Category Archives: Master Data Management
Maybe the word “death” is a bit strong, so let’s say “demise” instead. Recently I read an article in the Harvard Business Review around how Big Data and Data Scientists will rule the world of the 21st century corporation and how they have to operate for maximum value. The thing I found rather disturbing was that it takes a PhD – probably a few of them – in a variety of math areas to give executives the necessary insight to make better decisions ranging from what product to develop next to who to sell it to and where.
Don’t get me wrong – this is mixed news for any enterprise software firm helping businesses locate, acquire, contextually link, understand and distribute high-quality data. The existence of such a high-value role validates product development but it also limits adoption. It is also great news that data has finally gathered the attention it deserves. But I am starting to ask myself why it always takes individuals with a “one-in-a-million” skill set to add value. What happened to the democratization of software? Why is the design starting point for enterprise software not always similar to B2C applications, like an iPhone app, i.e. simpler is better? Why is it always such a gradual “Cold War” evolution instead of a near-instant French Revolution?
Why do development environments for Big Data not accommodate limited or existing skills but always accommodate the most complex scenarios? Well, the answer could be that the first customers will be very large, very complex organizations with super complex problems, which they were unable to solve so far. If analytical apps have become a self-service proposition for business users, data integration should be as well. So why does access to a lot of fast moving and diverse data require scarce PIG or Cassandra developers to get the data into an analyzable shape and a PhD to query and interpret patterns?
I realize new technologies start with a foundation and as they spread supply will attempt to catch up to create an equilibrium. However, this is about a problem, which has existed for decades in many industries, such as the oil & gas, telecommunication, public and retail sector. Whenever I talk to architects and business leaders in these industries, they chuckle at “Big Data” and tell me “yes, we got that – and by the way, we have been dealing with this reality for a long time”. By now I would have expected that the skill (cost) side of turning data into a meaningful insight would have been driven down more significantly.
Informatica has made a tremendous push in this regard with its “Map Once, Deploy Anywhere” paradigm. I cannot wait to see what’s next – and I just saw something recently that got me very excited. Why you ask? Because at some point I would like to have at least a business-super user pummel terabytes of transaction and interaction data into an environment (Hadoop cluster, in memory DB…) and massage it so that his self-created dashboard gets him/her where (s)he needs to go. This should include concepts like; “where is the data I need for this insight?’, “what is missing and how do I get to that piece in the best way?”, “how do I want it to look to share it?” All that is required should be a semi-experienced knowledge of Excel and PowerPoint to get your hands on advanced Big Data analytics. Don’t you think? Do you believe that this role will disappear as quickly as it has surfaced?
I love exploring new places. I’ve had exceptional experiences at the W in Hong Kong, El Dorado Royale in the Riviera Maya and Ventana Inn in Big Sur. I belong to almost every loyalty program under the sun, but not all hospitality companies are capitalizing on the potential of my customer information. Imagine if employees had access to it so they could personalize their interactions with me and send me marketing offers that appeal to my interests.
Do I have high expectations? Yes. But so do many travelers. This puts pressure on marketing and sales executives who want to compete to win. According to Deloitte’s report, “Hospitality 2015: Game changers or spectators?,” hospitality companies need to adapt to meet consumers’ increasing expectations to know their preferences and tastes and to customize packages that suit individual needs.
In this interview, Jeff Klagenberg, senior principal at Myers-Holum, explains how one of the largest, most customer-focused companies in the hospitality industry is investing in better customer, product, and asset information. Why? To personalize customer interactions, bundle appealing promotion packages and personalize marketing offers across channels.
Q: What are the company’s goals?
A: The executive team at one of the world’s leading providers of family travel and leisure experiences is focused on achieving excellence in quality and guest services. They generate revenues from the sales of room nights at hotels, food and beverages, merchandise, admissions and vacation club properties. The executive team believes their future success depends on stronger execution based on better measurement and a better understanding of customers.
Q: What role does customer, product and asset information play in achieving these goals?
