Tag Archives: customer data integration
Which misstep are you making to solve your customer experience problem?
No one ever said that solving the customer experience problem was going to be easy.
Companies aren’t structured to support complex customer relationships across different functional areas – such as marketing, sales and customer service – nor across their many brands, products, channels and locations. But your customers view every employee conversation, location, ecommerce site, email or communication as a reflection of just one company – yours.
Breaking free of organizational and channel silos to create great customer experiences is difficult even for smart companies. Here are two personal examples.
Last year, I bought a television from a leading online retailer. This retailer sets the industry standard. They make it very easy to buy from them. I belong to their membership program and can purchase anything in one-click. This is a smart company.
But the very next day I received an email from this company with a slew of televisions similar to the one that I had just purchased. The offers were too late and irrelevant, and left me wondering how smart they really are.
Why? Fragmented information and siloed applications. My browsing history and purchase history hadn’t yet been connected. The order fulfillment team knew that I bought something; and yet, the marketing team didn’t. I quickly deleted the email.
Here’s another one: I’ve had a charge card from a global financial services company for nearly 15 years. It’s another very smart company. I never leave home without that card. Three years ago my husband and I were married; and I changed my last name. But, I occasionally receive marketing emails from this company addressed to Monica Smith.
Why? Inconsistency across their systems and out-of-date information. An email marketing system has old information while their charge card system doesn’t. So how do they know which is correct? In their analytics am I counted twice because they have at least two views of me (one of which is 3 years out of date)? I delete those emails also.
We’ve all had these experiences. In the age of engagement, should we still expect them?
Smart companies want to make sure they’re being smart about the way they manage the total customer experience; and for that they need to have a clean, consistent, and connected view of the total customer relationship. Luckily, customers leave data footprints. To be useful, this data needs to be continually managed so that it is up-to-date, accurate, complete, and validated in order to fuel their applications and analytics with trusted customer profiles.
To help understand why it’s not working, we’ve published an ebook on the three missteps that smart companies make to try to fix the customer experience problem (but don’t truly move them closer to being customer-ready). It’s a quick and worthwhile read.
Once you’ve finished, come back here and share your thoughts on how you’ve tried to solve your customer experience problem and become customer-ready (or add a new misstep if we missed one).
This blog post initially appeared on CMSwire.com and is reblogged here with their consent.
Friends of mine were remodeling their master bath. After searching for a claw foot tub in stores and online, they found the perfect one that fit their space. It was only available for purchase on the retailer’s e-commerce site, they bought it online.
When it arrived, the tub was too big. The dimensions online were incorrect. They went to return it to the closest store, but were told they couldn’t — because it was purchased online, they had to ship it back.
The retailer didn’t have a total customer relationship view or a single view of product information or inventory across channels and touch points. This left the customer representative working with a system that was a silo of limited information. She didn’t have access to a rich customer profile. She didn’t know that Joe and his wife spent almost $10,000 with the brand in the last year. She couldn’t see the products they bought online and in stores. Without this information, she couldn’t deliver a great customer experience.
It was a terrible customer experience. My friends share it with everyone who asks about their remodel. They name the retailer when they tell the story. And, they don’t shop there anymore. This terrible customer experience is negatively impacting the retailer’s revenue and brand reputation.
Bad customer experiences happen a lot. Companies in the US lose an estimated $83 billion each year due to defections and abandoned purchases as a direct result of a poor experience, according to a Datamonitor/Ovum report.
Customer Experience is the New Marketing
Gartner believes that by 2016, companies will compete primarily on the customer experiences they deliver. So who should own customer experience?
Twenty-five percent of CMOs say that their CEOs expect them to lead customer experience. What’s their definition of customer experience? “The practice of centralizing customer data in an effort to provide customers with the best possible interactions with every part of the company, from marketing to sales and even finance.”
Mercedes Benz USA President and CEO, Steve Cannon said, “Customer experience is the new marketing.”
The Gap Between Customer Expectations + Your Ability to Deliver
My previous post, 3 Barriers to Delivering Omnichannel Experiences, explained how omnichannel is all about seeing your business through the eyes of your customer. Customers don’t think in terms of channels and touch points, they just expect a seamless, integrated and consistent customer experience. It’s one brand to the customer. But there’s a gap between customer expectations and what most businesses can deliver today.
Most companies who sell through multiple channels operate in silos. They are channel-centric rather than customer-centric. This business model doesn’t empower employees to deliver seamless, integrated and consistent customer experiences across channels and touch points. Different leaders manage each channel and are held accountable to their own P&L. In most cases, there’s no incentive for leaders to collaborate.
