People are strange(rs)

While I was reading Peter Hesselinks’s blog post, I felt an immediate urge to listen to The Doors, without a doubt one of the most influential rock bands of the last century. Listening to my iPod I came across another fitting “lyrics analogy”, which I found quite suitable as a title for this post….

The concept of recognizing and knowing your customer is, in essence, an ancient concept. Having a clear view of who your customer is and what he or she is actually buying (or intending to buy), has proven to be a serious business advantage over the years. You do not want your customer to feel like a stranger.

In the 1960’s it was quite common that the dairyman or the milkman would deliver from door to door. He usually knew how much milk and other products every family wanted. If he had accidentally delivered curdled milk, you would have made sure to tell him the next day. The milkman would almost automatically be informed if a family would move to another house or when it was some child’s birthday for which he consequently would have brought a special treat… This was a convenient and survivable business situation.

Nowadays, we live in a multi-channel society in which customers are used to do business in a variety of ways, which of course is far less transparent than the situation described above.

However, be it in a shop or through a website; essentially the current customer wishes are not that different than these of the customers of some fifty years ago: They still want to be recognized, they still prefer a personal approach, and they do not want to have to spend time informing you of a simple move or the purchase of another product.

But for the businesses serving that customer, a great deal has changed. Customer data is stored in a CRM system, complaints in the complaints database, the payment history in financial software and the order history in an ERP suite. This information fragmentation leads to problems with regard to the single customer view. And these problems impact virtually every area of the value chain of your business. From primary activities like inbound- and outbound logistics, marketing, sales and operations to supporting activities like procurement and human resources. Does the following list ring any bells?

  • Adding the same customer information manually in multiple databases
  • Building workarounds for customer data problems
  • Searching for missing data
  • Manually enriching customer data in one system or the same customer data in multiple systems
  • Assembling customer data across disintegrated databases

The solution to these problems lies in Master Data Management (MDM) of customer data. MDM enables companies to truly serve their customers by having the information they need at their fingertips, when they need it. Start your single customer view today.


Hello, I X U, Won’t you tell me your name?

This is a guest post by Peter Hesselink of SDL Content Management Technologies

You want to address visitors in a proper way. Preferably by calling them by their name, showing that you know them, make them feel welcome, indicate you want to have a dialogue with them.

Hello, I welcome you, won’t you tell me your name?

When people visit your site they remain anonymous until they ‘reveal’ themselves. Registering, logging in, etcetera. Until that time they stay visitors or even ‘strangers’.

Hello, I like you, won’t you tell me your name?

You can tell a lot about people by their behaviour, from their interaction with your website. And if you like what you are seeing, you really would like to get to know them personally. Maybe they are already known to you, your customer, but you don’t know that, are unaware of the fact or unable to ascertain.

They even may like you as well, and their ‘like’ makes it possible to reach them, but not at that moment, with a personalized message.

Hello, I know you, won’t you tell me your name?

This is what happens all the time: people revisit your website, which you (can) know thanks to the wonderful invention of cookies. The whole day a lot of UVO’s (Unidentified Visiting Objects – people, robots and crawlers) come to your website. And you know them, because you recognize them by their cookie or even IP address. You can even serve them personalized content, but still can not address them by their name. You do not really ‘know’ these unidentified individuals, these UVP’s who may be VIP’s to your company.

Now it can become embarrassing. You probably also have had the experience of meeting somebody who you have spoken to before, but cannot remember their name anymore, I have had these experiences … Because you met them in a different place, and/or long ago (your memory is not what it used to be anymore).

This can happen on your website: you know they are there, because they have (re-)registered or logged-in, or from previous behaviour or characteristics. But you do not ‘recognize’ them or show this by personalizing the website content.

This all can be caused due to the fact that information is being collected online, through the website, email, or other means, on different moments, stages and places in the customer journey. And stored in different systems and databases. The total system cannot ‘recollect’ it.

It becomes annoying when for instance a customer has to resubmit information which he or she has provided before. They become frustrated and dissatisfied.

Having to ask again … Or not knowing that it is the same person as the one already stored in your database …

A registration could do the trick, after having logged with their user name and password in you are better able to meet their expectations. Or by letting the customer provide unique, identifiable information, like a customer number or something alike. But this does not make it more (user) ‘friendly’.

Hello, I love you, won’t you tell me your name?

That only works when you are somebody like Jim Morrison of the Doors …

Ambient recognition

Data is being collected at several touch points, moments, implicit and explicit (watch out for another post about implicit and explicit profiling) et cetera and stored in different systems, databases and so on. Having a ‘single view of the customer’ is a challenge. But customers expect that companies have this. They hate it when they have the idea that the company does not ‘know’ them, cannot recollect it.

From back in the days I was working at Acxiom Corporation here in The Netherlands I know the challenge in getting the right name and address information and getting it right (the area of DQM and MDM).

Recently I attended an event of the Dutch Dialogue Market Association, titled Data & Dialogue, chaired by Holger Wandt, principal advisor at Human Inference, an expert in the field of Data Quality and Integration (Gartner thinks so as well, named HI in their Magic Quadrant for data quality tools  as a visionary). We spoke afterwards about these challenges.

So how to achieve this? Well, by best combining ‘all worlds’. In a next post on I will draw an outline of such a solution making use of Human Inference tools and the Tridion Ambient Data Framework (watch the video).

