Data Quality and Business Outcome

take-2The connection between MDM (Master Data Management) and business outcome was discussed on this blog in the previous post called MDM, Reltio, Gartner and Business Outcome.

Now, MDM and Data Quality are closely connected disciplines. So, it was interesting to read today’s post on the Experian Data Quality UK blog, where James Marrable states this: Want to improve performance? Improve your data.

In his section around improving data James, among other things, suggests asking this question: “Do you have other data sources you can bring in to support the data you have?”

This is a key question to me and in my eyes a very important mean to make your data bring business outcome. Applying second party and third party data can increase the potential value of your first party data in these ways:

  • Utilizing third party data to compile complete, accurate and timely party data assets needed for understanding and connecting with customers.
  • Receive second party data to compile complete, accurate and timely product information.
  • Having a holistic view of internal and external data needed for decision making.

Hereby you will sell more, reduce costs and mitigate risks.

Merchants vs Manufacturers in the Information Age

Merchants sells the goods produced by manufacturers. In that game merchants and manufacturers are basically allies. Then of course the merchant’s profit may depend on the margin he can get between the manufacturers price to him and the merchant’s price to his customer. In that game, merchants and manufacturers are kind of enemies.

When it comes to providing product information to the end customers, merchants and manufacturers are allies too. The more complete product information placed in front of the end customer, the better. This is increasingly important today with more and more goods sold in self-service scenarios as in ecommerce.

standoffBut again, there seems to be an enemy angle here too. Who should have the burden of lifting product information as the manufacturers have it to the way it is presented at the point-of-sales provided by the merchant? Often this seems to be stalled in a standoff as described in the post Passive vs Active Product Information Exchange.

At Product Data Lake we offer merchants and manufacturers an honorable way out of this standoff:

Mantra for Retailers: Streamline Product Information to Delight Customers

In his third guest blog post here on this blog Rajneesh Kumar of Pimcore examines how this in-house PIM solution facilitates the way sales teams, online marketers, logistics departments and other units can work in perfect unison.

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Managing retail is a complex business. It starts with keeping all the attributes of your product information consistent across all platforms. That’s because your customers are everywhere today. They check out your products online and in store. They express themselves on chat boxes, send emails asking straight questions, buy using desktops/tablets/mobiles, call customer care and use all the devices at their disposal interchangeably in doing so.

Ergo, your product information should better be accurate, high-quality, comprehensive, consistent and up-to-the-minute at all times, across all platforms. As your business expands, number of products increase, the chances of botching up only get higher.

In this sea of complexity, one of the key differentiators in your growth story can be the PIM solution you implement. Pimcore’s PIM can be an answer to your retail needs, here’s why:

Retailers’ Needs Answered with Ease:

In today’s changing consumer dynamics, where 72% of businesses have named improving customer experience as their top priority, a robust product information management system is vital for retailers.

It’s no secret that retailers are grappling with the ever-changing product information requirements. They know it very well their customers are deluged with choices. If they don’t give their customers a consistent experience across all digital touch-points irrespective of the time, date, location, phase in the customer life cycle, they stand to lose. With Pimcore’s PIM, integrating different systems, breaking down silos and managing data efficiently can put you on a trajectory of growth.

A PIM Solution that’s Simple yet Mature:

At the core, it’s all about managing the details about your products, like SKUs, specifications, core product data, digital assets, content, omni-channel data, metrics, and the works. And Pimcore does it like no other PIM software.

Be it the drag and drop approach, quick and easy data entry and management or a context sensitive navigation, it’s a breeze to maintain data assets on Pimcore. Its unrivaled interface too, makes it simple to manage data from multiple domains within one consolidated platform. Besides, Pimcore can be a great fit with CMS, DAM, and Commerce, which can immensely curb your time-to-market.

Unmatched Data Integration, Management and Delivery:

As a retailer, your business’s success will always hinge on your ability to integrate, manage and deliver properly. Pimcore’s data integration is unique in every sense. It has the capacity to integrate into just about any IT environment. This is due to its API driven approach and “connect anything” architecture, so whether it’s Oracle, SAP, Navision or anything else, you can look forward to a seamless integration.

