A PRACTICAL GUIDE TO MODERN MARKETING ANALYTICS How marketing analytics becomes the next competitive weapon in building stronger customer relationships
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Table of Contents THE BIG DATA OPPORTUNITY FOR MARKETERS... 4 WHY YESTERDAY S ANALYTICS SYSTEMS WON T CUT IT... 5 ANATOMY OF A MODERN MARKETING ANALYTICS SOLUTION... 7 4 REQUIREMENTS OF A MODERN MARKETING ANALYTICS PLATFORM... 8 THE STRONGVIEW APPROACH... 9 ABOUT STRONGVIEW... 9
THE BIG DATA OPPORTUNITY FOR MARKETERS "Big data" is being hailed far and wide as a transformative technology trend that is changing the way companies do business and its implications for marketers are just as farreaching. The promise of big data for marketers is that it can propel them into a position where they can truly understand individual customer context and begin leveraging that insight to engage in highly targeted and relevant communications. If they can channel the flood of raw customer data into actionable insights, marketers can unlock the secret to more relevant and meaningful customer interactions, and in turn higher customer lifetime value. In other words, they ll have the means to achieve long-term competitive advantage and increased profitability. The promise of big data for marketers is that it can help them understand individual customer context. So, how is marketing going to get there? Below are just some of the ways in which big data analytics enable a deeper and timelier understanding of the customer. Deep Customer Insight: Determine the present needs, preferences and desires of the customer and understand his or her current lifecycle state to deliver contextually relevant experiences. Finer Customer Segments: Segment customers into closely defined clusters and then target these clusters with greater precision to achieve higher response rates. Higher Customer Retention: Discover the drivers of customer affinity and response, and leverage them to retain profitable customers and reduce attrition. These insights can be used by marketers to identify the preferences and interests of a customer in real-time to deliver personalized content that reaches the customer at their point of need or want. But what s new about that? How is big data new? In fact, what does big data really mean? The prevailing definition of big data is the convergence of data from many sources that overwhelms business and technical users through its volume, velocity and variety the three Vs. And it is precisely the volume, velocity and variety of the digital customer data that marketers now have access to that makes big data such a game changer. Collecting, analyzing and acting upon customer profile and transaction information is nothing new for marketers. After all, organizations have long been investing millions of dollars to build enterprise data warehouses and implement CRM and marketing automation systems to store and analyze customer data. However, the three Vs of big data are exposing the shortcomings of the traditional marketing platforms used by most marketers today. 4 A Practical Guide to Modern Marketing Analytics
Interaction Data is Key Driver of Big Data Volume The rise of accessible interaction data is largely contributing to the increasing size of data available to marketers for analysis. Customer interaction data includes: Shopping/Web Behavior Channel Engagement Device OS Activity Location Time Customer Lifecycle WHY YESTERDAY S ANALYTICS SYSTEMS WON T CUT IT The reason why traditional marketing platforms are struggling with big data comes down to how they were originally designed. Data warehouses and CRM systems have traditionally been built to manage a limited set of demographic and transactional data, including customer information such as gender, age, marital status, home ownership and purchase history (limited variety). These attributes are either static or change very slowly (low velocity), which has led to relatively low volume. As a result, the customer profile that emerges from these data management systems is also inherently static. The customer interaction data that is available to marketers today, however, is just the opposite. We re talking about the steady stream of digital interaction data footprints that online customers now leave in their wake data about what customers clicked on, searched for, watched, Liked on Facebook, browsed or purchased, tweeted or commented on, and even their location, IP address and where they went via geo-location apps. The volume of data is immense, it changes constantly, and it contains a massive variety of structured, unstructured and semi-structured data types. Traditional data warehouses and marketing analytic systems have been designed to capture particular types of customer attributes defined at a certain point in time. Because of this, analytic applications that rely on this data become outdated as soon as there is a change in the way a company does business that necessitates a change in the type of customer information they need to collect. Current systems also don t allow for the third V of big data variety. In the era of big data, it s practically impossible to anticipate all of the attributes by which a marketer might need to analyze his or her customer information. As a marketer, you don t want to be stuck where you can t analyze customer data based on a new attribute or define a new segment on the fly because the underlying data model doesn t support it. Simply put, these traditional systems and their static data models weren t built to handle digital customer interaction data at the volume, velocity or variety that exists today. And they weren t built for marketers. Today, most marketing analytic systems depend on IT personnel at every step of the process. It seems inconceivable that a marketing manager would have to write a SQL query in order to perform a simple customer segmentation, yet this is exactly what many of these systems require. The 3 Vs of Big Data Volume The sheer amount of data to be analyzed Velocity The rate at which various types of data are changing Variety The different types of data available for analysis 5 A Practical Guide to Modern Marketing Analytics