Old Navy’s CMO, Ivan Wicksteed got it right when he said,
“Seventy percent of searches for Old Navy are on a mobile device. Consumers look at the product online and often want to touch it in the store. The end goal is not to get them to buy in the store. The end goal is to get them to buy.”
The end goal is what incentives should be based on.
Executives at most organizations I’ve spoken with admit they are at the very beginning stages of their journey to becoming omnichannel retailers. They recognize that empowering employees with a total customer relationship view and a single view of product information and inventory across channels are critical success factors.
Becoming an omnichannel business is not an easy transition. It forces executives to rethink their definition of customer-centricity and whether their business model supports it. “Now that we need to deliver seamless, integrated and consistent customer experiences across channels and touch points, we realized we’re not as customer-centric as we thought we were,” admitted an SVP of marketing at a financial services company.
You Have to Transform Your Business
“We’re going through a transformation to empower our employees to deliver great customer experiences at every stage of the customer journey,” said Chris Brogan, SVP of Strategy and Analytics at Hyatt Hotels & Resorts. “Our competitive differentiation comes from knowing our customers better than our competitors. We manage our customer data like a strategic asset so we can use that information to serve customers better and build loyalty for our brand.”
Hyatt uses data integration, data quality and master data management (MDM) technology to connect the numerous applications that contain fragmented customer data including sales, marketing, e-commerce, customer service and finance. It brings the core customer profiles together into a single, trusted location, where they are continually managed. Now its customer profiles are clean, de-duplicated, enriched and validated. Members of a household as well as the connections between corporate hierarchies are now visible. Business and analytics applications are fueled with this clean, consistent and connected information so customer-facing teams can do their jobs more effectively.
When he first joined Hyatt, Brogan did a search for his name in the central customer database and found 13 different versions of himself. This included the single Chris Brogan who lived across the street from Wrigley Field with his buddies in his 20s and the Chris Brogan who lives in the suburbs with his wife and two children. “I can guarantee those two guys want something very different from a hotel stay,” he joked. Those guest profiles have now been successfully consolidated.
According to Brogan,
“Successful marketing, sales and customer experience initiatives need to be built on a solid customer data foundation. It’s much harder to execute effectively and continually improve if your customer data is a mess.”
Improving How You Manage, Use and Analyze Data is More Important Than Ever
Some companies lack a single view of product information across channels and touch points. About 60 percent of retail managers believe that shoppers are better connected to product information than in-store associates. That’s a problem. The same challenges exist for product information as customer information. How many different systems contain valuable product information?
Harrods overcame this challenge. The retailer has a strategic initiative to transform from a single iconic store to an omnichannel business. In the past, Harrods’ merchants managed information for about 500,000 products for the store point of sale system and a few catalogs. Now they are using product information management technology (PIM) to effectively manage and merchandise 1.7 million products in the store and online.
Because they are managing product information centrally, they can fuel the ERP system and e-commerce platform with full, searchable multimedia product information. Harrods has also reduced the time it takes to introduce new products and generate revenue from them. In less than one hour, buyers complete the process from sourcing to market readiness.
It Ends with Satisfied Customers
By 2016, you will need to be ready to compete primarily on the customer experiences you deliver across channels and touch points. This means really knowing who your customers are so you can serve them better. Many businesses will transform from a channel-centric business model to a truly customer-centric business model. They will no longer tolerate messy data. They will recognize the importance of arming marketing, sales, e-commerce and customer service teams with the clean, consistent and connected customer, product and inventory information they need to deliver seamless, integrated and consistent experiences across touch points. And all of us will be more satisfied customers.
A friend of mine recently reached out to me about some advice on CRM solutions in the market. Though I have not worked for a CRM vendor, I’ve had both direct experience working for companies that implemented such solutions to my current role interacting with large and small organizations regarding their data requirements to support ongoing application investments across industries. As we spoke, memories started to surface when he and I had worked on implementing Salesforce.com (SFDC) many years ago. Memories that we wanted to forget but important to call out given his new situation.
We worked together for a large mortgage lending software vendor selling loan origination solutions to brokers and small lenders mainly through email and snail mail based marketing. He was responsible for Marketing Operations, and I ran Product Marketing. The company looked at Salesforce.com to help streamline our sales operations and improve how we marketed and serviced our customers. The existing CRM system was from the early 90’s and though it did what the company needed it to do, it was heavily customized, costly to operate, and served its life. It was time to upgrade, to help grow the business, improve business productivity, and enhance customer relationships.
After 90 days of rolling out SFDC, we ran into some old familiar problems across the business. Sales reps continued to struggle in knowing who was a current customer using our software, marketing managers could not create quality mailing lists for prospecting purposes, and call center reps were not able to tell if the person on the other end was a customer or prospect. Everyone wondered why this was happening given we adopted the best CRM solution in the market. You can imagine the heartburn and ulcers we all had after making such a huge investment in our new CRM solution. C-Level executives were questioning our decisions and blaming the applications. The truth was, the issues were not related to SFDC but the data that we had migrated into the system and the lack proper governance and a capable information architecture to support the required data management integration between systems that caused these significant headaches.
