Old Dog, New Tricks

Ok let’s clear one thing up straight away – the old dog in the title isn’t me! In this case the old dog is the customer data technology market, which hasn’t yet delivered that elusive “full 360 view” of a customer. It is based on relational database technology and separated analytic and operational uses. It’s time to teach that old dog some new (technology) tricks. Plan C

I am thrilled to once again be focused on customer data and analytics technology. I’ve spent most of my career working on customer-centric technology, from master data management to integration and governance, big data and recently predictive analytics. Most organizations I’ve met want better insights on their customers – in fact, 50% of big data projects are focused on the customer domain. The need for good customer data has never been greater.

Despite that, the number one problem I’ve heard for 15 years is “my customer data isn’t accurate”. That’s as true today as it was in 1999 when the Customer Data Integration (later Master Data Management) market emerged.

How can this still be a challenge today? It’s because the world we operate in has changed so drastically. The proliferation of devices and the Internet of Things mean that customers are interacting with organizations via more channels and devices than ever before. And those new interactions don’t produce nicely structured data ready to be loaded into a database or warehouse for analysis. In fact, 80% of data is unstructured – webchat logs, social media posts, call centre recordings, PDF documents … and all of those contain value insights into the customer.

New ‘big data’ technology allows us to manage all forms of data from internal and external sources, to analyze incredible volumes of data at real-time speeds. These technologies can challenge established status quo and bring together operational and analytic processing in one system. They can also truly build a complete context for a customer by moving well-beyond traditional data record matching into the realm of ‘understanding the complete context of all customer data’. But those technologies are a collection of tools – collectively they could solve the customer data problem, but what’s needed is someone to bring them all together with a specific focus on customer data.

And that is why I am so thrilled to join InfoTrellis. They have a unique offering to address the customer data problem in a new way with AllSight – managing every type of data, building the full context for a customer with contextual record-building, and enabling operational and analytic processing on a single system.

Watch out customer data technology market – you’re about to be disrupted!

A Tale of Rework & Opportunity Lost: Ungoverned Big Data

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Has this ever happened to you? You want to use some information for a business purpose, only to realize that you are not permitted to use the information in that way? Sure it has. It happens all the time. It happened to one company who we will call ABC. ABC hired a Chief Data Officer, Bill. Bill’s first task was to inventory all of ABC’s data, and how and where it was being used ( learn how to inventory your data and manage governance policies by clicking here). He also had to take stock of ABC’s existing governance program, to figure out all of the existing policies and whether they were being followed.

Bill’s first few months on the job were great. By taking inventory of data, he was able to help many other people – the CFO, VP Sales, and VP Operations, by connecting them with the data they needed. Then along came “the retention project”. Mary, the Chief Marketing Officer, had commissioned many different projects – some of them with cloud-based apps and outside vendors. She was getting great results, and “the retention project” was one such example. She got that off the ground with a 3rd party vendor and cloud solution to analyze web data trends and make predictions on customer churn events. She married that data with her customer database to make decisions on who should be retained. The project was then handed over to internal IT to support, and that’s when Bill got involved.

As Bill’s team audited the ‘retention project’, they noted that customer web view data was being used without obtaining their consent. By using that data to make offers to the customer, it violated a privacy law. That was a fairly cut and dry case of a governance rule violation, so Bill moved to shut down that data feed. Mary, predictably, wasn’t too pleased. She said shutting down that data flow essentially meant shutting down the project. Bill said ‘but it’s against the law’. And then Mary produced results that showed a 30% improvement in key client retention. Believe it or not, a vigorous debate ensured about the merits of continuing the campaign even though it was in violation of the law!

After thinking it over that night, Bill came up with a different approach. He and the governance team devised a rapid out-reach program to obtain consent from their client base. The consent request was included with another “business as usual” client outreach, and the thinking was it would improve the odds of gaining consent. In the interim, the data governance team had determined that mixing the client web-log data with external data and using it to determine an “average customer retention event” could possibly work, because it wouldn’t violate privacy laws. Bill’s team worked with Mary’s marketing analysts to test the analytics – and the result was the predictions were only -5% less accurate, which was an acceptable deviation. Project ‘retention’ was kept up and running, and yielded very impressive retention results during the interim period in which client consent was gathered.

ABC learned valuable lessons through ‘project retention’. First, they now collaborate on all data-centric projects with Bill and the data governance team to determine the right way to use data while staying in line with governance rules (watch a video on how to manage proactive governance in your organization here). Second, they established a proactive customer consent mechanism to gather a broader reaching set of consents for analytics and marketing purposes. And that’s really the moral of the story. The “bad guy” in this real-life scenario was a lack of process, which unwittingly pitted two employees into a zero-sum game, when they should have been working together towards the same goal. Violating privacy laws and governance rules are significant issues, but are actually the least of your concerns when it comes to governing big data. The real potential downside of ungoverned big data is rework and lost time – which translates into lost customers, lost revenue, and missed opportunities.

For more on how to govern big data proactively, read about Building Confidence in Big Data .

Share your input on whether governance, marketing, and big data & analytics is a zero-sum game in your organization or if you proactively work together to optimize your data usage.

You Can’t Forget What You Can’t Remember

In order to forget something, first you need to remember it.  That simple premise will cause organizations a great deal of pain as consumer privacy legislation takes effect.

The concern about consumer data privacy is at an all-time high.  70% of Europeans are concerned about the reuse of their personal data.[1]  86% of Americans are concerned with data collection from internet browsing and how it is used to generate personalized banner advertisements.[2]   Their primary concern is how that data may be used for other purposes, or packaged and resold to other entities.  With data breaches and issues such as the NSA’s collection of private data making headlines each week, it’s no wonder that consumer sensitivity is heightened.

This will present a very large problem for companies, because law makers are starting to take action.  The European Union announced changes to the 1995 Data Protection Directive to take effect starting in 2014.[3]  It contains one very logical and innocent looking directive – “the right to be forgotten” which means that upon request from a consumer, an organization must delete all of their personal data.  That sounds simple.  It’s actually a wildly complex problem, because of the premise above – you cannot forget what you cannot remember.  And most organizations aren’t particularly good at remembering their customers.

Click here to READ THE REST OF THIS BLOG ON http://www.ibmbigdatahub.com  – or click or go to http://ibm.co/1bEaJGS

Watch a video discussion on this topic here http://ibm.co/1gWKqwF

[1] Forrester Research.  EU Regulations And Public Opinion Shift The Scope Of Data Governance

by Henry Peyret, October 17, 2013

[2] Perfect Storm For Behavioral Advertising:

How The Confluence Of Four Events In 2009 May Hasten Legislation (And What This Means For Companies Which Use Behavioral Advertising) By:  Susan E. Gindin

[3] Forrester Research.  EU Regulations And Public Opinion Shift The Scope Of Data Governance

by Henry Peyret, October 17, 2013

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