Location Intelligence applied to Communication Service Providers

Transcription

1 Location Intelligence applied to Communication Service Providers Improving Business Decisions with the Where Factor EXECUTIVE SUMMARY Location Intelligence (LI) solutions have been turning the heads of decision makers in the Communications Services segments recently, reflecting the positive momentum coming from other industries. About provides innovative Location Analytics software solutions to solve complex location-dependent business problems. software connects directly to enterprise applications, maps large-scale datasets and applies spatial processing to enhance data visualization, reporting and predictive analytics. Why has LI gained so much attention? LI, done right, can produce almost immediate impact on the bottom line. For example, a Communications Services Provider might use LI to: Get both a bird's eye view of their network infrastructures-fiber routing, embedded copper, poles, rights of way, easements, central offices, service control points, towers, backhaul locations -as well as insight into their operations underground or on the street, poles or towers. Address repair and field service problems from a spatial perspective such as optimizing the driving route of their service trucks to reduce time on the road, prioritizing critical jobs based on POP density and SLA s and arming themselves with the detailed history of infrastructure to speed repairs. Contact Us Improve marketing efforts by uncovering hidden relationships such as pinpointing competitive threats in retail channel and uncovering pockets of potential subscribers where expanded marketing effort via low cost channels could deliver more visitors to enhanced retail store experiences and upsell opportunities. 1

2 More and more, companies across multiple industry segments are deploying LI solutions to better leverage their investments in Business Intelligence solutions and their GIS (mapping) applications. These companies are seeing demonstrable improvements in operational metrics, customer growth and revenues. In a recent TechTarget/Esri 2012 survey, just over three-quarters of respondents said executives in their organizations feel it s somewhat or very important to use maps to view business data such as store locations, distribution networks, sales territories, revenue by region and competitor locations. Another benchmark research study from Ventana Research found strong interest in LI; more than three-fifths (61%) of participants said LI is very important in helping to improve business processes and performance, and even more (65%) said it is very important for improving interactions with their customers and suppliers. One of our own customers revealed that they have already achieved over a 7% improvement in sales attributed to improvements in sale and market coverage enabled by LI and continue to expect a positive ROI after implementing Phase 2 of their LI solution. Organizations have been investing in some sort of customer analysis solutions for years, mostly focused on analytics of some type or enterprise level business intelligence (BI). While companies have used analytics and BI to drive real-time marketing, sales optimization, broad-based decision making around supply chain, or even risk and compliance, some critical decision value was lacking. Today s executives and operational managers need intuitive applications that do more than traditional BI or real-time solutions. Location Intelligence solutions allows decision makers to collect, analyze, and model large and wide ranging sets of data, offering them faster, more accurate, more predictive, insightful, and relevant analysis, leading to better, more-informed decisions, faster. Organizations across all industries, and in particular the Communications Services industry, will benefit from expand their BI and Analytics toolsets to incorporate LI for decision modeling, combination of structured and unstructured data to include the where factor, to create an on-demand analysis tool that supports business operations and executive decision making. Improve Business Decisions with the Where Factor The Communications Services industry continues to undergo rapid change driven by technologies (4G, FTTH, OTT Video), product commoditization, device subsidization and rapid replacement cycles, bundled packages that can t sustain loyalty behaviors and tenure and more. The one sustaining constant is the importance of the customer. The good news is that most if not all Communications service providers no longer merely pay lip service to such a commonly expressed belief. In fact most are working harder every month to truly understand their customers. These companies know they must not only deliver targeted and personalized services and products, but also use better tools to identify customers, opportunities and bottlenecks as a way to improve their competitive position in the marketplace. 2

