Pitney Bowes Doubles Down on Customer Engagement

From its history of managing postal mail, Pitney Bowes has expanded into products for data management, analytics and location intelligence, as my colleague Mark Smith noted. Continuing this expansion through internal development and acquisitions of vendors such as Portrait Software and RTC, it has added to its portfolio products that include customer information management and customer engagement.

I have long maintained that companies can’t really improve customer engagement unless they know their customers. To get to know them they need systems that can extract fromvr_Customer_Analytics_05_dissatisfaction_with_customer_analytics all their data stores and analyze all forms of customer data. In this effort, our benchmark research into next-generation customer analytics shows, the most common impediment (for 63% of organizations) to applying such tools is that the data is not readily available. Pitney Bowes addresses this and related issues through Customer Information Management, a suite of products that provide data management and integration, data quality and customer analytics and enable companies to do customer analysis based on a range of data sources. As yet it doesn’t work with many unstructured sources of customer data such as call recordings and text-based records, which are needed to complete the full view of the customer to support information-driven decisions and actions.

For me the most interesting features are found in its suite of Customer Engagement products, which although having document management at their core are being developed to include an array of channels of engagement and handling of interactions across the enterprise. Pitney Bowes says that it has a five-year plan to create a single platform that will support omnichannel customer engagement across assisted and self-service channels throughout the customer life cycle and across the enterprise; the primary goal is to help users increase customer lifetime value. Recently the company announced the latest release of a key component, EngageOne Server 4.0, which will be the foundation for the complete platform. EngageOne Server enables companies to manage all aspects of producing electronic documents and delivering them to customers through a variety of channels. It includes capabilities to create and manage document templates, author and approve text-based content, produce required content as a batch process, on demand or interactively, and deliver the content in print, fax, email or SMS forms or on the company’s website. All of this content can be stored securely for later retrieval and use. Release 4.0 adds several new features to enhance functionality and make it easier to use, more scalable, accessible and secure, and cloud-ready.

The first non-text-based channel it supports is personalized interactive video (PIV). This comes by way of the acquisition of RTC and to my knowledge makes Pitney Bowes the first vendor to support this as a self-service channel. The concept is simple: Instead of making a phone call customers connect to a voice-activated video that enables them to have an interactive dialogue in much the same way as talking to an agent. The dialogue can include a real person or an animated character asking questions or presenting answers, video clips, links to other shared content such as a website and presentation of content such as a document. It can change dynamically depending on information provided or the customer’s responses to questions, so that with the right programming the interaction can be personalized for the caller and the issue.

The interaction thus can take many forms – a Q&A session, a request for information, a complaint about a product or a query about a bill. Here is a relatively simple example: The caller provides his or her name, asks a question about the latest bill, is presented with an image of the bill and then engages in a Q&A session to resolve the issue using the bill to focus the dialogue. In trying the system, I found it easier to use than touch-tone or visual IVR, more engaging than a video call and more satisfying than speech-activated software-based agents. However, I caution companies choosing to work with this channel to create such videos with the customer in mind, ensuring that it supports what customers want to do and how they want to do it, rather than as a means of trying to reduce the cost of handling interactions.

Our benchmark research into next-generation customer engagement shows that companies have three main challenges in providing customers with the omnichannel experiences they expect: It is difficult to integrate systems (for 49%), channels vr_NGCE_15_supporting_multiple_channelsare managed as silos (47%), and responses to customers across channels are inconsistent (39%). Addressing all these challenges is not easy, as I explained in a recent perspective about the technologies required to deliver EPIC customer experiences. The Pitney Bowes products have capabilities that can help address these issues, including tools that  integrate with third-party products and other tools for collaboration that enable users to share information and join in the resolution of issues, which has the potential to improve consistency in interaction handling.

EngageOne Server has more work to be a complete omnichannel product, but Pitney Bowes says it is committed to developing it into a comprehensive customer engagement platform that supports consistent handling of interactions across all channels and throughout the customer life cycle. My research shows that video calling is a channel likely to take off as consumers use video calls to engage with each other. PIV innovatively builds on video calling and has the potential to accelerate adoption of interactive self-service.

As I recently wrote I advocate customer lifetime value as a key customer experience metric, but it is not easy to calculate. Pitney Bowes has a development program in place to create products that should help companies meet these objective so I will keenly watch how it develops both its customer information and customer engagement products and recommend that companies seeking to improve these aspects do likewise.