During the implementation phase, IT imported our entire customer database of 200K+ unique customer entities from the old system to SFDC. Unfortunately, the mortgage industry was very transient and on average there were roughly 55K licenses mortgage brokers and lenders in the market and because no one ever validated the accuracy of who was really a customer vs. someone who had ever bought out product, we had a serious data quality issues including:
- Trial users who purchased evaluation copies of our products that expired were tagged as current customers
- Duplicate records caused by manual data entry errors consisting of companies with similar but entered slightly differently with the same business address were tagged as unique customers
- Subsidiaries of parent companies in different parts of the country that were tagged again as a unique customer.
- Lastly, we imported the marketing contact database of prospects which were incorrectly accounted for as a customer in the new system
We also failed to integrate real-time purchasing data and information from our procurement systems for sales and support to handle customer requests. Instead of integrating that data in real-time with proper technology, IT had manually loaded these records at the end of the week via FTP resulting in incorrect billing information, statement processing, and a ton of complaints from customers through our call center. The price we paid for not paying attention to our data quality and integration requirements before we rolled out Salesforce.com was significant for a company of our size. For example:
- Marketing got hit pretty hard. Each quarter we mailed evaluation copies of new products to our customer database of 200K, each costing the company $12 per to produce and mail. Total cost = $2.4M annually. Because we had such bad data, we would get 60% of our mailings returned because of invalid addresses or wrong contact information. The cost of bad data to marketing = $1.44M annually.
- Next, Sales struggled miserably when trying to upgrade a customer by running cold call campaigns using the names in the database. As a result, sales productivity dropped by 40% and experienced over 35% sales turnover that year. Within a year of using SFDC, our head of sales got let go. Not good!
- Customer support used SFDC to service customers, our average all times were 40 min per service ticket. We had believed that was “business as usual” until we surveyed what reps were spending their time each day and over 50% said it was dealing with billing issues caused by bad contact information in the CRM system.
At the end of our conversation, this was my advice to my friend:
- Conduct a data quality audit of the systems that would interact with the CRM system. Audit how complete your critical master and reference data is including names, addresses, customer ID, etc.
- Do this before you invest in a new CRM system. You may find that much of the challenges faced with your existing applications may be caused by the data gaps vs. the legacy application.
- If they had a data governance program, involve them in the CRM initiative to ensure they understand what your requirements are and see how they can help.
- However, if you do decide to modernize, collaborate and involve your IT teams, especially between your Application Development teams and your Enterprise Architects to ensure all of the best options are considered to handle your data sharing and migration needs.
- Lastly, consult with your technology partners including your new CRM vendor, they may be working with solution providers to help address these data issues as you are probably not the only one in this situation.
CRM systems have come a long way in today’s Big Data and Cloud Era. Many firms are adopting more flexible solutions offered through the Cloud like Salesforce.com, Microsoft Dynamics, and others. Regardless of how old or new, on premise or in the cloud, companies invest in CRM not to just serve their sales teams or increase marketing conversion rates, but to improve your business relationship with your customers. Period! It’s about ensuring you have data in these systems that is trustworthy, complete, up to date, and actionable to improve customer service and help drive sales of new products and services to increase wallet share. So how to do you maximize your business potential from these critical business applications?
Whether you are adopting your first CRM solution or upgrading an existing one, keep in mind that Customer Relationship Management is a business strategy, not just a software purchase. It’s also about having a sound and capable data management and governance strategy supported by people, processes, and technology to ensure you can:
- Access and migrate data from old to new avoiding develop cost overruns and project delays.
- Identify, detect, and distribute transactional and reference data from existing systems into your front line business application in real-time!
- Manage data quality errors including duplicate records, invalid names and contact information due to proper data governance and proactive data quality monitoring and measurement during and after deployment
- Govern and share authoritative master records of customer, contact, product, and other master data between systems in a trusted manner.
Will your data be ready for your new CRM investments? To learn more:
- Download Salesforce Integration for Dummies
- Download a new Whitepaper on how to Maximize Integration ROI with a Hybrid Approach
- Consolidating Multiple Salesforce Orgs: A Best Practice Guide
- Sign up for a 30 Day Trial of Informatica Cloud Integration
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According to Accenture – 2013 Global Consumer Pulse Survey, “85 percent of customers are frustrated by dealing with a company that does not make it easy to do business with them, 84 percent by companies promising one thing, but delivering another; and 58 percent are frustrated with inconsistent experiences from channel to channel.”
