Marketing Analytics for Communications Service Providers

WHITE PAPER Marketing Analytics for Communications Service Providers How a customer-centric data repository and marketing analytics engine can boost your relevance and results Marketing Analytics for Communications Service Providers Table of Contents The Pitfalls of Product-Focused Marketing........................................... 1 From Product-Centric to Customer-Centric........................................... 2 The Data Foundation for a Comprehensive, Customer-Centric View.................2 Data Quality and Analytics................................................................................3 Outputs of the Marketing Analytics Engine.......................................................4 Marketing Analytics Engine in Action: Microsegmentation....................... 4 Identify groups of customers with similar needs, wants and preferences...............................................................................................5 Home in on the specific clusters with multivariate microsegmentation..............5 Closing Thoughts................................................................................. 6 How SAS Can Help.........................................................................................7 i Marketing Analytics for Communications Service Providers This white paper was written by Ken King, Director of Telecommunications and Media Convergence at SAS. King is a global expert on the use of advanced business analytics to solve complex business problems for the communications industry. He consults with SAS clients and industry thought leaders on topics such as churn management, social network analysis, product bundling, offer optimization, forecasting and operational improvements. SAS solutions are deployed in almost every large telecommunications service provider. King has more than 25 years of global telecom industry experience in designing, deploying and supporting voice and data networks. He has extensive experience in migration of communication networks from circuit to packet switching. His background includes roles in sales, marketing, product management, alliances, engineering, testing, training and technical support. King has a BS in computer and information science from the University of Florida and an MBA in product innovation management from North Carolina State University. He has dual Australian and American citizenship. Marketing Analytics for Communications Service Providers What if, with a few clicks of the mouse, you could identify the business accounts and prospects that had responded well to your last campaign, determine exactly what attributes they shared, and use that information to find 1,000 more just like them? With that insight, you could make smarter marketing decisions with each campaign. Without that information, marketing would be something of a shot in the dark. For example, relying on intuition and a visual scan of the data, you might surmise that companies with 50 to 75 employees seemed more likely to accept a particular offer. You would generate a target list of companies of that size, execute a campaign against that list, and have it flop. OK, so that wasn’t it. You might then theorize that the best targets seemed to be locally owned retail outlets, so you’d run a target list, execute another campaign, and have lackluster results again. Trouble is, the good prospects are probably defined by a combination of attributes. From eyeballing the data, would you know that the best prospects are consumer electronics retailers with a revenue increase of 4-7 percent in the last six months, who have not upgraded their services or equipment in the previous 24 months? Or retailers that have 10 or more locations within three adjoining area codes? Or community colleges and trade schools that offer 50 or more online courses to local and out-of-state students? Such insights require the ability to correlate information from multiple data sources: internal and external, transactional and demographic, customer and market. Extracting meaningful insights from masses of disparate data requires more than intuition and common sense. It takes analytics. That realization is driving a profound transformation in how communications service providers are generating – and using – customer insights. The Pitfalls of Product-Focused Marketing For most service providers, the market is highly fragmented, including consumers, small to midsize businesses (SMBs), and enterprises representing the gamut of vertical markets. Market offers, messages and communications are quite different for each group. This paper focuses on the SMB market segment, but the concepts apply to any target market. The growing competitive scene leaves no room for inefficient or scattershot marketing efforts, yet that scenario is common. I recently heard from an SMB marketing director at a major provider who said, “We had a variety of sales channels – inbound and outbound, direct and indirect – to reach our SMB customers, but we found we were getting in each other’s way with overlapping efforts – definitely not optimized. We felt like we were wasting money and still not getting to the entire base of customers with the most relevant product and/ or solution.” 1 Marketing Analytics for Communications Service Providers The problem is not a lack of data. Service providers are awash in data. However, until recently, marketing efforts have tended to be product-oriented, so most data was organized around products, not customers. Internal systems tend to produce data that is difficult to roll up at a customer level. When you face the customer, you want to be relevant and accurate, but when the marketing team works to provide leads to the sales channels, it is often working with incomplete or outdated data, very much oriented around product. A customer either has this product or doesn’t, and that information becomes a key driver of campaigns for that product or the next upgrade of that product. A common approach has been to pick a channel, pick a campaign strategy and a tactic, and say “Go.” The campaign may be super-successful in pockets, but you wouldn’t know why. What was unique about the customers who purchased via the campaign and those who did not? There’s no time for that, and no way to gain that understanding anyway. Just move on to the next campaign. The net effect of this type of process is that if you hit customers too many times with different messages, customers get irritated and find your offers irrelevant. Service providers are seeing the limitations of this traditional marketing model and definitely want to improve their lead targeting and their ability to create offers that represent a win-win for the customer and the CSP. From Product-Centric to Customer-Centric The customer-centric vision a good one: understand your customers better than anyone, so you can market to them better than anyone. You’ll be able to send them the proverbial “right offer at the right time via the right channel.” Obviously, it takes more than masses of subscriber data and transactional data to achieve this ideal. Service providers need a technology platform capable of performing ad hoc analysis, predictive modeling and campaign development – a marketing analytics engine. This platform includes three key elements: a customer-focused data repository, an analytics core with the data quality and analytics tools to transform that data into insight, and the outputs that incorporate that insight into marketing action and other business decisions. The Data Foundation for a Comprehensive, Customer-Centric View The first step in creating a marketing analytics engine is to identify and integrate multiple data sources, including information about customers, products, online activity, sales and campaign results, and contract lifecycle status. The next step is to integrate third-party data, such as Dun & Bradstreet information. A solid marketing analytics engine can incorporate several hundred variables that describe your SMB customers, enabling you to build very effective profiles of them. 2 Marketing Analytics for Communications Service Providers Within a few months, a service provider can integrate a wide range of data sources into an aggregate view to look at customers in totality. With this data foundation, marketers can not only see a customer’s products, services and transaction history, but understand that information in context with purchased third-party data – information such as the business size, vertical market, various firmographics and more. The data framework can (and should) evolve over time. Don’t think you have to spend six or nine months collecting all these data sources before you can get started. The providers that have succeeded with this have done it in a very incremental way. Focus on the most important business question first, and go after the data sources you need to answer that business question. Once you start to organize the data, questions or gaps will appear, and you will begin to understand what additional data you can get. You can continue to add more data sources as you find them, or as your organization merges with or acquires other entities, to continue to nurture a more comprehensive view of customers.