Further complicating matters, the size and frequency of incoming data is expected to increase exponentially, which will only exacerbate the existing shortcomings of traditional systems and contribute to increased latency of marketing decision making. The IT personnel that marketers currently depend on to provide the required data and analysis for marketing engagements will be routinely overwhelmed with the sheer volume and velocity of incoming customer information not to mention the immense variety, which these systems don t even support. As shown in the diagram below, the static data model of today's systems forces marketers to rely on IT each time they need to uncover new customer insights. The latency introduced by this never-ending loop significantly inhibits a marketer's ability to leverage the data effectively in today's competitive environment. Caught in the Static Model Update Loop MARKETING DEPARTMENT 1-2 Weeks Marketing Engagements Daily Build New Reports & Dashboards New Business Realities 3-5 Weeks Daily IT Data Modeling Update Daily New Attributes to Analyze IT DEPARTMENT Average Time Elapsed: 7+ weeks In traditional analytics systems, marketers are dependent on IT staff to extract insights from customer data and update data attributes. 6 A Practical Guide to Modern Marketing Analytics
If traditional data warehouses and CRM systems can t provide the real-time customer insights needed to stay competitive in today s constantly changing marketplace, what can? ANATOMY OF A MODERN MARKETING ANALYTICS SOLUTION Marketers need a data storage system that allows them to load and access interaction and profile data whenever they need to. This storage system also needs to be able to expand at a moment s notice without requiring long IT lead times to provision additional servers and hard drives. This may sound like the stuff of fantasy, but this is what the era of big data demands an elastic data warehouse that is owned and operated by marketers. In addition, marketers need an analytics platform for this elastic data warehouse that allows them to perform reporting, dash boarding and ad-hoc advanced analysis all without assistance from IT or a data scientist. A modern big data analytics platform must lift the burden of data analysis from the shoulders of IT and place this power into the hands of marketers in a self-service environment. As shown below, removing IT from the data modeling equation allows marketers to perform new analyses and gain valuable new insights in a matter of days instead of weeks. Respond Rapidly to Changing Analytics Needs MARKETING DEPARTMENT Marketing Engagements 1-3 Days Daily Self-Serve Analytics New Business Realities Daily Average Time Elapsed: 3 Days In a big data-era marketing analytics system, marketers can manage and analyze large volumes of customer data to derive real-time insights to meet business needs without help from IT. 7 A Practical Guide to Modern Marketing Analytics
4 REQUIREMENTS OF A MODERN MARKETING ANALYTICS PLATFORM When selecting a modern marketing analytics platform, there are four key features that you need to look for to ensure that it can effectively make sense of big data and make it actionable in your cross-channel campaigns. 1. Integrated. Marketers must be able to integrate in real-time with all relevant customer data systems and external streams. 2. Intuitive. Marketers must be able to easily gain insights from all internal and external customer data, as well as perform new analyses on the fly without IT involvement. 3. Elastic. Marketers must be able to store and access an unlimited amount of profile and interaction data in an elastic cloud-based data warehouse than can scale on-demand. 4. Performance. Marketers must have solutions that scale to store and analyze massive amounts of information while maintaining a high level of system performance. The attributes of the modern marketing analytics platform described above differ significantly from traditional systems. We've broken down those differences in the chart below. Traditional Analytic Systems Modern Marketing Analytic Platforms Primary User Business Analyst Marketing Manager/LOB Data Type Static (Demographic & Purchase History) Dynamic & Static (Customer Interaction and Profile Data) Data Ingestion Batch Mode On-Demand Data Retention 7-10 Years Unlimited Data Analysis IT-Dependent Self-Service Ownership IT Marketing Data Model Pre-Modeled Attributes Flexible & Customizable Attributes If your current marketing analytics platform maps to the limitations of traditional systems listed in the first column, you should consider planning for the future and find a modern solution that allows you to embrace the marketing opportunities presented by big data. For more information on choosing the right technology solution, be sure to check our companion Success Guide, "The Future of Marketing Analytics Technology." 8 A Practical Guide to Modern Marketing Analytics
THE STRONGVIEW APPROACH StrongView enables marketers to embrace the new big data reality with InteractionStore, the world's first web-scale customer insight solution for analyzing and acting upon unlimited, cross-channel customer interaction data. Fully integrated with StrongView's cross-channel campaign management solution Message Studio, InteractionStore offers unlimited storage of customer interaction data while maintaining high levels of performance and system response. These capabilities empower marketers with faster time-to-insight for more relevant and precise targeting and personalization. InteractionStore provides marketers a critical capability for becoming a Present Tense Marketer. Present Tense Marketers understand customer context at all points in time and use this deep understanding to deliver better marketing and build stronger customer relationships. InteractionStore leverages state-of-the-art cloud technologies to address the challenges of big data, making it easy for marketers to understand and act on unlimited amounts of data across multiple channels. InteractionStore provides insight when you want it, action when you need it. Learn more about InteractionStore and Present Tense Marketing at: www.strongview.com/products/data ABOUT STRONGVIEW StrongView's cross-channel marketing solutions provide enterprise marketers with the tools, services and insights required to effectively engage today's constantly connected customers. Combining a powerful cross-channel campaign management solution with market-leading data access and analysis, StrongView's Marketing Cloud enables marketers to understand the current context of each customer and respond in real time with relevant messages across email, mobile, social, display and web. A champion of "Present Tense Marketing," StrongView is committed to delivering solutions that reflect the new reality of the technology-empowered customer. Based in Redwood City, CA and backed by leading venture capital investors, StrongView has been helping global brands in retail, travel, finance, entertainment and online services overcome the limitations of other marketing platform providers for more than a decade. For a stronger view of marketing go to www.strongview.com, and follow us at www.twitter.com/strongview and www.facebook.com/strongviewinc. StrongView Toll free U.S. +1 (800) 971-0380 Toll U.S. +1 (650) 421-4255 Toll U.K. +44 (0) 118 903 6068 info@strongview.com 9 A Practical Guide to Modern Marketing Analytics