Consumers expect more from the companies they do business with. In response, many companies are shifting from managing their business based on an application-, account- or product-centric approach to a customer-centric approach. And this is one of the main drivers for master data management (MDM) adoption. According to a VP of Data Strategy & Services at one of the largest insurance companies in the world, “Customer data is the lifeblood of a company that is serious about customer-centricity.” So, better managing customer data, which is what MDM enables you to do, is a key to the success of any customer-centricity initiative. MDM provides a significant competitive differentiation opportunity for any organization that’s serious about improving customer experience. It enables customer-facing teams to assess the value of any customer, at the individual, household or organization level.
Amongst the myriad business drivers of a customer-centricity initiative, key benefits include delivering an enhanced customer experience – leading to higher customer loyalty and greater share of wallet, more effective cross-sell and upsell targeting to increase revenue, and improved regulatory compliance.
To truly achieve all the benefits expected from a customer-first, customer-centric strategy, we need to look beyond the traditional approaches of data quality and MDM implementations, which often consider only one foundational (yet important) aspect of the technology solution. The primary focus has always been to consolidate and reconcile internal sources of customer data with the hope that this information brought under a single umbrella of a database and a service layer will provide the desired single view of customer. But in reality, this data integration mindset misses the goal of creating quality customer data that is free from duplication and enriched to deliver significant value to the business.
Today’s MDM implementations need to take their focus beyond mere data integration to be successful. In the following section, I will explain 3 levels of customer views which can be built incrementally to be able to make most out of your MDM solution. When implemented fully, these customer views act as key ingredients for improving the execution of your customer-centric business functions.
Trusted Customer View
The first phase of the solution should cover creation of trusted customer view. This view empowers your organization with an ability to see complete, accurate and consistent customer information.
In this stage, you take the best information from all the applications and compile it into a single golden profile. You not only use data integration technology for this, but also employ data quality tools to ensure the correctness and completeness of the customer data. Advanced matching, merging and trust framework are used to derive the most up-to-date information about your customer. You also guarantee that the golden record you create is accessible to business applications and systems of choice so everyone who has the authority can leverage the single version of the truth.
At the end of this stage, you will be able to clearly say John D. who lives at 123 Main St and Johnny Doe at 123 Main Street, who are both doing business with you, are not really two different individuals.
Customer Relationships View
The next level of visibility is about providing a view into the customer’s relationships. It takes advantage of the single customer view and layers in all valuable family and business relationships as well as account and product information. Revealing these relationships is where the real value of multidomain MDM technology comes into action.
At the end of this phase, you not only see John Doe’s golden profile, but the products he has. He might have a personal checking from the Retail Bank, a mortgage from the Mortgage line of business, and brokerage and trust account with the Wealth Management division. You can see that John has his own consulting firm. You can see he has a corporate credit card and checking account with the Commercial division under the name John Doe Consulting Company.
At the end of this phase, you will have a consolidated view of all important relationship information that will help you evaluate the true value of each customer to your organization.
Customer Interactions and Transactions View
The third level of visibility is in the form of your customer’s interactions and transactions with your organization.
During this phase, you tie transactional information, historical data and social interactions your customer has with your organization to further enhance the system. Building this view provides you a whole new world of opportunities because you can see everything related to your customer in one central place. Once you have this comprehensive view, when John Doe calls your call center, you know how valuable he is to your business, which product he just bought from you (transactional data), what is the problem he is facing (social interactions).
A widely accepted rule of thumb holds that 80 percent of your company’s future revenue will come from 20 percent of your existing customers. Many organizations are trying to ensure they are doing everything they can to retain existing customers and grow wallet share. Starting with Trusted Customer View is first step towards making your existing customers stay. Once you have established all three states discussed here, you can arm your customer-facing teams with a comprehensive view of customers so they can:
- Deliver the best customer experiences possible at every touch point,
- Improve customer segmentation for tailored offers, boost marketing and sales productivity,
- Increase cross-sell and up-sell success, and
- Streamline regulatory reporting.
Achieving the 3 views discussed here requires a solid data management platform. You not only need an industry leading multidomain MDM technology, but also require tools which will help you integrate data, control the quality and connect all the dots. These technologies should work together seamlessly to make your implementation easier and help you gain rapid benefits. Therefore, choose your data management platform. To know more about MDM vendors, read recently released Gartner’s Magic Quadrant for MDM of Customer Data Solutions.
Bad data is bad for business. Ovum Research reported that poor quality data is costing businesses at least 30% of revenues. Never before have business leaders across a broad range of roles recognized the importance of using high quality information to drive business success. Leaders in functions ranging from marketing and sales to risk management and compliance have invested in world-class applications, six sigma processes, and the most advanced predictive analytics. So why are you not seeing more return on that investment? Simply put, if your business-critical data is a mess, the rest doesn’t matter.
