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Why Data is more important than you think in CRM September 4, 2011

Posted by Ivor's Window to the IT and CRM World in Microsoft CRM.
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The Data Challenges of Implementing a CRM System.

Abstract

CRM is again in vogue, companies are talking implementation and many projects are underway world-wide and lots of people are talking about success, however what is not being talked about are the failed implementations which may besmirch the name of the specific product or even damage the reputation of CRM, when in fact the failures have nothing whatsoever to do with the product or CRM itself.

One of the real reasons for CRM failure has to do with the reality of Data Cleansing and bringing across bad data from an old system.

The Data (Cause and Effect)

For even an entry level CRM system to be successful, it is vital that the Customer static information within the system is accurate, believable and current, as well as being regularly cleansed and updated. Added to this is the reality that the Contact information is required to be even more accurate and up to date. If this is not the case, users will not make use of the system as their primary source of contact data, and this is start of the slippery slope.

Where does the data come from?

At the commencement of a CRM project, data can be sourced from various places, and I have seen the following as being regular contributors to the CRM Systems that I have implemented.

Source

Debilitating Factors

ERP System

Generally accurate from a postal address perspective, Contact Data poor

Existing CRM System

Fragmented and often without consistency and mostly inaccurate

Existing Outlook Contacts

Standards are often different and the depth of data is weak

Spreadsheets in use

Again standards differ and the quality of the data can be poor

Home-made systems

Data from a proliferation of Access Databases and other applications is often data poor

Manual Records

Will mostly not have all the appropriate data (Addresses) completed

Business Card Holders

An accurate source of data, many cards collected will be of non customers or prospects and not relevant to a CRM system

Service System

Like the ERP this is likely to have good base data, but often has only records for a specific group of customers

Customer v Prospect

The typical accountant view, that “I don’t want prospect records in my ERP system” is understandable as is the view that the CRM primary Contact is not the same as the Primary Contact as seen by the accounts department, who need their data for following up debtors.

Prospects are important to Sales staff, and are an essential part of a CRM implementation, however integration of CRM to an ERP environment is going to have to live with the concept of records existing in the one system and not in the other.

Naming conventions are another data element where scope exists for duplication and poor record keeping. Accounting systems will generally keep the name of the business in line with the legal name, where the customer might be known to the salespeople under the trading name or a derivative of the legal name. This can have issues when leads are converted to customers, in that once a salesperson sells an account and a credit application form is completed, Salespeople seldom then update the CRM system with the correct details.

Multi Branches have a way of further complicating this scenario, where in certain circumstances the sales team deal with multiple branches, and the ERP system requires just one record for accounting purposes. The converse also applies where the accounts department send out records and deliveries to multiple addresses, and the sales team only have dealings with one instance at Head Office.

Clearly the starting point is going to be muddy, should the organisation be seeking a good system with clean data, some serious work is generally required to get the data to the appropriate standard.

Consider for a moment the following data from a real customer. We were asked to have a look at their system 1 year after a self implementation.

(There are 20,134 Customer Records and 23,256 Contact Records on the CRM System).

Data

Observation

8504 of the above Customer Records have no name in the Name Field

This is quite unusual, the source data must have been very poor

2762 Contact Records have something in the e-mail field

This is common with a 10% completion rate

1656 records do not have an @ in the email field

Data should have been validated 60% of e-mail data is not valid!

3548 Contact Records in the database only have a first name

Not a problem if this is the normal business model, could cause e-mail duplication

381 new records entered in 1 year, only 6 of these had postcodes

Poor Data Capture to a new system is inexcusable

32% of Customer records have a postal address

This is typical and can affect mail merges and marketing in a negative way

This is reasonably typical of a CRM implementation where the source data was imported from a previous system without prior cleansing.

To clean this data would be a huge job and there are often hidden costs associated with Data Cleansing. When the sales price is tight, giving the customer the bad news about additional costs tends to mean that this subject is ignored, papered over and only raised once the project is fully underway.

Sales people in particular have a reputation for being poor administrators, this is often a throwback from a previous era where salespeople were generally not using computers and were keyboard illiterate. Today however most people know how to use computers, and are able to use systems, and there is no excuse for not capturing the correct information.

A major excuse that we hear when sales people are asked to update their records, is that it will be too time consuming (They then will not be selling during this time and this could impact the business), this is a spurious argument, akin to blackmail, however I have seen management fall for it time after time.

The Data Solutions

Bite sized chunks are what is required in terms of updating records. If all sales staff are mandated to update 2 records per day (5 minutes of work) a team of 5 sales people will be updating 200 records in a month. The concept of running a data cleaning afternoon (Could be a Friday), where each salesperson dedicates 2 to 4 hours to updating their personal records is another way of handling this situation. It is amazing how much work can be done with a concerted effort all focussed on the same objective.

Given than most companies across most disciplines seem to have the 80/20 rule, where 80% of the business comes from 20% of the customers, then the initial focus needs to be on these 20%. This is just something that has to get done. If this is handled with each person looking into their top customers, and everyone does it at the same time, then in a very short space of time, the records of the top customers are suddenly up to date.

External Data Cleansers, when given a list of customers, and access to a system can also attack a large group of customers very quickly, updating records.

CRM Used as a Data Cleansing Tool

Microsoft CRM can be very effectively used as Data Cleansing Tool by the creation of Views and Special Advanced Find’s, and by adding a “Data Cleansed” Field to various forms and monitoring these elements.

A View that shows all customers with no Phone or Fax Numbers, or where other data is missing will allow management to log on and view how many records still meet this negative criteria, and by keeping records one can manage how these numbers decrease on a daily, weekly and monthly basis.

If a field is added to CRM for Account and Contact, which gets updated with a date once the record has been cleansed, It is possible to pull reports from the system showing the number of records updated over a specific period.

Targets can be set and this can linked to incentives. Again special views get run on all records that have been classified as cleansed to ensure that the standards are being kept.

Exports to Excel can give a pictorial view of gaps in data.

Smart Software where postcodes can be sourced from a database and this is used to populate the CRM system, as well as enriching of data based on intelligent field recognition are more expensive but ultimately more accurate methods of updating the records required.

More importantly someone needs to be made custodian of the data and be held responsible for its accuracy and completeness. This needs to be at Executive or Management level, and should have the appropriate “Bite” to ensure that staff undertake their duties correctly.

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