A: Without the highest quality business-critical data, how can employees continually improve customer interactions? How can they bundle appealing promotional packages or personalize marketing offers? How can they accurately measure the impact of sales and marketing efforts? The team recognized the powerful role of high quality information in their pursuit of excellence.
Q: What are they doing to improve the quality of this business-critical information?
A: To get the most value out of their data and deliver the highest quality information to business and analytical applications, they knew they needed to invest in an integrated information management infrastructure to support their data governance process. Now they use the Informatica Total Customer Relationship Solution, which combines data integration, data quality, and master data management (MDM). It pulls together fragmented customer information, product information, and asset information scattered across hundreds of applications in their global operations into one central, trusted location where it can be managed and shared with analytical and operational applications on an ongoing basis.
Q: How will this impact marketing and sales?
A: With clean, consistent and connected customer information, product information, and asset information in the company’s applications, they are optimizing marketing, sales and customer service processes. They get limitless insights into who their customers are and their valuable relationships, including households, corporate hierarchies and influencer networks. They see which products and services customers have purchased in the past, their preferences and tastes. High quality information enables the marketing and sales team to personalize customer interactions across touch points, bundle appealing promotional packages, and personalize marketing offers across channels. They have a better understanding of which marketing, advertising and promotional programs work and which don’t.
Q: What is the role did the marketing and sales leaders play in this initiative?
A: The marketing leaders and sales leaders played a key role in getting this initiative off the ground. With an integrated information management infrastructure in place, they’ll benefit from better integration between business-critical master data about customers, products and assets and transaction data.
Q. How will this help them gain customer insights from “Big Data”?
A. We helped the business leaders understand that getting customer insights from “Big Data” such as weblogs, call logs, social and mobile data requires a strong backbone of integrated business-critical data. By investing in a data-centric approach, they future-proofed their business. They are ready to incorporate any type of data they will want to analyze, such as interaction data. A key realization was there is no such thing as “Small Data.” The future is about getting very bit of understanding out of every data source.
Q: What advice do you have for hospitality industry executives?
A: Ask yourself, “Which of our strategic initiatives can be achieved with inaccurate, inconsistent and disconnected information?” Most executives know that the business-critical data in their applications, used by employees across the globe, is not the highest quality. But they are shocked to learn how much this is costing the company. My advice is talk to IT about the current state of your customer, product and asset information. Find out if it is holding you back from achieving your strategic initiatives.
Also, many business executives are excited about the prospect of analyzing “Big Data” to gain revenue-generating insights about customers. But the business-critical data about customers, products and assets is often in terrible shape. To use an analogy: look at a wheat field and imagine the bread it will yield. But don’t forget if you don’t separate the grain from the chaff you’ll be disappointed with the outcome. If you are working on a Big Data initiative, don’t forget to invest in the integrated information management infrastructure required to give you the clean, consistent and connected information you need to achieve great things.
“Opportunity for the large community to share experiences, lessons learnt, and help those that are starting the MDM journey get on the right track.”
Next month, Informatica will host its third MDM Day conference. Our past two events in Las Vegas and London have been huge successes thanks to the active participation of our customers, partners, and colleagues. The conference is structured to provide opportunities for you to share your ideas, provide guidance to our product management team, and learn from other customers’ MDM and PIM journeys.
When: February 12th, 8:30 AM – 5:00 PM
Where: Westin Times Square
How: Register Here
“If you don’t like change, you’re going to like irrelevancy a lot less.” I saw this powerful Ralph Waldo Emerson quotation in an MDM Summit presentation by Dagmar Garcia, senior manager of marketing data management at Citrix. In this interview, Dagmar explains how Citrix is achieving a measurable impact on marketing results by improving the quality of customer information and prospect information.
Q: What is Citrix’s mission?
A: Citrix is a $2.6 billion company. We help people work and collaborate from anywhere by easily accessing enterprise applications and data from any device. More than 250,000 organizations around the globe use our solutions and we have over 10,000 partners in 100 countries who resell Citrix solutions.
Q: What are marketing’s goals?
A: We operate in a hyper-competitive market. It’s critical to retain and expand relationships with existing enterprise and SMB customers and attract new ones. The marketing team’s goals are to boost campaign effectiveness and lead-to-opportunity conversion rates, while improving operational efficiencies.