Not all business leaders know there’s a better way to manage their business-critical data. So, I asked Dennis Moore, the senior vice president and general manager of Informatica’s MDM business, who clocked hundreds of thousands of airline miles last year visiting business leaders around the world, to talk about the impact of using accurate, consistent and connected data and the value business leaders can gain through master data management (MDM).
Q. Why are business leaders focusing on business-critical data now?
A. Leaders have always cared about their business-critical data, the master data on which their enterprises depend most — their customers, suppliers, the products they sell, the locations where they do business, the assets they manage, the employees who make the business perform. Leaders see the value of having a clear picture, or “best version of the truth,” describing these “master data” entities. But, this is hard to come by with competing priorities, mergers and acquisitions and siloed systems.
As companies grow, business leaders start realizing there is a huge gap between what they do know and what they should know about their customers, suppliers, products, assets and employees. Even worse, most businesses have lost their ability to understand the relationships between business-critical data so they can improve business outcomes. Line of business leaders have been asking questions such as:
- How can we optimize sales across channels when we don’t know which customers bought which products from which stores, sites or suppliers?
- How can we quickly execute a recall when we don’t know which supplier delivered a defective part to which factory and where those products are now?
- How can we accelerate time-to-market for a new drug, when we don’t know which researcher at which site used which combination of compounds on which patients?
- How can we meet regulatory reporting deadlines, when we don’t know which model of a product we manufactured in which lot on which date?
Q. What is the crux of the problem?
A. The crux of the problem is that as businesses grow, their business-critical data becomes fragmented. There is no big picture because it’s scattered across applications, including on premise applications (such as SAP, Oracle and PeopleSoft) and cloud applications (such as Salesforce, Marketo, and Workday). But it gets worse. Business-critical data changes all the time. For example,
- a customer moves, changes jobs, gets married, or changes their purchasing habits;
- a suppliers moves, goes bankrupt or acquires a competitor;
- you discontinue a product or launch a new one; or
- you onboard a new asset or retire an old one.
As all this change occurs, business-critical data becomes inconsistent, and no one knows which application has the most up-to-date information. This costs companies money. It saps productivity and forces people to do a lot of manual work outside their best-in-class processes and world-class applications. One question I always ask business leaders is, “Do you know how much bad data is costing your business?”
Q. What can business leaders do to deal with this issue?
A. First, find out where bad data is having the most significant impact on the business. It’s not hard – just about any employee can share stories of how bad data led to a lost sale, an extra “truck roll,” lost leverage with suppliers, or a customer service problem. From the call center to the annual board planning meeting, bad data results in sub-optimal decisions and lost opportunities. Work with your line of business partners to reach a common understanding of where an improvement can really make a difference. Bad master data is everywhere, but bad master data that has material costs to the business is a much more pressing and constrained problem. Don’t try to boil the ocean or bring a full-blown data governance maturity level 5 approach to your organization if it’s not already seeing success from better data!
Second, focus on the applications and processes used to create, share, and use master data. Many times, some training, a tweak to a process, or a new interface can be created between systems, resulting in very significant improvements for the users without major IT work or process changes.
Lastly, look for a technology that is purpose-built to deal with this problem. Master data management (MDM) helps companies better manage business-critical data in a central location on an ongoing basis and then share that “best version of the truth” with all on premise and cloud applications that need it.
Let’s use customer data as an example. If valuable customer data is located in applications such as Salesforce, Marketo, Seibel CRM, and SAP, MDM brings together all the business-critical data, the core that’s the same across all those applications, and creates the “best version of the truth.” It also creates the total customer relationship view across functions, product lines and regions, which CRM promised but never delivered.
MDM then shares that “mastered” customer data and the total customer relationship view with the applications that want it. MDM can be used to master the relationships between customers, such as legal entity hierarchies. This helps sales and customer service staff be more productive, while also improving legal compliance and management decision making. Advanced MDM products can also manage relationships across different types of master data. For example, advanced MDM enables you to relate an employee to a project to a contract to an asset to a commission plan. This ensures accurate and timely billing, effective expense management, managed supplier spend, and even improved workforce deployment.
When your sales team has the best possible customer information in Salesforce and the finance team has the best possible customer information in SAP, no one wastes time pulling together spreadsheets of information outside of their world-class applications. Your global workforce doesn’t waste time trying to investigate whether Jacqueline Geiger in one system and Jakki Geiger in another system is one or two customers, sending multiple bills and marketing offers at high cost in postage and customer satisfaction. All employees who have access to mastered customer information can be confident they have the best possible customer information available across the organization to do their jobs. And with the most advanced and intelligent data platform, all this information can be secured so only the authorized employees, partners, and systems have access.
