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. It also explains how in choosing a partner we show a slight preference for someone whose name resembles our own, or why Mary will prefer to live in Maryland, while Monica is more inclined to settle in Santa Monica. Most of these preferences only show themselves through our subliminal selves, so we are not actually aware of the motivation for some of our choises. Another US study endorses these findings: inspired by the results mentioned above, researchers decided they’d investigate on another letter. They came up with the letter K, which in baseball stands for strikeout. The study showed once again that there is a connection between a letter and its causer: batters whose names began with a K struck out more often than other batters.

Ominous names
A UK research tells us that as much as one in 5 parents regret how they named their child. The novelty might have worn off after a few years, but can there be any real objections to a certain name? Apparently, there are plenty! Ironically it’s not the parents who’ll have to carry this burden for the rest of their lives…

“Hi, I’m Antwan, but you can call me Antoine…”
It seems that even children’s language skills are influenced by their name. This has to do with the effect negative emotions can have on a child’s performance. If for example you decided to name your son ‘Gene’ but spell it ‘Jene’, he is very likely to get confronted with disbelief from his teachers. “Are you sure your name isn’t spelled with a ‘G’?” This can severely undermine Jene’s sense of confidence. That explains why children with an unusual name or a name that is unusually spelled generally are less adequate spellers and readers.

“But Sissi is a Royal name, dear!”
When a girl is called Frankie we think it’s a fun name, a cool and robust statement to fit a strong personality. Yet when a boy is called Mckenzie, (yes, some parents think it’s cute to give their boy a name that has a feminine touch to it ) we see a similar effect, but with a different outcome. This is something his parents obviously had not foreseen: their son will constantly be shaking off his girly image. The effect is striking: boys with a androgynous name misbehave more often than their unambiguously named peers, especially when they reach puberty. A boy called Mckenzie or Aubrey is even more likely to display bad behaviour when there is a girl with the same name among his peers. One more reason for parents to stick to conventions when choosing a name for their newborn.

Want to produce the new Einstein? Call her Kate!
A name can be a burden, but if you use this knowledge wisely, you might just turn it into an advantage. What happens to a girl when she has finished school and needs to choose what subject to study? Well, according to a US study, her choice depends on her name. As it turns out girls with a very feminine name like Julietta or Isabella are more likely to study humanities, while those whose name is less obviously feminine are more partial towards science. The question is: who’s aspiring to whom? Could it be that parents would treat Kate in a different way than Barbara? Or did the parents subconciously decide they wanted to raise a scientist when they decided to call their daughter Kate?

Would you rather hire Vanity or Grace?
Of course it’s not just letters or gender that determines how we feel about a name. In fact, how other people perceive us very much depends on the meaning of our name. For example: when looking for a new member on your marketing team, would you rather hire Vanity or Grace? In spite of what her name tells us, Grace might be a job jumper who doesn’t know how to work in unison with her colleagues. Vanity on the other hand could just be a daughter of a well-read mother who had just finished her latest Thackeray when she gave birth. Still, both women will either meet a lot of prejudice or feel the need to live up to a very high standard because of their name.

It all goes to show that a name defenitely posesses some self-fulfilling qualities. Given the fact that so many parents regret their choice of names afterwards makes me think that the owners of that name might share these sentiments. So what does that mean when looking at it from a data quality point of view? Unisex names for example are responsible for a lot of data quality issues. As the borders between male and female names are fading we’ll need to update our knowledge continually. The human in Human Inference will definitely take care of that. After all, we wouldn’t want to you to put off Mrs Clinton when sending her a petition to take pity on the Syrian citizens starting: “Dear Mr. Clinton…”.

Source: Livescience.com & Babynames.com

One of the first things I will start working on this year is a paper on First Time Right. Naturally, my colleagues and I had discussed the content of such a paper before, but during my Christmas holiday I figured out what the line of thought for the paper should be. Next to the definition and the importance of the priciple and the approach in data quality solutions, I think that First Time Right is definitely about the business value and the advantages for the customers.

Let me give you a short preview:

Customer data plays a crucial role in the value chain of any business infrastructure. Whether purchasing, production, distribution, marketing, sales or service is concerned, the availability and the quality of your customer data is of great importance to these processes. A few examples?

- A customer calls his insurance company in order to find an answer for a question he has on his fire insurance. How fast will the operator in the customer service department find the right customer?

