketing efforts to the right mediums at the most effective times. Data-driven marketing also allows marketers to analyze the types of messaging and offers that consumers are most responsive to, often analyzed through A/B testing. This lets marketers focus their efforts into projects that will offer superior ROI and are of the highest value to the consumer. Conversely, it also allows marketing teams to see where they may be going wrong and how to correct the issue — as with the above example from Status Page. Data-driven marketing can also be used to optimize customer experience. If a marketer sees a bounce rate at a certain point of their campaign, they can evaluate the why and adjust as necessary so that the customer experience is optimized. This is the kind of initiative that has a powerful impact on growth and retention. Challenges of Data-Driven Marketing One of the biggest cons of data-driven marketing is also its biggest advantage — the intense focus on using insights in the decision-making process. This hyperfocus on using data to make marketing decisions can come at the expense of creativity, depending on how marketers choose to leverage data-derived insights. When metrics tunnel vision takes over, creativity is no longer driving the message and the ‘magic’ of connecting with consumers no longer happens. Savvy marketers implement the right blend of creativity and numbers-driven factors into every marketing campaign and tactic. Additionally, data can also indicate a course of action that goes against a brand’s values. While this is rare, marketers should maintain a sense of brand integrity and use data to inform, but not dictate, decision-making when it comes to sacrificing values. Brand guidelines are helpful to ensure that brand identity standards and values are maintained. Best Practices for Data-Driven Marketing The key to obtaining success with data-driven marketing efforts is to plan, test, analyze, iterate, and then redeploy and scale accordingly once you’ve gleaned enough insights to inform your course of action. Decide what you’re measuring and how you’ll be successful. Utilize A/B testing and other measures in order to see what works best and then compare results to your original KPIs. Then, implement and invest accordingly, taking care to analyze new data and adjusting your marketing efforts continuously. Data drives the majority of marketing decisions in today’s highly competitive world. If you’re not yet using data to derive marketing insights and inform decision-making, you’re already behind the curve.
CUSTOMER EXPERIENCE MANAGEMENT
A Definition of Customer Experience Management Customer experience management (CEM) describes how a company takes control of its interactions with customers. Gartner offers a spot-on CEM definition: “the practice of designing and reacting to customer interactions to meet or exceed customer expectations and, thus, increase customer satisfaction, loyalty and advocacy.” Organizations’ departments and groups often plan customer interactions from their own perspectives, or silos, rather than from a customer’s perspective. CEM is the concept of viewing and improving those interactions entirely from the customers’ perspective, and true CEM encompasses the customers’ entire journey with a business. The goal of customer experience management is to build customer loyalty and to reduce customer churn. Benefits of Customer Experience Management As businesses find themselves trying to remain competitive in today’s ultra-competitive and connected world, customer experience management has become critical to their success. In fact, customer experience management is incredibly valuable to companies of nearly any size because of the benefits of CEM, as outlined by SAS: Strengthen brand preference through differentiated experiences Increase revenue with incremental sales from existing customers and new sales by word of mouth Improve customer loyalty, and create brand advocates, through valued and memorable customer interactions Reduce customer churn to lower costs Methods of Customer Experience Management There are several methods of customer experience management, but most companies approach it using the same basic CEM model. First, companies get feedback from their customers to get a fundamental understanding of their experience. Companies may capture feedback through surveys and customer satisfaction polls and outreach. After companies have gathered feedback from customers, they share the insights across the organization. It is most helpful if the insights are shared in a timely fashion and in the most relevant way for each department. It’s critical that the right people get the right customer insights at the right time. Finally, companies need to ensure they are delivering the optimal customer experience based on that feedback. Companies must continually evaluate their customer experience in order to improve upon it. Challenges of Customer Experience Management Of course, designing a successful CEM strategy can be a daunting task. Businesses must know their customers, and know them well, in order to get customer experience management right. One of the toughest challenges is creating a consistent multi-channel brand experience. Don’t forget that customers are interacting with your brand online, through customer service, in person, and more. It is crucial that you ensure brand consistency at every point of interaction. Another challenge of customer experience management is getting a single view of the customer. Companies get customer data from a multitude of sources, and the trick is to consolidate all of that data into a single view to gain a 360-degree view of the customer. This becomes especially difficult if the data remains siloed. Another challenge of customer experience management is personalization. Customers have expectations and are aware that companies have more information about them today than ever before. That translates to customer demand for personalization, and businesses must remember to personalize every interaction. Businesses can succeed at personalization if they add context to their customer focus so they can offer what the customer wants, when the customer wants it. Customer Experience Management Systems Companies do not need to handle their customer experience management all on their own. Customer experience management systems are software solutions that help to improve time-to-market by delivering more personalized experiences to customers. Leading customer experience management solutions connect data sources in real time so that companies are better equipped to engage customers through personalized experiences, which leads to greater customer lifetime value. The key to customer experience management is getting a single view of customers by breaking down silos and getting the deep customer insights that help businesses create more personalized customer interactions.