Q. Which industries stand to gain the most from mastering their data?
A. In every industry there is some transformation going on that’s driving the need to know people, places and things better. Take insurance for example. Similar to the transformation in the travel industry that reduced the need for travel agents, the insurance industry is experiencing a shift from the agent/broker model to a more direct model. Traditional insurance companies now have an urgent need to know their customers so they can better serve them across all channels and across multiple lines of business.
In other industries, there is an urgent need to get a lot better at supply-chain management or to accelerate new product introductions to compete better with an emerging rival. Business leaders are starting to make the connection between transformation failures and a more critical need for the best possible data, particularly in industries undergoing rapid transformation, or with rapidly changing regulatory requirements.
Q. Which business functions seem most interested in mastering their business-critical data?
A. It varies by industry, but there are three common threads that seem to span most industries:
- MDM can help the marketing team optimize the cross-sell and up-sell process with high quality data about customers, their households or company hierarchies, the products and services they have purchased through various channels, and the interactions their organizations have had with these customers.
- MDM can help the procurement team optimize strategic sourcing including supplier spend management and supplier risk management with high quality data about suppliers, company hierarchies, contracts and the products they supply.
- MDM can help the compliance teams manage all the business-critical data they need to create regulatory reports on time without burning the midnight oil.
Q. How is the use of MDM evolving?
A. When MDM technology was first introduced a decade ago, it was used as a filter. It cleaned up business-critical data on its way to the data warehouse so you’d have clean, consistent, and connected information (“conformed dimensions”) for reporting. Now business leaders are investing in MDM technology to ensure that all of their global employees have access to high quality business-critical data across all applications. They believe high quality data is mission-critical to their operations. High quality data is viewed as the the lifeblood of the company and will enable the next frontier of innovation.
Second, many companies mastered data in only one or two domains (customer and product), and used separate MDM systems for each. One system was dedicated to mastering customer data. You may recall the term Customer Data Integration (CDI). Another system was dedicated to mastering product data. Because the two systems were in silos and business-critical data about customers and products wasn’t connected, they delivered limited business value. Since that time, business leaders have questioned this approach because business problems don’t contain themselves to one type of data, such as customer or product, and many of the benefits of mastering data come from mastering other domains including supplier, chart of accounts, employee and other master or reference data shared across systems.
The relationships between data matter to the business. Knowing what customer bought from which store or site is more valuable than just knowing your customer. The business insights you can gain from these relationships is limitless. Over 90% of our customers last year bought MDM because they wanted to master multiple types of data. Our customers value having all types of business-critical data in one system to deliver clean, consistent and connected data to their applications to fuel business success.
One last evolution we’re seeing a lot involves the types and numbers of systems connecting to the master data management system. In the past, there were a small number of operational systems pushing data through the MDM system into a data warehouse used for analytical purposes. Today, we have customers with hundreds of operational systems communicating with each other via an MDM system that has just a few milliseconds to respond, and which must maintain the highest levels of availability and reliability of any system in the enterprise. For example, one major retailer manages all customer information in the MDM system, using the master data to drive real-time recommendations as well as a level of customer service in every interaction that remains the envy of their industry.
Q. Dennis, why should business leaders consider attending MDM Day?
A. Business leaders should consider attending MDM Day at InformaticaWorld 2014 on Monday, May 12, 2014. You can hear first-hand the business value companies are gaining by using clean, consistent and connected information in their operations. We’re excited to have fantastic customers who are willing to share their stories and lessons learned. We have presenters from St. Jude Medical, Citrix, Quintiles and Crestline Geiger and panelists from Thomson Reuters, Accenture, EMC, Jones Lang Lasalle, Wipro, Deloitte, AutoTrader Group, McAfee-Intel, Abbvie, Infoverity, Capgemini, and Informatica among others.
Last year’s Las Vegas event, and the events we held in London, New York and Sao Paolo were extremely well received. This year’s event is packed with even more customer sessions and opportunities to learn and to influence our product road map. MDM Day is one day before InformaticaWorld and is included in the cost of your InformaticaWorld registration. We’d love to see you there!
See the MDM Day Agenda.
SaaS companies are growing rapidly and becoming the top priority for most CIOs. With such high growth expectations, many SaaS vendors are investing in sales and marketing to acquire new customers even if it means having a negative net profit margin as a result. Moreover, with the pressure to grow rapidly, there is an increased urgency to ensure that the Average Sales Price (ASP) of every transaction increases in order to meet revenue targets.