Having rich product information in a flexible and agile data model, which is user-friendly, consistently organized, aggregated, classified, and ready for translation is one the biggest virtues of Pimcore.

Retailers can expect a lasting information infrastructure support, which will secure them for the future and ensure data integrity.

Pimcore Helps in Carving Impeccable Customer Journeys:

In retail, user’s perspective reigns supreme. Every possible trajectory of a customer’s journey must be thought through distinctly and mapped out. Everything that a customer is capable of doing, the touch-points they might engage through, all their possible actions, the way they see it must be taken into account. And Pimcore’s PIM can be of excellent help in doing this. It will act as a powerful link between your data and your customers in every step of their journey. It can subtly guide them, which will eventually lead them towards decision making.

Wrapping Up:

Customer centricity may be the driving force in today’s retail environment, but that doesn’t take away the importance of other stakeholders such as suppliers, sales teams, online marketers, logistics departments and other units. It’s pertinent that they all work in perfect unison, minus any silos, in order to contribute towards creating a great customer journey. Pimcore’s PIM can give you a leading edge in making it happen.

Rajneesh KumarA digital marketer and growth hacker, Rajneesh Kumar is currently marketing manager at Pimcore Global Services (PGS), an award-winning consolidated open source platform for product information management (PIM), web content management (CMS), digital asset management (DAM) and e-commerce. He is well versed with web analytic tools, paid media marketing and has hands on experience on seo techniques, organic promotion and content marketing.

The Link Between Privacy and Product Data

Do we as a consumer need to be told what to buy? Or do we rather want to be told what we are buying?

This theme was examined in a previous post titled You Must Supplement Customer Insight with Rich Product Data.

Not at least on the European scene with the upcoming General Data Protection Regulation (GDPR) there are limits to how far you can go in profiling your (prospective) costumers. And I am sure those people will value more you are telling them the complete story about your products, rather than guessing what products (from your range) they might need.

As a consumer, we want the facts about the products to make a self-service purchase. We want to be able to search for and navigate precisely to a product suitable for a specific use. We want the facts in a way, so we can compare, perhaps using a comparison service, between different brands and lines. We want to know what accessories goes with what product. We want to know what spare parts goes with what product.

By the way: Business buyers want all that too. And a person being a business buyer is a person (data subject) in the eyes of GDPR too.

For providing complete and consistent product data you as a (re)seller need to maintain high quality product data and if your product portfolio is just above very very simple, you need a Product Information Management (PIM) solution and, if you have trading partners, you need a PIM-2-PIM solution to exchange product information with your trading partners.

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When You Know that Statement is Wrong

1271Oftentimes it still takes a human eye to establish if a number, year, term or other piece of information is wrong.

I had that experience today at Harvard Square in Cambridge (Boston) when looking at the sign in front of our lunch restaurant. Established 1271 it says. Hmmmm. North American natives were not known for establishing restaurants. Also, the Vikings did not stay that long or went that south in North America.

The restaurant website actually admits the sign is wrong and this is a printing flaw (should have been 1971) that they have chosen to keep – maybe also in order to test the clever people hanging around Harvard.

Anyway, without attempting to turn this into a foodie blog, the food is OK but the waiting time for being served does resemble spans of centuries.

You Must Supplement Customer Insight with Rich Product Data

school_420x310This week I attended an event called Retail Summer School at Columbia Business School in New York.

Much of the talking was about how to get insights on your (prospective) customers by collecting data in all kinds of ways – while observing the thin line between cool and creepy.

My thinking, of course biased by my current Product Data Lake venture, is that you should also pay attention to product data. For at least two reasons:

Algorithm effectiveness: Your algorithms on what products to present based on your rich insight into your customers need will only work if you are able to automatically match the needs against very specific product attributes. And most retailers don not have that today if you look at product descriptions on their ecommerce sites.