Richard J. Snow

VP & Research Director

Data and Analytics in the Cloud is a Reality Today

Our recently completed benchmark research on data and analytics in the cloud shows that analytics deployed in cloud-based systems is gaining widespread adoption. Almost half (48%) of vr_DAC_04_widespread_use_of_cloud_based_analyticsparticipating organizations are using cloud-based analytics, another 19 percent said they plan to begin using it within 12 months, and 31 percent said they will begin to use cloud-based analytics but do not know when. Participants in various areas of the organization said they use cloud-based analytics, but front-office functions such as marketing and sales rated it important more often than did finance, accounting and human resources. This front-office focus is underscored by the finding that the categories of information for which cloud-based analytics is most often deemed important are forecasting (mentioned by 51%) and customer-related (47%) and sales-related (33%) information.

The research also shows that while adoption is high, organizations face challenges as they seek to realize full value from their cloud-based data and analytics initiatives. Our Performance Index analysis reveals that only one in seven organizations reach the highest Innovative level of the four levels of performance in their use of cloud-based analytics. Of the four dimensions we use to further analyze performance, organizations do better in Technology and Process than in Information and People. That is, the tools and analytic processes used for data and analytics in the cloud have advanced more rapidly than users’ abilities to work with their information. The weaker performance in People and Information is reflected in findings on the most common barriers to deployment of cloud-based analytics: lack of confidence about the security of data and analytics, mentioned by 56 percent of organizations, and not enough skills to use cloud-based analytics (42%).

Given the top barrier of perceived data security issues, it is not surprising the research finds that the largest percentage of organizations (66%) use a private cloud, which by its nature ostensibly is more secure, to deploy analytics; fewer use a public cloud (38%) or a hybrid cloud (30%), although many use more than one type today. We know from tracking analytics and business intelligence software providers that operate in the public cloud that this is changing quite rapidly. Comparing vr_DAC_06_how_to_deploy_cloud_based_analyticsdeployment by industry sector, the research analysis shows that private and hybrid clouds are more prevalent in the regulated areas of finance, insurance and real estate and government than in services and manufacturing. The research suggests that private and hybrid cloud deployments are used more often for analytics where data privacy is a concern.

Furthermore, organizations said that access to data for analytics is easier with private and hybrid clouds (29% for public cloud vs. 58% for private cloud and 67% for hybrid cloud). In addition, organizations using private and hybrid cloud more often said they have improved communication and information sharing (56% public vs. 72% private and 70% hybrid). Thus, the research data makes clear that organizations feel more comfortable implementing analytics in a private or hybrid cloud in many areas.

Private and hybrid cloud implementations of data and analytics often coincide with large data integration efforts, which are necessary at some point to benefit from such deployments. Those who said that integration is very important also said more often than those giving it less importance that cloud-based analytics helps their customers, partners and employees in an array of ways, including improved presentation of data and analytics (62% vs. 43% of those who said integration is important or somewhat important), gaining access to many different data sources (57% vs. 49%) and improved data quality and data management (59% vs. 53%). We note that the focus on data integration efforts correlates more with private and hybrid cloud approaches than with public cloud approaches, thus the benefits cannot be directly assigned to the various cloud approaches nor the integration efforts.

Another key insight from the research is that data and analytics often are considered in conjunction with mobile and collaboration initiatives which have different priorities for business than IT or in consumer markets. Nine out of 10 organizations said they use or intend to use collaboration technology to support their cloud-based data and analytics, and 83 percent said they need to support data access and analytics on mobile devices. Two-thirds said they support both tablets and smartphones and multiple mobile operating systems, the most important of which are Apple iOS (ranked first by 60%), Google Android (ranked first by 26%) and Microsoft Windows Mobile (ranked first by 13%). We note that Microsoft has a higher percentage of importance here than its reported market share (approximately 2.5%) would suggest. Similarly, Google Android has greater penetration than Apple in the consumer market (51% vs. 41%). We expect that the influence of mobile operating systems related to data and analytics in the cloud will continue to evolve and be impacted by upcoming corporate technology refreshment cycles, the consolidation of PCs and mobile devices, and the “bring your own device” (BYOD) trend.

The research finds that usability (63%) and reliability (57%) arevr_DAC_20_evaluation_criteria_for_cloud_based_analytics the top technology buying criteria, which is consistent with our business technology innovation research conducted last year. What has changed is that manageability is cited as very important as often as functionality, by approximately half of respondents, a stronger showing than in our previous research.  We think it likely that manageability is gaining prominence as cloud providers and organizations sort out issues in who manages deployments along with usage and licensing, along with who actually owns your data in the cloud which my colleague Robert Kugel has discussed.

As the research shows, the importance of cloud data and analytics is continuing to grow. The importance of this topic makes me eager to discuss further the attitudes, re­quire­­ments and future plans of organizations that use data and analytics in the cloud and to identify the best prac­tices of those that are most proficient in it. For more information on this topic, and learn more on best practices for data and analytics in the cloud, and download the executive summary of the report to improve your readiness.


Ventana Research