If you’re like me, when you hear the name Pitney Bowes you think “postage meter,” not software. After all, the 93-year-old company that joined the New York Stock Exchange in 1950 and has been listed in the S&P 500 since its opening day might seem more like a relic that never crossed the chasm than a big data and analytics leader.
But perceptions are deceiving.
This morning Pitney Bowes announced that it has added advanced big data management capabilities to its Spectrum Technology platform.
What is the Spectrum Technology Platform?
For those of us who haven’t kept up with Pitney Bowes in the last decade, the company began its transition from a physical products provider to a digital communications company at the beginning of the millennium. It acquired 80, yes 80, companies between 2000-2010, most notable among them: Group 1 Software (data quality and customer communications), MapInfo (location intelligence solutions), Portrait Software (customer-centric solutions that combine advanced customer analytics with inbound and outbound campaign management).
The combination and integration of these purchases result in the Pitney Bowes’ software business and its Spectrum Technology Platform which promises to help enterprises -- large and small -- to extract more value from data to drive greater profitability, reduce risk and deliver more personalized and contextually relevant experiences.
The company’s transition has been so successful that Gartner now names Pitney Bowes as one of four market leaders in Customer Communications Management (CCM) Software.
Not only that, but it claims tech savvy companies like Facebook, eBay, Aon and others as its customers; they use Pitney Bowes products for applications like powering location intelligence for mobile devices, building out global identity (e.g., identifying a customer as he walks into a bank in order to deliver personalized service), to assess risk for insurance companies and so on. The world’s largest CRM provider, who can’t be named, uses their software to identify and eliminate duplicate IDs.
“We’re like the Intel inside,” says Navin Sharma, vice president of Product Management, Information Management Software and Solutions at Pitney Bowes. He says that the Spectrum Platform allows companies to deliver trusted data and insights in context across touch-points to maximize the value of customer information. It does this by aggregating, cleansing and consolidating data from disparate sources (including data from streaming data sources like Twitter, social listening, location data from GPS and web browsers) and enriching it with corporate and third party reference data. Needless to say, Pitney Bowes helps its clients make sense of big data.
Pitney Bowes Introduces the Knowledge Graph
The resulting high quality data is then used to build out a knowledge graph which provides a multi-dimensional views of information so that decision makers from various parts of the organization can see it in a way that’s relevant for them.
“Sales, marketing and compliance want different views of customer data,” says Sharma. “We show them how their most critical data assets relate in context."
Pitney Bowes knowledge graph can also show companies where their customers shop, work and play as well as what relationships they have with products. “It’s a system of interaction,” says Sharma.
The new release of the Spectrum Technology platform includes analytics which can be leveraged for data, to show who’s influential in a network, and who is likely to churn.
Key capabilities in the Spectrum Technology release include:
- Visual Data Modeling: Subject-matter experts’ model to the business outcome using an intuitive "white-boarding" approach delivered via a web UI. This provides an agile way to manage complex relationships and hierarchies and support better collaboration between business and IT functions.
- Process-centric Data Governance: With access to corporate data as well as external sources at their fingertips, business stewards are able to review and resolve issues quickly. They can also capture and visualize data quality trends against established key performance indicators (KPIs) to monitor the health of the data assets in context of their processes.
- Big Data Readiness: With the ability to handle large data sets, combined with advanced clustering and in-memory caching, organizations can process large volumes of data coming in at high velocity.
- Enhanced Entity Resolution: Advanced search coupled with matching algorithms against unstructured data, enables companies high-performance access to disambiguated information for building 360 degree customer views.
- Industry and Application Certifications: In the new version, support for several new standards and applications has been added. This includes support for HL7, the healthcare information standard, latest versions of SAP applications, NetSuite and postal certifications for CASS (US) and SERP (Canada).
Forget 'Share of Wallet,' It’s About the Network’s Net Worth
It can’t be repeated often enough that the companies who leverage their data best will win the future. Pitney Bowes data-enriched platform seeks to do exactly that by helping its customers incorporate big data and social data assets to its other data stores.
“It used to be that the share of wallet was determined by the household, now it’s according to a network’s net worth,” says Sharma.