Tag Archives: PIM
“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
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.
Do you know how good your multichannel data is? This blog covers four business objectives when accelerating multi channel commerce and which quality of product data is needed to deliver to that and a summary of questions to ask when establishing your strategy. These questions help ecommerce managers, category managers and marketers at retailers, distributors and brand manufacturers ask the right questions on product and customer data when establishing a multi channel strategy.
The Multichannel Challenge: Availability of Relevant Information
At every customer touch point, the ready availability of product information has a profound effect on buying decisions. If your customers can’t find what they’re shopping for, don’t understand how well your product meets their needs, or aren’t confident in their choice, they won’t complete their purchase.
When customers are researching or actively online shopping for products, research says 40 is the magic number:
40 % of buyers intend to return their purchase at the time they order it.
40 % order multiple versions of a product.
40 % of all fashion product returns are the result of poor product information (Consumer electronics are 15,3%; Sources: Trusted Shops, 2012, Internet World Business 7.1.2013)
All the high-quality product data in the world is useless if an organization cannot leverage that data for quicker time to market, improved e-commerce performance, and greater customer satisfaction.
Four Business Objectives When Accelerating Multi Channel Commerce
This white paper comes with four common use cases that illustrate typical business objectives within a multichannel commerce strategy. When looking into your product information, here is a list of questions you might consider.
1. Increasing conversions and lowering return rates by ensuring that customers can access product information in an easy-to-consume form.
- Where is the flawed content coming from?
- What tools and incentives can we provide for suppliers to maintain the high quality content?
- Which data quality processes should be automated first?
- Do we need a bespoke data model to fit your requirements?
- Can we effectively use industry standards for communicating with suppliers (such as GS1 or eClass)?
2. Lowering manual processing costs by merging the best product content from multiple suppliers.
- How many product catalogs do we have and what are the processes that slow us down?
- Who is responsible for the quality of the product information?
- How can we define and enforce the objective and measurable policies?
- Which supplier has best descriptions / certain translation, high-quality images / video / etc.?
- How do we collaborate with our large and small suppliers to achieve best data quality?
3. Growing margins through “long tail” merchandising of a broader assortment of products.
- Can we automate product classification?
- Which taxonomy will work best for us?
- Do all stakeholders have visibility of data quality metrics and trends?
- How can we leverage information across all channels and customer touch points, not only ecommerce?
4. Increasing customer satisfaction through more consistent information and corporate identity across sales channels.
- How should we connect customer and product information to provide personalized marketing?
- How can we leverage supplier and location data for regional marketing?
- How do we enable crowd sourcing of comments, reviews and user images?
- What information do internal and external users need to access in real time?
Find more information with the complete white paper on multichannel commerce and data quality.
Access to information has always been extremely important to people and organizations. In an increasingly complex and interconnected world, data is an essential competitive advantage for companies. With rapidly growing data volumes, increased complexity, and high market speed, our goal is simple: to easily connect people and data.
Turning data into business outcomes has always been our value proposition at Heiler Software. Using the value of data and information potential is totally in line with the positioning of Informatica. Unleashing the potential of information will help to make the careers of our customers, partners and employees even better.
From beginning of all conversations, from the announcement of the acquisition in October 2012 until today, Informatica’s managers and employees always stuck to the promise they made. That is a great commitment for our employees and customers. Now Informatica has announced the exciting news that the acquisition of Heiler is completed.
Heiler is now a part of the Informatica family. Our entire team is looking forward to the future with Informatica. For Heiler, the door for an exciting and successful future is wide open. Informatica will provide our customers and our employees a promising perspective in a dynamic industry.
Hundreds of customers rely on Informatica’s multi-domain MDM platform to manage customer, location, and asset data, and synchronize accurate master data across operational and analytic systems. I am sure Informatica is committed to being a trusted partner and will work to ensure success with all Heiler’s products.
Heiler has just released PIM 7 to speed up the time to market with all products, across all sales and marketing channels. Also, since March 2013, Procurement 7.1 is available. Informatica is known for innovation. I am convinced that Informatica will continue investing in our business. Their goal is to generate real-time commerce business processes and create a unique customer experience for our customers’ business. Our award winning PIM fits in the Universal MDM strategy to deliver to one vision: Enabling our customers to offer the right product, for the right customer, from the right supplier, at the right time, via the right channels and locations. It is all about inspiring.
Joining the forces will allow our customers to leverage Informatica’s expertise in data quality and data integration to deliver greater business value. With Informatica’s Data Quality offerings, our customers will be able to further accelerate the introduction of your products to market. Additionally, customers will be able to easily onboard data from their suppliers, then distribute to its customers and partners electronically with Informatica B2B. We share a common goal to establish the combination of Informatica MDM and Heiler PIM as the gold standard in the industry.
Another benefit of the acquisition is that all customers will receive world-class support from Informatica’s Global Customer Support organization, which delivers a comprehensive set of support programs including 24×7 support across 10 regional support centers. Customers have ranked Informatica as #1 in customer satisfaction for seven years in a row. In addition, Informatica’s strong global partner ecosystem brings the right resources to solve business and technical challenges across more industries.
By reaching this important milestone my mission as CEO of Heiler Software AG will be fulfilled. Personally, I’m going to stay connected to Informatica and I am excited to get involved in the future of this excellent and innovative company.
The future of Universal MDM is close to my heart.
Rolf J. Heiler, born 1959, married, three children, graduated in 1982 in Business management, majoring in IT and process organization. In 1987, Rolf Heiler founded Heiler Software GmbH. From 2000 Heiler Software was quoted on the stock exchange in 2000 in the “New Market” sector.