3 In order to address these business priorities, organizations will need to go beyond business intelligence (BI) and customer relationship management (CRM) and implement a new generation of solutions: on-demand customer intelligence (LI). Focusing on customers and technology solutions to serve them better is not new, but customer information still is not being leveraged to its full potential. Why? True LI solutions, and the benefits they offer to organizations and customers, remain elusive due to incomplete solutions or inadequate technology, lack of improvement in key operational and analytical and business leadership in adopting emerging best practices. While the Communications Services industry has made major strides in improving the customer s experience there remains ample opportunity to achieve better outcomes and outsized benefits. These service providers face challenges similar to other consumer and prosumer-oriented businesses. They have huge volumes of data to be mined, monitored, analyzed and reported on a regular basis. Many Service Providers are still forced to work with siloed solutions in an effort to develop real intelligence and learning for customer acquisition and retention. They struggle to effectively use customer information because customers now interact with their service providers through many channels: retail locations, kiosks, dealers, call Center, Web and Social Media, etc. Capturing, structuring, consolidating and analyzing data within channel operations is usually not overly difficult. But, just analyzing and responding to select data tied to a specific channel limits the decision analysis and recommended outcomes to segments of the customer base or select channels. More challenging is the fact that companies are hard-pressed to leverage the data for longitudinal tracking truly understanding customers by collecting and comparing their specific attributes, attitudes, and preferences about products and services, demographic data, purchase patterns and self perceptions and to compare how individuals fit into larger customer groups. When you add to this the general lack of understanding of where things happen one can better understand the limits even the leading service providers face in aligning their business strategy and operations to achieve improved customer experiences and loyalty. TDWI research produced in 2012 on Customer Analytics, including Location Analytics identified business functions or operations for which respondents considered analytics most important were marketing (81%, with 52% indicating very important ), sales and sales reporting (79%, with 45% very important ), and campaign management (74%, with 47% very important ). Market research (43% very important ) and customer service and order management (also 43% very important ) were also high among business functions regarded as critical. In fact, the ESRI/TechTarget study shows 33 % of the organizations indicate that using or planning to use real-time location intelligence oriented solutions is essential to their business success; 54% of organizations from Ventana Research recent study consider the LI very important or important to providing improved ability to visually display and analyze customer and operational data, through a LI solution. Why is this so important? The need for functionality to help organizations understand the true value of a customer or predict the future potential cash flows associated with customers will become increasingly critical as a tool for making major business decisions. Market-based experience suggests that real-time modeling and decision optimization, enabled by location intelligence solutions, are the keys to success for companies striving to achieve the desired customer experience and deliver differentiated experiences by channel. 3

4 Of critical concern, is traditional customer data warehouse and customer analytics databases inability to identify Where things happen. Said another way, if organizations can t properly identify where the who, what, when and how in their business happens, then their decisions and recommendations on how best to deliver a satisfying customer experience might always be in doubt. For example, in the highly competitive wireless market, if wireless providers can t track where customers will be, and what behaviors and events actually happen within that locale then it will be next to impossible to predict what will happen in the future and where. Managing customer satisfaction is about delivering a customer experience that meets expectations. These modeled experiences become more robust and more valuable when you add in the fifth dimension- the where factor. So, if the organization has limited or no capabilities to hypothesize the where of future customer behaviors and to model those behaviors against current market outcomes, then their customer analytics teams will lack the full range of capabilities necessary to support new product or service introductions and to sustain desired loyalty behaviors. THE IMPACT The need for advanced LI solutions has never been stronger. It s a well known axiom of marketing that it s more expensive to attract a new customer than it is to retain an existing one. With compressed margins, globalization, and lack of opportunities for organic growth, this is more relevant than ever and applies not only to customers, but information. Organizations must leverage existing data to develop products better suited to their customers needs in order to retain business. The ability to analyze, plan, and predict customer behavior in real-time becomes a key component of a solid customer acquisition and retention strategy. Drivers for Real-Time Decisioning As a result, organizations are turning to real-time decisioning solutions to meet the increased competitive pressures. The ability to anticipate customer needs is a key ingredient in delivering greater customer value and competitive differentiation, and is a strong driver for adopting real-time location intelligence capabilities. Communications service providers look a lot more like High-Tech product and service companies these days, then plain old telephone companies of years gone by. These high tech product and service providers sell mobile and Internet devices as a means to drive subscriber data use. These devices often have shelf life of 6-9 months before being outdates and leap-frogged with newer devices. This forces high-tech device providers and their channel partners, the communications services providers, to know more about and provide better service to their existing customer base, because product leadership and innovation no longer provide a sustainable advantage in commodity-based businesses. This also means that increasingly a customer-intimate marketing organization can be a fast-follower in delivering new products to market if they know where to focus their marketing spend to either gain the biggest lift in device uptake or even convince their subscriber base to sit out the current device life-cycle and wait for the next big thing. 4

