Mark Quinlivan is the CEO of Carrier IQ; he has over 23 years of domestic and international management experience. Most recently, Mr Quinlivan was the COO of edocs, acquired in 2005 by Siebel Systems. Before edocs, Mr Quinlivan held senior positions at Lucent Technologies including as SVP of Worldwide Consulting and Integration. Prior to Lucent, Mr Quinlivan held senior management positions at Ascend Communications and Stratus Computer. Mark Quinlivan earned an undergraduate degree in Management and a Masters degree in Computer Science from WPI, and completed the PMD program at the Harvard University School of Business.
Today’s complex service environment is hard to control without adequate data. Most of the traditional ways of measuring network services are based upon the use of network measurements that quite often do not give an accurate picture of the end user’s experience. This is particularly true for data-based services. Mobile Service Intelligence uses information from today’s highly sophisticated handsets, while in normal use, to monitor true customer experience both to assess service quality and, importantly, to predict future revenue opportunities.
In a mobile world where devices are increasingly expected to access more data, perform more functions, and live off-line as well as off-portal, Mobile carriers and handset vendors need far more insight into the way networks and devices combine to deliver mobile services. It is a world that has expanded far beyond voice and SMS; it is no longer enough just to know how the network is performing, how much the customer is spending or the phones’ capabilities. The growth of mobile broadband services among European carriers amplifies the need to connect the dots to manage and improve the quality of the end-to-end customer experience and be able to segment this data in detail by device type, application and location. This is particularly challenging when no network traffic is generated; for instance, when a user attempts - and fails - to access a data service or when it is the speed of the response of the device that matters. With the arrival of new techniques for delivering detailed and accurate data about usage and experience at the handset, carriers are finding new ways to improve customer satisfaction. Mobile Service Intelligence uses information from phones while in normal use to monitor true customer experience both to assess service quality and, importantly, to predict future revenue opportunities. Tracking customer needs The European mobile market is constantly evolving but quality remains a critical differentiator, whether you see the mobile industry as a leading-edge content provider or as a utility pipe that delivers third-party offerings. Gone are the days when services were just a network with a phone at the end. Today’s services are the result of a complex value chain including content providers, aggregators, gateways, and handset, laptop and device applications. As a result, it is no longer sufficient to measure the quality of the component parts alone; operators need to know about the end-user experience and the way they consume the delivered services. The customer expects decent data, music, video and/or games, not just quality voice communications. Like with other services, when expectations are not met consumers simply go to another provider. Meeting customer expectations by improving a service or a handset in isolation is increasingly difficult if you do not know exactly what is happening as the customer sees it. Sure, carriers can deploy drive testing, use network probes and protocol sniffers, wait for returns, conduct user surveys, or just hope that customers will call in describing their experiences. The problem is that none of these options really gives a picture at the level of detail needed or within the timeframe required. Without detailed and accurate data, carriers miss opportunities to improve customer services and, importantly, to anticipate threats to revenue or opportunities. In fact, recent evidence suggests that some of the KPIs (key performance indicators) carriers presently use to manage their businesses have a limited impact on overall customer satisfaction, so crucial in the current market climate. For instance, one commonly finds traditional voice-based metrics being used to monitor network quality including data services, and with very few metrics that directly measure data services and provide true indications of end-point, customer’s device, performance. Operator challenges In this world of complex services, operators can play a range of possible roles - from total service provider to pure data transport. Data transport is a commodity business that is unlikely to bring operators new revenues. On the other hand, many operators that tried to be total service providers have since elected to provide an intelligent pipe in collaboration with established content brands (like Google, Yahoo and even Apple) giving consumers what they crave whilst keeping the door open to new revenue opportunities. So the operator has two challenges, if their product is a commodity, the differentiation is based on price and customers’ experience. If the operator is an intelligent pipe, it needs to acquire the intelligence to play this role. The challenge to provide this intelligent insight is being able to understand, evaluate and strategise about areas which have previously remained hidden from the operator. Two examples articulate this problem well, especially in regards to mobile content: To accelerate mobile content usage and uptake during the last ten years, carriers have been increasingly adopting an open network approach. To achieve this they involve numerous third-party content providers, who use the carrier’s network to attract their own subscribers. This indirect relationship means that carriers who already experience severe limitations measuring the usage and usability of content are now challenged to measure the even wider field of content distribution. When they can measure how content is consumed on the device itself, operators get a better picture of the customer satisfaction and usage levels. A specific example comes from an operator that was monitoring data services to assist them in selecting between equipment vendors. The operator was using traditional ‘dropped calls’ statistics to measure data quality. Investment decisions were based on this and other information. When the actual throughput was measured based on delivered services the results were very different; the number of dropped ‘data calls’ was shown to have very little impact on total data throughput or the customer’s experience. In effect, the historical measures did not accurately provide the needed information and could have led the operator to make incorrect business decisions. Traditional methods including surveys, network monitoring and device management tools all work well, but they do not give the depth of insight into service quality and customer experience required. Now, as phones and devices become smarter, more capable and more complex, it is possible to use the device itself to measure service quality and user experience at the device - where the customer receives the service - and obtain a level of insight previously unavailable to operators. Mobile service intelligence This approach is called Mobile Service Intelligence; it uses the mobile phone or broadband dongle itself, combined with advanced data processing applications to provide detailed metrics. These metrics directly represent the quality and nature of the services being delivered to the customer base. Mobile Service Intelligence is able to do this by analysing data on usage patterns and fault conditions by type, location, application or network performance from millions of users, even when that functionality is independent of the network. This analysis puts the ‘IQ’ or ‘smarts’ into the data collected. For example, a carrier launching a new service targeted at a certain age group, initially has strong take-up, but then it tails off. The operator is then uncertain whether this is due to market saturation or up-take issues and cannot resolve the problem using current methods. By using Mobile Service Intelligence, operators can monitor services in detail, allowing them to quickly identify problems at the root. For instance, it may be that the limited take-up is not due to lack of demand, but to the difficulty users have accessing the service on the first attempt. With this insight, the operator working with the handset or application vendor can resolve the problem early in the product’s life cycle and use an advertising push to drive a new wave of take-up. This new approach can also help operators set new KPIs to improve the customer experience. For instance, an operator’s product manager hears complaints from the field regarding a service, but each of the internal departments claim, based on their own operating statistics, that their part of the solution is functioning well. Mobile Service Intelligence techniques helps classify the problems and create new KPIs based on actual customer experience. As a result, business units can track customer-focused rather than equipment-focused KPIs and ensure that investment and improvement choices are targeted for customer benefit. Actionable intelligence Every division and every business unit can use Mobile Service Intelligence applications. A recent report by Tony Cripps at Ovum called, ‘Mobile service metrics: overcoming the experience gap’, highlights the importance of this intelligence. Without device-side insight, operators miss the opportunity to improve the customer experience and increase revenues. The report concluded that there was a high degree of interest in utilising such data by a broad spectrum of vendors, including suppliers in the network and service management space, mobile device management, data warehousing, business intelligence and customer care arenas. This new generation of ‘actionable intelligence’ is increasingly sought after and operators have come to recognise the value of actively managing the business towards end customer experience based on insight and differentiation. Carriers will compete to offer content and service providers a value proposition beyond simple data transport. Mobile Service Intelligence can provide the insight and differentiation that helps wireless operators make smart business decisions that can dramatically lower operating costs, increase customer satisfaction, reduce customer churn and increase revenues.