But, it’s difficult to create meaningful customer segments and target them with relevant cross-sell and up-sell offers if marketing lacks access to clean, consistent and connected customer information and visibility into the total customer relationship across product lines.
Q: What is your role in achieving these goals?
A: I’ve been responsible for global marketing data management at Citrix for six years. My role is to identify, implement and maintain technical and business data management processes.I work with marketing leadership, GEO-based team members, sales operations, and operational experts to understand requirements, develop solutions and communicate results. I strive to create innovative solutions to improve the quality of master data at Citrix, including the roll-out and successful adoption of data governance and stewardship practices within Marketing and across other departments.
Q: What drove the decision to tackle inaccurate, inconsistent and disconnected customer and prospect information?
A: In 2011, the quality of customer information and prospect information was identified as the #1 problem by our sales and marketing teams. Account and contact information was incomplete, inaccurate and duplicated in our CRM system.
Another challenge was fragmented and inconsistent master account information scattered across the organization’s multiple applications. It was difficult to know which source had the most accurate and up-to-date customer and prospect information.
To be successful, we needed a single source of the truth, one system of reference where data management best practices were centralized and consistent. This was a requirement to understand the total customer relationship across product lines. We asked ourselves:
- How can we improve campaign effectiveness if more than 40% of the contacts in our customer relationship management system (CRM) are inactive?
- How can we create meaningful customer segments for targeted cross-sell and up-sell offers when we don’t have visibility into all the products they already have?
- How can we improve lead to opportunity conversion rates if we have incomplete prospect data?
- How can we improve operational efficiencies if we have double the duplicate customer and prospect information than the industry standard?
- How can we maintain high data quality standards in our global operations if we lack the data quality technology and processes needed to be successful?
Q: How are you managing customer and prospect information now?
A: We built a marketing data management foundation. We centralized our data management and reduced manual, error-prone and time-consuming data quality efforts. To decrease the duplicate account and contact rate, we focused on managing the quality of our data as close to the source as possible by improving data validation at points of entry.
Q: What role does Informatica play?
A: We using master data management (MDM) to:
- pull together fragmented customer, prospect and partner information scattered across applications into one central, trusted location where it can be mastered, managed and shared on an ongoing basis,
- organize customer, prospect and partner information so we know how companies and people are related to each other, which hierarchies and networks they belong to, including their roles and organizations, and
- syndicate clean, consistent and connected customer, partner and product information to applications, such as CRM and data warehouses for analytics.
Q: Why did you choose Informatica?
A: After completing a thorough analysis of our gaps, we knew the best solution was a combination of MDM technology and a data governance process. We wanted to empower the business to manage customer information, navigate multiple hierarchies, handle exceptions and make changes with a transparent process through an easy-to-use interface.
At the same time, we did extensive industry research and learned Informatica MDM was ranked as a visionary and thought leader in the master data management solution space and could support our data governance process.
Q: Can you share some of the results you’ve achieved?
A: Now that marketing uses clean, consistent and connected customer and prospect information and an understanding of the total customer relationship, we’ve seen a positive impact on these key metrics:
↑ 20% lead-to-opportunity conversion rates
↑ 20% operational efficiency
↑ 50% quality data at point of entry
↓ 50% in prospect accounts duplication rate
↓ 50% in creation of duplicate prospect accounts and contacts
↓ 50% in junk data rate
Murphy’s First Law of Bad Data – If You Make A Small Change Without Involving Your Client – You Will Waste Heaps Of Money
I have not used my personal encounter with bad data management for over a year but a couple of weeks ago I was compelled to revive it. Why you ask? Well, a complete stranger started to receive one of my friend’s text messages – including mine – and it took days for him to detect it and a week later nobody at this North American wireless operator had been able to fix it. This coincided with a meeting I had with a European telco’s enterprise architecture team. There was no better way to illustrate to them how a customer reacts and the risk to their operations, when communication breaks down due to just one tiny thing changing – say, his address (or in the SMS case, some random SIM mapping – another type of address).