5 As well, real-time, location oriented decisioning, linking the where factor together with other key data can better enable marketing departments, retail store operations and even supply chain with the necessary information to promote and sell the new products and build brand equity, while delivering more differentiated and better service. This location-oriented analysis will help to visualize the pockets of early adopters around a metropolitan area. Store channel operations can team with supply chain to ensure new devices are in the right stores closest to the pockets of target customers. Marketing can better tailor their local print advertising, spot radio, TV and Cable ad buys to get the message to the right targets in the right geographies within a larger metro area. Even better, in the world of mobile devices and mobile advertising, these same providers can greatly improve the lift in their location based mobile marketing (SMS, MMS, video, display, etc.) by leveraging the improved learning from location based analysis to geofence their own mobile messaging. For another example, Communications Service providers have been focused on protecting their most valuable customers, which may or may not be their most loyal. These most valuable customers are the ones who chose higher price point subscription plans but under-utilize their voice or data monthly usage. Service providers are most likely to depend on real-time analytics solutions to monitor and track these target customer segments. And they may even be better positioned to protect these segments from churning, even more so then the most loyal customer. But, this effort is being adopted across the industry and overall, a better understanding of customers enables providers to deliver a fit to purpose customer experience. Like the arms race of a bygone era, service providers need to step up their real-time analytics and decisioning capabilities. Most current solution sets lack the location aware analysis capabilities that can enrich the understanding of customer s and improve the analysis outcomes that drive the next best activity to retain the most valuable customers. Vertical Adoption of Real-Time Decisioning Competition has driven providers to offer bundled services and promotional pricing plans to overcome customer inertia to switching providers. In turn, providers use market conditions as opportunities to up-sell existing customers. Real-time market based analysis leading to improved decisioning is immensely critical in an industry where market conditions are changing by the minute. Adding the context of where together with the other analysis dimensions can only improve the analysis outcomes. Further, presenting the analysis in a map view, with advanced query and data visualization tools, such as longitudinal analysis using time sliders, integrating heat maps to visual results with marketing and sales performance data increases the efficacy of recommendations. The marketing and sales functions, which in most Service Provider organizations is empowered with the responsibility for identifying, attracting, satisfying, and keeping customers, are clearly two of the lead players to benefit from LI. Marketing functions are becoming increasingly quantitative; they are replacing gut feel with data-driven decision making. Data drives the pursuit of efficiency and the achievement of measurable results. Sales functions can be important beneficiaries of LI. Sales reports typically focus on providing visibility into the pipeline. Managers can use data insights to improve sales forecasting of potential revenues based on deeper knowledge of priority opportunities, most valued customer segments, improved Territory Design, Management and Optimization. Clearly customer-specific information allows an organization to tailor its offers, incentives, and customer service levels to ever changing market conditions (e.g., price, incentives, etc.). Providers can not only exceed customers expectations but also anticipate them accurately in the future. Adopting next-generation LI in telecom provides ample opportunity to improve customer behavior management and to deliver an intelligent, informative, and interactive customer experience. 5