The nature of the cloud allows these SaaS companies to release new features every few months, which sales reps can then promote to new customers. When new functionalities are not used nor understood, customers often feel that they have overpaid for a SaaS product. In such cases, customers usually downgrade to a lower-priced edition or worse, leave the vendor entirely. To make up for this loss, the sales representatives must work harder to acquire new leads, which results in less attention for existing customers. Preventing customer churn is very important. The Cost to Acquire a Customer (CAC) for upsells is 19% of the CAC to acquire new customer dollars. In comparison, the CAC to renew existing customers is only 15% of the CAC to acquire new customer dollars.
Accurate customer usage data helps determine which features customers use and which are under utilized. Gathering this data can help pinpoint high-value features that are not used, especially for customers that have recently upgraded to a higher edition. The process of collecting this data involves several touch points – from recording clicks within the app to analyzing the open rate of entire modules. This is where embedded cloud integration comes into play.
Embedding integration within a SaaS application allows vendors to gain operational insights into each aspect of how their app is being used. With this data, vendors are able to provide feedback to product management in regards to further improvements. Additionally, embedding integration can alert the customer success management team of potential churn, thereby allowing them to implement preventative measures.
To learn more about how a specialized analytics environment can be set up for SaaS apps, join Informatica and Gainsight on April 9th at 10am PDT for an informational webinar Powering Customer Analytics with Embedded Cloud Integration.
When I was seven years old, Danny Weiss had a birthday party where we played the telephone game. The idea is this: there are 8 people sitting around a table, the first person tells the next person a little story. They tell the next person, the story, and so on, all the way around the room. At the end of the game, you compare the original story that the first person tells and compare it to the story the 8th person tells. Of course, the stories are very different and everyone giggles hysterically… we were seven years old after all.
The reason I was thinking about this story is that data integration development is similarly inefficient as a seven year old birthday party. The typical process is that a business analyst, using the knowledge in their head about the business applications they are responsible for, creates a spreadsheet in Microsoft Excel that has a list of database tables and columns along with a set of business rules for how the data is to be transformed as it moved to a target system (a data warehouse or another application). The spreadsheet, which is never checked against real data, is then passed to a developer who then creates code in separate system in order to move the data, which is then checked by a QA person which is then checked again by the business analyst at the end of the process. This is the first time the business analyst verifies their specification against real data.
99 times out of 100, the data in the target system doesn’t match what the business analyst was expecting. Why? Either the original specification was wrong because the business analyst had a typo or the data is inaccurate. Or the data in the original system wasn’t organized the way the analyst thought it was organized. Or the developer misinterpreted the spreadsheet. Or the business analyst simply doesn’t need this data anymore – he needs some other data. The result is lots of errors, just like the telephone game. And the only way to fix it is with rework and then more rework.
But there is a better way. What if the data analyst could validate their specification against real data and self correct on the fly before passing the specification to the developer. What if the specification were not just a specification, but a prototype that could be passed directly to the developer who wouldn’t recode it, but would just modify it to add scalability and reliability? The result is much less rework and much faster time to development. In fact, up to 5 times faster.
That is what Agile Data integration is all about. Rapid prototyping and self-validation against real data up front by the business analyst. Sharing of results in a common toolset back and forth to the developer to improve the accuracy of communication.
Because we believe the agile process is so important to your success, Informatica is giving all of our PowerCenter Standard Edition (and higher editions) customers agile data integration for FREE!!! That’s right, if you are a current customer of Informatica PowerCenter, we are giving you the tools you need to go from the old fashion error-prone, waterfall, telephone game style of development to a modern 21st century Agile process.
• FREE rapid prototyping and data profiling for the data analyst.
• Go from prototype to production with no recoding.
• Better communication and better collaboration between analyst and developer
PowerCenter 9.6. Agile Data Integration built in. No more telephone game. It doesn’t get any better than that.
In a previous blog post, I wrote about when business “history” is reported via Business Intelligence (BI) systems, it’s usually too late to make a real difference. In this post, I’m going to talk about how business history becomes much more useful when combined operationally and in real time.
E. P. Thompson, a historian pointed out that all history is the history of unintended consequences. His idea / theory was that history is not always recorded in documents, but instead is ultimately derived from examining cultural meanings as well as the structures of society through hermeneutics (interpretation of texts) semiotics and in many forms and signs of the times, and concludes that history is created by people’s subjectivity and therefore is ultimately represented as they REALLY live.
The same can be extrapolated for businesses. However, the BI systems of today only capture a miniscule piece of the larger pie of knowledge representation that may be gained from things like meetings, videos, sales calls, anecdotal win / loss reports, shadow IT projects, 10Ks and Qs, even company blog posts 😉 – the point is; how can you better capture the essence of meaning and perhaps importance out of the everyday non-database events taking place in your company and its activities – in other words, how it REALLY operates.