In my case, I moved about 250 miles within the United States a couple of years ago and this seemingly common experience triggered a plethora of communication screw ups across every merchant a residential household engages with frequently, e.g. your bank, your insurer, your wireless carrier, your average retail clothing store, etc.
For more than two full years after my move to a new state, the following things continued to pop up on a monthly basis due to my incorrect customer data:
- In case of my old satellite TV provider they got to me (correct person) but with a misspelled last name at my correct, new address.
- My bank put me in a bit of a pickle as they sent “important tax documentation”, which I did not want to open as my new tenants’ names (in the house I just vacated) was on the letter but with my new home’s address.
- My mortgage lender sends me a refinancing offer to my new address (right person & right address) but with my wife’s as well as my name completely butchered.
- My wife’s airline, where she enjoys the highest level of frequent flyer status, continually mails her offers duplicating her last name as her first name.
- A high-end furniture retailer sends two 100-page glossy catalogs probably costing $80 each to our address – one for me, one for her.
- A national health insurer sends “sensitive health information” (disclosed on envelope) to my new residence’s address but for the prior owner.
- My legacy operator turns on the wrong premium channels on half my set-top boxes.
- The same operator sends me a SMS the next day thanking me for switching to electronic billing as part of my move, which I did not sign up for, followed by payment notices (as I did not get my invoice in the mail). When I called this error out for the next three months by calling their contact center and indicating how much revenue I generate for them across all services, they counter with “sorry, we don’t have access to the wireless account data”, “you will see it change on the next bill cycle” and “you show as paper billing in our system today”.
Ignoring the potential for data privacy law suits, you start wondering how long you have to be a customer and how much money you need to spend with a merchant (and they need to waste) for them to take changes to your data more seriously. And this are not even merchants to whom I am brand new – these guys have known me and taken my money for years!
One thing I nearly forgot…these mailings all happened at least once a month on average, sometimes twice over 2 years. If I do some pigeon math here, I would have estimated the postage and production cost alone to run in the hundreds of dollars.
However, the most egregious trespass though belonged to my home owner’s insurance carrier (HOI), who was also my mortgage broker. They had a double whammy in store for me. First, I received a cancellation notice from the HOI for my old residence indicating they had cancelled my policy as the last payment was not received and that any claims will be denied as a consequence. Then, my new residence’s HOI advised they added my old home’s HOI to my account.
After wondering what I could have possibly done to trigger this, I called all four parties (not three as the mortgage firm did not share data with the insurance broker side – surprise, surprise) to find out what had happened.
It turns out that I had to explain and prove to all of them how one party’s data change during my move erroneously exposed me to liability. It felt like the old days, when seedy telco sales people needed only your name and phone number and associate it with some sort of promotion (back of a raffle card to win a new car), you never took part in, to switch your long distance carrier and present you with a $400 bill the coming month. Yes, that also happened to me…many years ago. Here again, the consumer had to do all the legwork when someone (not an automatic process!) switched some entry without any oversight or review triggering hours of wasted effort on their and my side.
We can argue all day long if these screw ups are due to bad processes or bad data, but in all reality, even processes are triggered from some sort of underlying event, which is something as mundane as a database field’s flag being updated when your last purchase puts you in a new marketing segment.
Now imagine you get married and you wife changes her name. With all these company internal (CRM, Billing, ERP), free public (property tax), commercial (credit bureaus, mailing lists) and social media data sources out there, you would think such everyday changes could get picked up quicker and automatically. If not automatically, then should there not be some sort of trigger to kick off a “governance” process; something along the lines of “email/call the customer if attribute X has changed” or “please log into your account and update your information – we heard you moved”. If American Express was able to detect ten years ago that someone purchased $500 worth of product with your credit card at a gas station or some lingerie website, known for fraudulent activity, why not your bank or insurer, who know even more about you? And yes, that happened to me as well.
Tell me about one of your “data-driven” horror scenarios?