- A large software company is running a report from its CRM-system in order to invite a selection of their international customer to an event they are organizing. How do they know that they are indeed selecting the intended customer? And how do they know they haven’t selected the same customer twice?

- In the self-service portal of a large retailer, customers are allowed to enter and alter personal information. How is the retailer going to prevent data pollution?

I think that organizations need a guiding principle to automatically, quickly and reliably check if the customer data already exists in the database(s). In addition, the data must be validated and, if necessary, corrected, completed and standardized.

This principle is called First Time Right. Concise application of the first time right-principle will always lead to an increase in customer satisfaction, to a boost in productivity and to higher revenue.

I expect to finish the white paper in about two weeks. Any thoughts on this preview? I’ll send out another post when I’m done….

Every year when autumn comes the assistants of the sales department get a little nervous. They know what will happen in short term. It’s almost Christmas and the selections of contacts to receive a Christmas card have to be made.

Every year it’s the same. First the selections for every account manager are made and they will have to check manually if these are correct. This year will be the same as ever, which means that:

• relevant companies and contacts are missing
• new companies and contact persons will be added
• contact persons will be deleted
• contact persons will be transferred to their new company
• addresses appear to be not up-to-date

This is one of the best audits to validate the quality of your data. The number of additions, modifications and deletions indicates how accurate your employees have maintained the data in the CRM system. I think that most of us recognize the problem and maybe are part of the cycle themselves. Moreover, it clearly shows where your data management procedures fail. Most likely the account managers are expected to maintain the data themselves, which they don’t see as their primary task. If not account managers have to maintain the data the sales support team usually has to do so. But who will give them the required input? Only accurate data entry, actively monitoring and periodically checking against external sources will help to keep your CRM system up-to-date.

In general the Christmas card has little value for your relation with your contact persons, but such an intense mass mailing is very profitable for your data quality. Until your procedures are in place, keep sending Christmas cards to optimize your data quality.

A major bank in Dongguan (China) refused a potential customer because his name is Li Jun. Apparently, there were already over 300 bank accounts assigned to the name Li Jun. Not that this particular Li Jun was responsible for opening all these accounts, there were just too many men with exactly the same name. The bank states that the refusal is nothing personal, since nobody with the name Li Jun will be accepted as customer in the near future….. In the meanttime, Li Jun is taking legal action against the bank.

When I read this news article this morning, my first thoughts were that it was perhaps a hoax. It turns out , however, that the news fact is true. From a data quality point of view this strikes me as really strange. How does this particular bank manage its customer data? Are there no additional identifiers (address, date of birth, etc.) to determine that you are actually dealing with the customer you think you are dealing with? Imagine that every John Smith would have a hard time to open a bank account, to apply for a job or to buy a product via the web. Or Jenny Jones? Bob Johnson? When is a name too “common”? It is common misbelief that the complexity of ideographic characacters such as Mandarin Chinese makes it harder to identify. At Human Inference we carried out some pretty serious dedups of Chinese files and-taking into account that Mandarin Chinese is a tonal language and other priciples of fault-tolearnce apply- the duplicate identification was rather accurate.

It is all a matter of using an intelligent matching method and knowing what kind of data one is working on. Every name can be identified; even “common” names.

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. According to Gartner, Customer Data Integration (CDI) is a combination of technology, services and processes to deliver an accurate, timely and complete view of the customer across multiple channels, lines of business, departments and divisions drawing customer data from multiple sources and systems.

I think that the real “miracle” of CDI lies in the automated, intelligent matching of customer records. Mind you, I’m not questioning the importance of the various CDI-processes (for example, I think that the post of my colleague Ramon de Noronha on the creation of “golden” records is majorly important), I’m just saying that -whenever the integration of customer data is an issue- intelligent, automated matching is the key prerequisite for success.

The quality of your customer data integration solution is only as powerful as the quality of your matching engine. If this statement intrigues you, I strongly advise you to read the white paper “High Precision Matching at the heart of Customer Data Integration“. Enjoy!

Ideally you want to know more then the data points your organisation is able to collect like address, order history and phone number (and please let those be accurate). What would really help effective marketing is knowing your customer’s contact preferences, social demographics, financial health, social network, employment, daily commute, etc. etc.

Keeping your data accurate with people moving, dying and changing jobs all the time is difficult enough as it is. Keeping abreast of your customers social data seems virually impossible. Has anyone experimented with collecting social network data to do this?