One of the keys to figuring out how businesses really operate is identifying and utilizing those undocumented RULES that are usually underlying every business. Select company employees, often veterans, know these rules intuitively. If you watch them, and every company has them, they just have a knack for getting projects pushed through the system, or making customers happy, or diagnosing a problem in a short time and with little fanfare. They just know how things work and what needs to be done.
These rules have been, and still are difficult to quantify and apply or “Data-ify” if you will. Certain companies (and hopefully Informatica) will end up being major players in the race to datify these non-traditional rules and events, in addition to helping companies make sense out of big data in a whole new way. But in daydreaming about it, it’s not hard to imagine business systems that will eventually be able to understand the optimization rules of a business, accounting for possible unintended scenarios or consequences, and then apply them in the time when they are most needed. Anyhow, that’s the goal of a new generation of Operational Intelligence systems.
In my final post on the subject, I’ll explain how it works and business problems it solves (in a nutshell). And if I’ve managed to pique your curiosity and you want to hear about Operational Intelligence sooner, tune in to to a webinar we’re having TODAY at 10 AM PST. Here’s the link.
Unlike some of my friends, History was a subject in high school and college that I truly enjoyed. I particularly appreciated biographies of favorite historical figures because it painted a human face and gave meaning and color to the past. I also vowed at that time to navigate my life and future under the principle attributed to Harvard professor Jorge Agustín Nicolás Ruiz de Santayana y Borrás that goes, “Those who cannot remember the past are condemned to repeat it.”
So that’s a little ditty regarding my history regarding history.
Forwarding now to the present in which I have carved out my career in technology, and in particular, enterprise software, I’m afforded a great platform where I talk to lots of IT and business leaders. When I do, I usually ask them, “How are you implementing advanced projects that help the business become more agile or effective or opportunistically proactive?” They usually answer something along the lines of “this is the age and renaissance of data science and analytics” and then end up talking exclusively about their meat and potatoes business intelligence software projects and how 300 reports now run their business.
Then when I probe and hear their answer more in depth, I am once again reminded of THE history quote and think to myself there’s an amusing irony at play here. When I think about the Business Intelligence systems of today, most are designed to “remember” and report on the historical past through large data warehouses of a gazillion transactions, along with basic, but numerous shipping and billing histories and maybe assorted support records.
But when it comes right down to it, business intelligence “history” is still just that. Nothing is really learned and applied right when and where it counted – AND when it would have made all the difference had the company been able to react in time.
So, in essence, by using standalone BI systems as they are designed today, companies are indeed condemned to repeat what they have already learned because they are too late – so the same mistakes will be repeated again and again.
This means the challenge for BI is to reduce latency, measure the pertinent data / sensors / events, and get scalable – extremely scalable and flexible enough to handle the volume and variety of the forthcoming data onslaught.
There’s a part 2 to this story so keep an eye out for my next blog post History Repeats Itself (Part 2)
Everyone knows that Informatica is the Data Integration company that helps organizations connect their disparate software into a cohesive and synchronous enterprise information system. The value to business is enormous and well documented in the form of use cases, ROI studies and loyalty / renewal rates that are industry-leading.
Event Processing, on the other hand is a technology that has been around only for a few years now and has yet to reach Main Street in Systems City, IT. But if you look at how event processing is being used, it’s amazing that more people haven’t heard about it. The idea at its core (pun intended) is very simple – monitor your data / events – those things that happen on a daily, hourly, minute-ly basis and then look for important patterns that are positive or negative indicators, and then set up your systems to automatically take action when those patterns come up – like notify a sales rep when a pattern indicates a customer is ready to buy, or stop that transaction, your company is about to be defrauded.
Since this is an Informatica blog, then you probably have a decent set of “muscles” in place already and so why, you ask, would you need 6 pack abs? Because 6 packs abs are a good indication of a strong musculature core and are the basis of a stable and highly athletic body. It’s the same parallel for companies because in today’s competitive business environment, you need strength, stability, and agility to compete. And since IT systems increasingly ARE the business, if your company isn’t performing as strong, lean, and mean as possible, then you can be sure your competitors will be looking to implement every advantage they can.
You may also be thinking why would you need something like Event Processing when you already have good Business Intelligence systems in place? The reality is that it’s not easy to monitor and measure useful but sometimes hidden data /event / sensor / social media sources and also to discern which patterns have meaning and which patterns may be discovered as false negatives. But the real difference is that BI usually reports to you after the fact when the value of acting on the situation has diminished significantly.
So while muscles are important to be able to stand up and run, and good quality, strong muscles are necessary to do heavy lifting, it’s those 6 pack abs on top of it all that give you the mean lean fighting machine to identify significant threats and opportunities amongst your data, and in essence, to better compete and win.