Setting up a Front-end Data Quality Firewall

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In a project with an international vendor some years ago, I introduced the concept of splitting the Data Quality Firewall (DQF) in a Frontend and Backend Data Firewall. These terms are spreading and I get question on how you should set up the Frontend DQF. Last query was just this week via Twitter. My focus is not on the technical side, but the usability and reward for operatives and companies.

Why is the Frontend DQF important?

I participated in the Information Quality Conference in London, where it was stated that 76% of poor data is created in the data entry phase. Be proactive in the data entry phase, instead of being reactive (sometime, if ever) later will help you a long way to good and clean data.

Elements of the Frontend DQF.

First identify in which systems data are created. It may be in a variety of systems like CRM, ERP, Logistics, Booking, Customer Care just to mention a few.

Error tolerant intelligent search in Data Entry systems.

Operatives have been taught by Google and other search engines to go directly to the search box to find information. When you search in Customer Entry systems, it is very often you do not find the customer. In order to this you need error tolerance and intelligence in your search functionality, as well as the suggestion feature. This will help you find the entry despite of typos, different spellings, hearing differences and sloppiness. This will be the biggest contributor to cleaner data. A spinoff is higher employee and customer satisfaction due to more efficient work.

If you want to learn more about error tolerance and intelligent search, read these posts:
Making the case of error tolerance in Customer Data Quality
Is Google paving the way for actual CRM/ERP Search?
Checklist for search in CRM/ERP systems.

Data Correction Registration Module

If you did not find the customer and the operatives have to enter the data, you have to make sure the data entered is accurate. You can install a module or workflows that checks and correct the information.

Most CRM systems will only find the customer if you do exact searches

Check against address vendors
If you have a subscription with an address vendor, you can send the query to them, and they can supply you with the most recently updated data. You can set up so it is easy for the operative, and the data will be correctly formatted to your systems.

This is quite easy for one country. If you are an international company, the laws and regulations are different from country to country. In addition the price can run up if you want local address vendors in several countries. It is important that you registration module can communicate with the local vendors, then format and make the entry correctly into your database(s)

Correct the Data Formats

You might choose not to subscribe to online verification by an address vendor. There are still many checks you can do in the data entry phase. You can check:

– is the domain of the e-mail valid?
– is the format of the telephone number correct?
– is the mobile number really a mobile number?
– is the salutation correct?
– is the format of the address correct?
– is the gender correct?

Example of registration module

Check for unwanted scam and fraud

You can check against:

– internal black lists
– sanction lists
– “Non Real Life Subjects”

Duplicate check

Even though duplicates should have been found in the search, you should do an additional duplicate check, when the entry is done.

If you incorporate these solutions, you should be able to control that the data you enter is clean and correct. It should be possible to get it from one vendor.  Then you can use the Backend DQF to ensure the cleansing of detoriating existing data.

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Is Google paving the way for actual CRM/ERP Search?

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Since 1992 CRM has been a big help in structuring my sales. A consisting challenge I’ve had with various CRM systems, was to find the customer in the system. I might have heard the customer’s name wrong, spelled it wrong, did typos, or my search with *.* did not work.  Frustrating, since I knew the customer was in there.

Most CRM systems will only find the customer if you do exact and correct searches

It was even more frustrating when I worked in a big computer company, and my coworkers entered my customer with slightly different spelling, and stole my commission.

When you do not find the customer, you enter them again and the Data Quality mess starts:

–          Wrong reports and predictions

–          Frustrated workers

–          Frustrated customers

–          Higher cost, lower conversion rates and your image take a hit.

3 years ago I predicted that search would become an important part of the CRM. With an error-tolerant search, you could find your customer instantly. I was wrong then, but finally the trend is here.  This year I have already have had several inquiries about CRM search.

Google is transforming CRM Search

Google has transformed the way we use the web the last 10 years.  We now automatically go to the search box, to find the information we want.  Not only on the world wide web but also:

–          In online shops

–          Intranets

–          Onsite search on government sites

–          Facebook has moved its search in center, acknowledging this is the best place.

“Our employees are so frustrated that they cannot find the information in the CRM system” is the reason I hear when they contact me for better CRM search.

I think we will see this in the future of CRM search:

–          One central search box, that search across all fields

–          Will be error tolerant

–          Have suggest feature, to help you complete the search

–          Will be connected to external vendors to automatically import customers if it is not already in the CRM system.

You can see my CRM Search Checklist here, and a demo video I have made about the future features of the CRM Search.

Most poor data is created in the data entry phase. With a good search and registration system, this can be minimized. A

Do you agree with my view on the CRM Search future?

Making the case of error tolerance in Customer Data Quality

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Sales people are the ones who complain most about poor data quality and at the same time probably the ones who create most of the dirty data. 76%  of the dirty data is created in the data entry phase. Why not make it easier by introducing some error tolerance in their CRM/ERP Search, Data Quality Firewall, Online Registration and in the data cleansing procedures?

Why is dirty data created?

There can be multiple correct spellings of a name
Let’s say your customer Christopher Quist calls you? I have gone through the name statistics in the Nordics. There are 10 ways that Christopher is spelled and 7 ways Quist is spelled.  This means there are 70 possible correct ways to write his name!

Christoffer Kvist

How big chance is it that the customer care or sales representative hits the correct form? It can be unprofessional to ask Christopher many times, it is time consuming and irritating. With an error tolerant search – the representative would find it immediately.

People hear differently.
I used to work at the Nordic call center for Dell in Denmark. I would hear and spell a name differently than the Danes. The most common way to write Christopher Quist in Norway would be Kristoffer Kvist and in Denmark it would be Christoffer Qvist. In the Nordic Call Centers it is not uncommon to answer telephones from another country, and therefore the chances of “listening” mistakes grow.

People do typos.
In the entering process it is easy to skip a letter, do double lettering, reverse letters, skip spaces, miss the key and hit the one beside it, or insert the key beside the one you hit. If we do all these plausible typos with the most Common way to write Christoffer Qvist in Danish – it would generate 314 ways of entering the name! The Norwegian version of Kristoffer Kvist would generate 293 plausible typos!

Sloppiness
Sometimes people believe it is easier or safer to just enter the data again.

Other mistakes error tolerance covers

  • Information written in the wrong field (contact name in the  company field)
  • Information is left out (Miller Furniture vs Millers House of Furniture)
  • Abbreviations (Chr. Andersen vs Christian Andersen)
  • Switch the order of the words (Energiselskabet Buskerud –Buskerud Energiselskab)
  • Word Mutations (Miller Direct Marketing – Müller Direct &
    Dialogue Marketing)

What will the result be for you if you have error tolerance?

  • Cost reduction – if you have a call center of 100 persons and they would save 20 seconds for each call. They could start immediately serving the customer, instead of making the customer spell their names.
  • Happy customers – it is annoying to always have to spell out the information to a sales representative if you want to buy something.
  • Happy workers – it is annoying trying to find a customer you know is in the system – but cannot find!  You spoil valuable selling time

Introduce true error tolerance today!