A new year has arrived with many predictions relating to business data. Sounds a lot like last year, eh? The difference in 2014 is that some companies have begun to make real progress in tackling the huge shifts in IT and data management. This year, I believe that MDM will evolve in three key ways to handle the ever-increasing mobility, volume, and sources of data. (more…)
I recently had a lengthy conversation with a business executive of a European telco. His biggest concern was to not only understand the motivations and related characteristics of consumers but to accomplish this insight much faster than before. Given available resources and current priorities this is something unattainable for many operators.
Unlike a few years ago – remember the time before iPad – his organization today is awash with data points from millions of devices, hundreds of device types and many applications.
One way for him to understand consumer motivation; and therefore intentions, is to get a better view of a user’s network and all related interactions and transactions. This includes his family household, friends and business network (also a type of household). The purpose of householding is to capture social and commercial relationships in a grouping of individuals (or businesses or both mixed together) in order to identify patterns (context), which can be exploited to better serve a customer a new individual product or bundle upsell, to push relevant apps, audio and video content.
Let’s add another layer of complexity by understanding not only who a subscriber is, who he knows and how often he interacts with these contacts and the services he has access to via one or more devices but also where he physically is at the moment he interacts. You may also combine this with customer service and (summarized) network performance data to understand who is high-value, high-overhead and/or high in customer experience. Most importantly, you will also be able to assess who will do what next and why.
Some of you may be thinking “Oh gosh, the next NSA program in the making”. Well, it may sound like it but the reality is that this data is out there today, available and interpretable if cleaned up, structured and linked and served in real time. Not only do data quality, ETL, analytical and master data systems provide the data backbone for this reality but process-based systems dealing with the systematic real-time engagement of consumers are the tool to make it actionable. If you add some sort of privacy rules using database or application-level masking technologies, most of us would feel more comfortable about this proposition.
This may feel like a massive project but as many things in IT life; it depends on how you scope it. I am a big fan of incremental mastering of increasingly more attributes of certain customer segments, business units, geographies, where lessons learnt can be replicated over and over to scale. Moreover, I am a big fan of figuring out what you are trying to achieve before even attempting to tackle it.
The beauty behind a “small” data backbone – more about “small data” in a future post – is that if a certain concept does not pan out in terms of effort or result, you have just wasted a small pile of cash instead of the $2 million for a complete throw-away. For example: if you initially decided that the central lynch pin in your household hub & spoke is the person, who owns the most contracts with you rather than the person who pays the bills every month or who has the largest average monthly bill, moving to an alternative perspective does not impact all services, all departments and all clients. Nevertheless, the role of each user in the network must be defined over time to achieve context, i.e. who is a contract signee, who is a payer, who is a user, who is an influencer, who is an employer, etc.
Why is this important to a business? It is because without the knowledge of who consumes, who pays for and who influences the purchase/change of a service/product, how can one create the right offers and target them to the right individual.
However, in order to make this initial call about household definition and scope or look at the options available and sensible, you have to look at social and cultural conventions, what you are trying to accomplish commercially and your current data set’s ability to achieve anything without a massive enrichment program. A couple of years ago, at a Middle Eastern operator, it was very clear that the local patriarchal society dictated that the center of this hub and spoke model was the oldest, non-retired male in the household, as all contracts down to children of cousins would typically run under his name. The goal was to capture extended family relationships more accurately and completely in order to create and sell new family-type bundles for greater market penetration and maximize usage given new bandwidth capacity.
As a parallel track aside from further rollout to other departments, customer segments and geos, you may also want to start thinking like another European operator I engaged a couple of years ago. They were trying to outsource some data validation and enrichment to their subscribers, which allowed for a more accurate and timely capture of changes, often life-style changes (moves, marriages, new job). The operator could then offer new bundles and roaming upsells. As a side effect, it also created a sense of empowerment and engagement in the client base.
I see bits and pieces of some of this being used when I switch on my home communication systems running broadband signal through my X-Box or set-top box into my TV using Netflix and Hulu and gaming. Moreover, a US cable operator actively promotes a “moving” package to help make sure you do not miss a single minute of entertainment when relocating.