Also, I am not impressed by the suggestions I get today. They generally fall into two buckets:

  • Things I absolutely do not need
  • Things I just bought

Self-service craving: As a customer, we will strike back. We do not need to be told what to buy. But we do want to know what we are buying. This means we want to be able to see rich product information. Therefore retailers must maintain a lot of product data and related digital assets that they should fetch at a trusted source: From the manufactures. And if the manufacturer wants their products to be the ones selected by the end customers, they must be able to deliver these data seamlessly to all their distributors, retailers and marketplaces.

The Problem with English

– and many other languages

This blog is in English. However, as a citizen in a country where English is not the first language, I have a problem with English. Which flavour or flavor of English should I use? US English? British English? Or any of the many other kinds of English?

It is, in that context, more a theoretical question than a practical one. Despite what Grammar Nazis might think, I guess everyone understands the meaning in my blend of English variants and occasional other spelling mistakes.

The variants of English, spiced up with other cultural and administrative differences, does however create real data quality issues as told in the post Cultured Freshwater Pearls of Wisdom.

EnglishWhen working with Product Data Lake, a service for sharing product information between trading partners, we also need to embrace languages. In doing that we cannot just pick English. We must make it possible to pick any combination of English and country where English is (one of) the official language(s). The same goes for Spanish, German, French, Portuguese, Russian and many other languages in the extend that products can be named and described with different spelling (in a given alphabet or script type).

You always must choose between standardization or standardisation.

Three Game Changers within Product Information Management

Product Information Management (PIM) is a fast-growing discipline enabled by PIM platforms. While the current market for PIM platforms is much about supporting a consistent in-house management of the information related to product models we make, buy and sell, there are new opportunities arising. Three of them on my radar are:

globalInternet of Things (IoT)

With the rise of IoT and the related theme Industry 4.0 we will in the future not just have to deal with the product model but also each physical instance of that product. As an example of how many product groups that might embrace, read about that IKEA is thinking about embedding its furniture with artificial intelligence.

Value webs

The recent buzzword in the chain starting with “supply chain” and going over “value chain” is “value web”. Learn about the arrival of continuously evolving business ecosystems and value webs in this article from Deloitte University Press. Product information management encompassing business ecosystems will be imperative in value webs.

Product Data Lake

This is in all humbleness my venture by having launched a PIM-2-PIM platform that deals with the current main pain in product information management, being exchanging product information between trading partners. We do that in an agile and automated way by supporting partnerships in value webs and are soon adding things to Product Data Lake.

Get into the game by registering for a trial account on Product Data Lake.

Data Quality for the Product Domain vs the Party Domain

Same Same But Different

The difference between solving data quality issues for party (customer, supplier and other business partner) master data and product master data was discussed 7 years ago on this blog in the post Same Same But Different.

Data Quality Dimensions
Some data quality dimensions

Since then I have worked intensively with both party master data and product master data and the data quality challenges organizations have within these domains.

Building on the findings from 7 years ago and recent experiences, I think there are two areas it is worth emphasizing on:

  • Data Quality Dimensions: All dimensions are important and they support each other in solving the issues. But there are some differences as explained in the post Multi-Domain MDM and Data Quality Dimensions. In my mind, uniqueness is the worst pain for party master data and completeness is the worst pain for product master data.
  • External Data Sources: The use of data sources was examined in the post 1st Party, 2nd Party and 3rd Party Master Data. In my mind, extensive utilization of third party data is paramount for party master data quality and effective exchange of second party data is paramount for product master data quality.

A Sharing Concept

For solving both party master data and product master data quality issues you need Multi-Domain MDM for business ecosystems as proposed in the Master Data Share concept.

Aloha Facebook, Where am I Today?

Facebook is set to fight fake news by using artificial intelligence. A good way to practice may be by playing a bit more around with their geolocation intelligence.

Today I, as far as I know, are on the Canary Islands. This is a part of Spain, though a little bit away from the motherland down the Atlantic Ocean off the North African coast. A main town on the islands is called Las Palmas.

However, according to Facebook I seem to be in a place called Las Palmas Subdivision on Hawaii in the Pacific Ocean on the other side of the globe with Hawaii being a bit away from where it were last time I looked on a map.

Facebook Geolocation Hickup