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 www.EngagingTimes.com 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?’

Komerc in Croatia

People find many ways to be unique, including in their choice of names and how they are written.  Common names may be written in any number of ways (Zachery, Zaccari, Zachery, Zakarey and so) and in any number of forms (Za’Korey, zaKori). This variation, and the importance that the customer attaches to it, reinforces the importance of first time right when collecting information about a person’s name.

I was reminded recently that this rule applies also to company names when reviewing a directory containing Croatian companies.  The directoryshowed a great variation in words that at first glance would seem ideal candidates for correction and standardization. For example, many companies contained strings like these:

Commerc, Comerce, Comerc, Kommerce, Kommerc, Komerce, Komerc

There are many other examples which had me scratching my head: Compani, Konsulting, Konzalting, Konsalting and so on.

Why the variance is spelling?  Are these companies with the English word commerce in their names where that word has been typed as heard by call centre workers with a limited knowledge of English? Are they typos of a valid Croatian word? Are they accurate representations of a valid Croatian word as rendered in different dialects? Is it a mixture of all these factors?

Continue reading ‘Komerc in Croatia’

Ask Me is linked with Any Body and relates with Walther Von Stolzing

Weird subject, isn’t it? Quite obvious for everybody, the persons ‘Ask Me’ and ‘Any Body’ are artificial names. They will never belong to a real person. How they relate to ‘Walter von Stolzing’ will follow.

For over 25 years Human Inference has collected reference data, for instance on persons. Because of our reference set we immediately recognize that ‘Ask Me’ and ‘Any Body’ are fake names. People are using these either in test situations or to hide their actual names.

In the old days we only needed to test on ‘Test Test’, in more recent years we see great inventiveness on these fake names. A brief example can be seen in the following list.

Alpha Beta Any Body
Ask Me Best Friend
Blue Sky Cool Dude
Dress Code El Comandante
Guess Who In Cognito

In case you cannot rely on reference data and interpretation you need to provide a check list. Providing it is one thing, but since users tend to be really creative, maintaining it is essential. Continue reading ‘Ask Me is linked with Any Body and relates with Walther Von Stolzing’

Has your name ever hurt you? – when nomen becomes omen

Addressing clients with the right data often means the difference between making a profit and not making a profit. Working with data quality experts has made me ever more consious of the value personal data represents for people. In this respect names are especially intriguing to me, as owners appear to identify with their name a lot. So I decided to do a little research and determine if people really are what their name tells you. Can nomen indeed become omen?

Your parents probably gave a lot of thought to the name they once gave you, and as it turns out they were right to do so! Research tells us a name can do wonders for its owner, as well as a lot of damage for that matter. Let’s have a look at some remarkable results.

Peter for President!
Recent studies show that in the US a student called Fred is more likely to fail his exam than a student who just happened to be named Andrew: people tend to indentify with their name and, in general, have a positive feeling about letters that correspond with their initials. Consequently Fred is far more likely to settle for a meager F, while Andrew will have an extra motive to strive for an A. Continue reading ‘Has your name ever hurt you? – when nomen becomes omen’