Short question, complex answer: Who is who and what is what in your database?


Any organization that deals with customer, prospect, supplier, distributor, product and service information, uses all kinds of data in their day-to-day business processes. Identification of a customer or a product within an automated system, using a specific id-number, the name or any other identifying feature, is a key issue in these processes. Furthermore, it is a task that needs considerable attention, since the collection and management of data is essentially error-prone. People make mistakes, names are understood incorrectly, numbers are typed in the wrong order; there are just too many reasons for defective data and poor information quality.

The collective term ‘business data’ is often used without a precise notion of what business data actually contain. It is not just the customer identification numbers and product codes. Naturally, the sort and the importance of data used in a business process will differ from organization to organization. However, a closer look at the seemingly endless variation will show that names and addresses of persons and organizations are as detailed and complicated as they are identifying. The following classification will show the details of names, addresses and complementary data.

* In personal names we will encounter: given (first) names, middle names, initials, surnames, surname prefixes, surname suffixes, forms of address, titles, functions, qualifications, professions, patronymics and nicknames.

* The name of an organization can consist of virtually everything: legal forms, fantasy words, natural language words, personal names, numbers, Roman numerals, ordinals, letters, acronyms, geographical indications, suffixes, articles, prepositions, conjunctions, indication of year of establishment and non-alphabetical signs.

* Postal Address data combine recipient information with delivery points: countries, regions, towns, districts, proximate towns, delivery service indicators, delivery service qualifiers, postcodes, addressee and mailee indicators, thoroughfare names, thoroughfare types,  house or plot  numbers, house number additions, building names, building types and delivery point access data, such as wing, floor or door.

* Complementary data used in business processes include: phone numbers, fax numbers, e-mail addresses, dates of birth, contract dates, social media account id’s, product and brand names, product codes, product numbers, gender indication, financial data, lifestyle data and transaction data.

Defining the data groups as precisely and as detailed as possible, is the first step towards useful interpretation. People, applying their natural language processing capabilities, structure the information as they interpret it. They will use their frame of reference, which includes their knowledge dictionary, their linguistic repository, statistical information and mathematical information.

Knowledge-based interpretation, incorporated in an automated system to solve data quality issues, must work in exactly the same way. Consider the following examples: Continue reading ‘Short question, complex answer: Who is who and what is what in your database?’

Data Value?

When I was attending the ECCMA Data Quality Solution Summit in October 2012, I got in an interesting discussion on the quality of a  specific customer data item. The actual point of the discussion was whether an address has quality when you are not aware of what the intended use and value of that particular address was. Intended use? Intended value?  Yes indeed!

As the importance of data quality management is becoming more and more obvious to organizations, the question is no longer “should I manage my data?”, but “how do I manage my data?”. In other words: What is the value of data in the context of the customer’s solution? How is the customer going to use the data? And what is the consequent value of the data for that particalur customer? Is the address mentioned in the discussion above going to be used for a geocoding solution or will it be a delivery address for a postal item?

I think that this is a very interesting way to look at data quality and data management. In his summit presentation, Walid el Abed of Global Data Excellence said that the value of data should be derived from the current or future outcome of the activities accomplished by using the data. In this context, he refers to a paradigm shift from KPI (key performance indicators) driven organizations to KVI (key value indicators) driven organizations.

I like that. At Human Inference we strive to enable organizations to benefit from personal and relevant interactions, based on trustworthy information. It is our “translation of bringing value to the customer’s data.  

Single customer view for REAL customer interaction

Having worked in the data and information quality industry for quite some years now, I’ve noticed that our industry feels that there is an urgent need for new acronyms every couple of years. Here’s a small selection: CRM, ERP, BI, SaaS, CDI, MDM, FTR….. Are you still with me? If so, you have probably been in this business for a substantial amount of time as well. As these acronyms mysteriously or automagically gain and loose popularity, I am now convinced that they all, more or less, serve the same purpose: They intend to be the “theoretical foundation” for solution selling.

Organizations spend a lot of time on optimizing their production chain, their invoicing processes and the quality of their customer database(s). For this, all kinds of tools and systems are being used (and the corresponding acronyms become popular…;-) . Some of these tools and systems are really intelligent, but many times the actual purpose of the deployment of these means is lost in the process. We need to really interact with our customers to help them benefit from the solutions we offer! Of course, we will have to make all the necessary information for customer interaction (social media data, invoicing data, transaction history data, etc.) available for everyone involved at all times.

Eventually, we all want to personalize our customer interaction. Make it a human interaction. Build a relationship…… Well, I could go on explaining my views on this subject, but as it happens we have made this one-minute-movie that explains it much better. Check it out. It’s worth it!

The “miracle” of customer data integration

mulitple view

The more a company knows about its customer’s wishes, needs and habits and the more that company is able to tailor its proposition accordingly, the greater the value it will eventually provide for its customers. We all know that there are countless examples where defective, fragmented, or just plain poor customer data cause unnecessary costs, decrease in revenue, employee dissatisfaction or frustation, damage of the corporate image and many other unsdesirable or painful consequences.

Customer data quality and integration problems impact every area of the value chain of organisations. Far too often companies have a multiple view of their customers. Customer Data Integration (or MDM for Customer Data) is the key to providing companies with a single view of their customer. Continue reading ‘The “miracle” of customer data integration’