Every time now I switch on my TV, I get content suggested to me. If telecommunication services would now be a bit more competitive in the US (an odd thing to say in every respect) and prices would come down to European levels, I would actually take advantage of the offer. And then there is the log-on pop up asking me to subscribe (or throubleshoot) a channel I have already subscribed to. Wonder who or what automated process switched that flag.
Ultimately, there cannot be a good customer experience without understanding customer intentions. I would love to hear stories from other practitioners on what they have seen in such respect
A front office as defined by Wikipedia is “a business term that refers to a company’s departments that come in contact with clients, including the marketing, sales, and service departments” while a back office is “tasks dedicated to running the company….without being seen by customers.” Wikipedia goes on to say that “Back office functions can be outsourced to consultants and contractors, including ones in other countries.” Data Management was once a back office activity but in recent years it has moved to the front office. What changed? (more…)
Gartner Estimates Growth for MDM Market and Positions Informatica as a Leader in The Magic Quadrant for Customer Data Solutions
Over the last few weeks I’ve been saying that the incredible popularity of our MDM-related events is a sign that MDM is a vital and growing market. Now I consider it reassuring that analysts agree. It’s also reassuring to see Informatica positioned as a Leader in the Magic Quadrant for Master Data Management of Customer Data Solutions, a position that Informatica has held for four years in a row.
In Gartner’s October 2013 Magic Quadrant for Master Data Management of Customer Data Solutions, analysts Bill O’Kane and Saul Judah estimates that the total software revenue for packaged MDM solutions was $1.6B in 2012, an increase of 7.8% from 2011, as compared with a 4.7% rise for the overall enterprise software market. Further, O’Kane and Judah estimate that the MDM of customer data solutions market segment was worth $527M in 2012, an increase of 5.4% from 2011. The analysts go on to say that the customer MDM market is far from mature, and that just 40% of the organizations surveyed by Gartner were beginning MDM initiatives.
One of MDM’s most important benefits is a single view of the customer across company departments and siloed systems. In this Magic Quadrant report, the analysts describe some of the business drivers for obtaining this view. For the banking and life sciences sectors, the analysts include “Compliance and risk management drivers, such as ‘know your customer,’ anti-money laundering and counterparty risk management in the banking sector, and Sunshine Act compliance in the life sciences sector.” I believe that many other industries could similarly benefit from trusted customer interactions. Another set of drivers they list are “cost optimization and efficiency drivers,” and finally, “revenue and profitability growth drivers,” explaining that examples of such drivers include “initiatives to improve cross-selling, upselling, and retention.”
Finally, the analysts observed a trend which we believe supports Informatica’s view of the importance of all-encompassing MDM solutions that can manage master data across enterprise. As noted in the report, “Many organizations have now invested in creating a new central system to master their customer data, with the majority (an estimated 80%) of organizations buying packaged MDM of customer data solutions, as opposed to building the capability themselves.”
To learn more about Gartner’s October 2013 Magic Quadrant for Master Data Management of Customer Data Solutions, see our press release or download the full report. After reading the report, please share your thoughts below.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
I was recently boarding a flight in New York and started reading the New York Times. One article jumped out: “User reviews make it harder for marketers to manipulate.” A Stanford University research report proves a wealth of product information and user reviews is causing a fundamental shift in how consumers make decisions.
Consumers rely more on one another
The latest research from Dr. Simonson and Emanual Rosen is based on an experiment performed decades ago at Duke University. In the experiment participants had to choose from a group of either two or three cameras. The research found that consumers chose the cheaper product when being offered two options, but when given three choices, most went with the middle one. It was called the “compromise effect,” which has been used by marketers to impact buying decisions.
But an updated version of the experiment allowed participants to read product ratings and reviews before choosing one of the three cameras. While a portion of the participants always choose the lowest-priced product, in this new scenario more participants are selecting the most expensive product over the middle-priced product based on customer reviews.
“The compromise effect is gone,” says Dr. Simonson in this New York Times article. The Book “Absolute Value” comes with a more in depth explanation: (http://www.absolutevaluebook.com/).
Imagine if you could own and control both customer opinion and product information? The next wave taking omnichannel commerce to the next level will address information relevancy at every channel and all customer interactions – called Commerce Relevancy.