I’m at Barcelona this week for the European Gartner MDM Summit. I had a chance to catch up with one of the Gartner MDM analysts before the event, and we had a discussion about the growth of MDM. He mentioned that MDM will become pervasive within the enterprise as organizations expand its use as a necessary foundation for governing all of their business-critical master data such as customers, products, and so on.
To solve their business problems accurately, companies seek targeted MDM solutions. For e.g., retail, distribution, and manufacturing companies use PIM for merchandising, distributing products, and supplier on-boarding, while financial services, healthcare, and high tech companies use customer MDM with their CRM, such as salesforce.com, for improving customer segmentation, cross-sell , and up-sell. (more…)
With the New Year dawning I wanted to look back at some industry trends from the past twelve months, and then look at ahead at what we’re likely to see in 2010. So, this week: recap. Next week: predictions.
“Multidomain MDM” Goes Mainstream
From its inception MDM was meant to be “multidomain” – a solution for multiple data types. This stood in contrast to CDI or PIM, each of which focuses on a single domain. But with CDI morphing into “MDM for Customer Data” and PIM to “MDM for Product Data,” the terminology got a bit muddled. Hence the somewhat redundant “multidomain MDM” came into common usage in 2009 to differentiate it from single-domain MDM. As we saw with the Gartner numbers that I reviewed in my last post, the obvious benefits of managing all domains via a single platform, easier maintenance, and the advantages of leveraging existing investments, are spurring increased adoption. Still, confusion remained over multidomain MDM in the last year, not just with terminology, but also with capabilities. I addressed this in a late November post, but to reiterate: It’s not just about the data model, a true multidomain MDM hub has to be able to model, cleanse, match and relate.
Proactive Data Governance Takes Root
Many IT decision-makers came to the realization in 2009 that reactive data governance is bad because it is not responsive to real-time business needs. Business users increasingly demanded real-time data availability and data stewards worked to put proactive data governance into place to meet these demands. My friend Dan Power covered this topic earlier this year, showing that authoring data directly in an MDM hub enables firms to decouple data entry from traditional CRM and ERP systems, and establish the hub as both the System of Entry and the System of Record.
Taking Aim At The Reference Data Problem
Early on in 2009 we started seeing a lot of customer activity around the “reference data problem” and that interest remained strong through the year. To quickly summarize: certain business processes, order-to-cash for instance, oftentimes use three or more different systems interacting with each other to complete the loop. If their “look-up code” data isn’t standardized (one uses “USA” the second “U.S.” the third “United States”) problems ensue. As a category, reference data is similar to, though distinct from, master data. Yet the similarities are such that effective MDM solutions are perfect for solving the reference data problem. My colleague Manish Sood blogged on this topic in detail here and here.
Be sure to come back next week to see our bold predictions for 2010!
The current hot topic in the MDM space is multidomain master data management. And rightly so, as multidomain MDM has the potential to drive far more value for companies than limited single-domain MDM initiatives (aka CDI, PIM) that focus on a specific class of data such as customer or product.
We’ve heard interesting discussions that multidomain MDM is just about storing the multiple domains within the data model. That is a major misinterpretation. While it’s certainly true that you need to have a data model that’s flexible enough to accommodate multiple data domains (e.g. product, customer, supplier), the data model itself is not the be-all and end-all of multidomain MDM. It’s a requisite starting point, sure, but you need to be able to do so much more. For instance, the ability to match and merge data across various domains is extremely important. Same goes for data cleansing.
Think of it this way: you’re using a dedicated PIM system. It does a great job of matching data fields in ways that are very valuable in addressing problems with product-centric aspects of your business: supply chain, inventory management, etc. Can this system do a good job matching and merging data fields from multiple domains? Can it provide the kind of data cleansing capabilities you’d need if you wanted to incorporate customer data?
A true multidomain MDM hub will provide out-of-the-box capability to:
- model any data domains
- cleanse, correct, standardize, and enrich all types of data
- match the different types of data and merge them into a single source of truth
- relate across the different types data: customer-to-product, vendor-to-material, contact-to-organization, employee-to-location, etc.
To top it all, the data governance application should support the creation, consumption, management, and monitoring of all these types of data.
So to realize the promised value of multidomain MDM, you’ll need a proven multidomain MDM hub and a data governance application that supports all these capabilities.
Critical master data management (MDM) functionality can be easily overlooked when request for proposals (RFP) are narrowly focused on a single business data type—such as customer (Customer Data Integration) or product (Product Information Management) — or on near-term requirements within a single business function. Consequently, IT teams and systems integrators alike run the risk of selecting and investing in technologies that may be difficult to extend to other data types or difficult to scale across the organization. Worse, such solutions will likely require costly custom coding down the road in order to add additional business data entities or to extend the system to other lines of business. These mistakes are easily avoided, but to do so it is important to keep the following ten capabilities in mind as your prepare your RFP. If a prospective vendor can’t answer in the affirmative to all ten questions, keep looking.
Ten Costly RFP Mistakes to Avoid
1. Will we be able to manage multiple business data entities within a single MDM platform?
2. Can the solution support my organization’s unique data governance needs?
3. Will it work with our standard workflow tool?
4. Is the MDM solution capable of supporting complex relationships and hierarchies?
5. Does the system rely on a flexible Service Oriented Architecture (SOA) model that automatically generates changes to the SOA services whenever the data model is updated?
6. Can we cleanse data inside the MDM platform?
7. Does the system allow for probabilistic matching using an assortment of matching techniques, including deterministic, probabilistic, heuristic, phonetic, linguistic, empirical, etc.?
8. Can the system create and maintain a golden record encompassing master data from different sources, which can be reconciled and centrally stored within a master data hub?
9. Is the solution designed to closely track history and lineage in order to support regulatory compliance?
10. Can the solution be implemented for several modes of operation, including analytical and operational?