6 SITUATIONAL FACTORS The speed at which organizations track, monitor, integrate, and analyze data varies depending on the technology used. Conventional wisdom in most organizations would tell you that on average, it takes two to five business days to make a real-time decision, with some taking longer. In other words, current real-time solutions are not real time and lack of speed analyzing customer data to meet their needs is still a challenge across the Service Provider segment. Logically, then the analysis to decision cycle time is directly related to the level of satisfaction with the solution. In general, high powered users of customer analytics and customer intelligence solutions are least satisfied with the more complex processes that support their customer-centric business objectives, such as the days required to respond to a competitive marketing campaign in real-time. In an environment where customers have many product choices and vendor options, the ability to react faster than the competition is critical, and more than a few days may be too long. Location Intelligence solutions combine the contextual learning of where integrated with qualitative and quantitative data, allowing for more sophisticated analysis and improves efficacy of the decision outcomes. By developing a LI strategy that looks more broadly, at the full set of real-time enterprise decisions- customer, product, channel, network, financial, organizations can use a robust analysis and decisioning business architecture to meet the business objectives more consistently. The value proposition of real-time location intelligence is driving future adoption of the technology. In fact, 12% of the respondents plan to implement or pilot a solution over the next year, and 31% of the respondents plan to evaluate LI technologies. Currently, other industry segments such as Retail; Consumer Products and Pharma/Life Sciences are the innovators and early adopters. However, Communications Service Providers are likely to increase their investments in LI and in time may lead the pack for pilots and full implementations over the next few year. KEY CONCLUSIONS AND TAKEAWAYS Managing the organization and aligning leadership is critical to success when new capacities and paradigms are embraced by any organization. In an effort to achieve business growth and profitability objectives, organizations will need to go beyond reporting and analytics, business intelligence (BI), and customer relationship management (CRM) and move more toward implementing on-demand location intelligence (LI) solutions. Focusing on customer- and technology-based solutions is not new, but customer information is still not being leveraged to its full potential. True LI solutions, and the benefits they offer to organizations and customers, remain elusive due to incomplete or inadequate technology deployment and incorporating LI leading practices into strategic analysis processes. More challenging is the fact that companies have been limited leveraging location data into comparing customers specific attributes, attitudes, and preferences about products/services, demographic data, purchase patterns, and self-perceptions. Location can help in comparing or contrasting how individuals fit into larger customer groups, hetero or homogeneously, or even with longitudinal tracking and analysis. Therefore, the need for an advanced LI solution is at its strongest. As a result, organizations are turning to location intelligence oriented decisioning solutions to meet the increased competitive pressures. However, simply implementing a traditional LI solution, even with some real- time capabilities, is not enough to ensure success. 6

7 A comprehensive LI solution must deliver information in a timeframe appropriate for on-demand decisioning, must support business strategy, and must combine three primary components: people, process, and technology. The technology of an on-demand LI solution includes software for integration, management, analysis, and delivery of information; tools for supporting workflow management and collaboration; and the underlying hardware platform to support the availability and scalability needs of the increasing user base. Underlying such a decision-centric LI solution must be a robust platform for data integration and data quality without which LI projects are bound to fail. As the data volumes and frequency with which data is collected increase, the challenges of managing data quality and integration are likely to continue. So in order to take that information to the next level, a business must employ a LI solution that takes data relevance into account and delivers a comprehensive customer profile. LI will provide other benefits to an organization by increasing knowledge about the customers themselves, and improved ability to predict customer behavior in an appropriate time frame. The advantages are obvious: improved service, increased customer satisfaction, improved cross-selling initiatives, increased customer advocacy for the organization, and, of course, customer retention, new customer acquisition, and increased revenues. In addition, integrated and real-time data are increasingly becoming a corporate mandate for reporting, risk mitigation, and compliance. As a result, on-demand LI can be leveraged to bring insight to the entire organization. Who Should Take Advantage of a Location Intelligence solution? Location Intelligence solutions can be integrated into all facets of your company, especially marketing, sales, distribution, and logistics. Your experts in marketing studies, site acquisition, marketing and communication, sales management and sales operations, finance, store operations, merchandising or store managers will benefit from a Location Intelligence solution to solve complex location-dependent business problems., a new generation of Location Intelligence Solutions is the new generation of Location Intelligence applications integrating predictive analytics, performance management, and marketing management solutions to solve complex locationdependent business problems. To learn more about, visit Sources New Generation of Location Analytics, new-generation-location-analytics Location Intelligence Benchmark Research, Ventana Research 2011 Revealing the Where of Business Intelligence using Location Analytics, TechTarget & ESRI, 2012 Customer Analytics in the Age of Social Media, TDWI Research,