Data Health Associates, LLC

Inch by Inch, It’s a Cinch

Maximize Return and Reduce Risk bySimplifying Your CRM Data Structure and

Grooming Methodology

Presented by John WoodData Health Associates, LLCFocused on the data of health and the health of data

Data Health Associates, LLC

We know your dirty little secret…

We know you have dirty CRM data…

Data Health Associates, LLC

Your data will never be as clean asyou want it to be.

Data Health Associates, LLC

This Afternoon’s Agenda

• Underscore the importance and value of proper data grooming

• Focus on maximizing the return on data grooming time and financial investment

• Identify the key risk areas of having dirty CRM data• Touch on best practices for CRM data management

efforts• Provide strategies for reducing the overall data

grooming need

Data Health Associates, LLC

Firms Implement CRM’s to:

• Capture, centralize and standardize contact data from a variety of sources

• Categorize contacts

• Provide timely, targeted communication to clients

• Drive effective cross-marketing between practice areas

• Track client touches activities

• Reward collaborative effort

Data Health Associates, LLC

Importance of Data Quality Management

Entire value of the CRM system is predicated on having clean, correct

and reliable data.

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Reasons for Dirty Data

• Data degrades at a rate of 1.5 to 3% per month*

• Diverse channels of data collection– Initial sources– Ongoing synchronizations– New hires

• Most data systems tend toward complexity– Category bloat– Too many lists / Too many queries and reports– Unnecessary fields

* - Study published by the Data Warehousing Institute.

Data Health Associates, LLC

Risks of Dirty Data

• Lack of data quality cost U.S. businesses more than $600 billion per year*

• Damaged credibility• Loss of clients• Legal violations• Black listing• The potential to violate attorney client

privilege• Loss of confidence in your CRM

* - Study published by the Data Warehousing Institute.

Data Health Associates, LLC

Two-Step Program

Admit that your data

needs cleaning

Clean your data!

Step 1 Step 2

Data Health Associates, LLC

Inch by Inch is a Cinch

• Don’t attempt to clean all your data at once. Focus on simple fixes that have a big rate of return.

• Focus on selected subsets of your data• Simplify your data structure• Clean the data that you’re currently using

or planning to use

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The Datacratic Oath

“Do no harm. Lose no data.”

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Focus on a High Rate of Return

• Clean the data you’re going to use.

• Focus on top firm or practice area clients• Focus on obvious duplicates

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Firm Case Study #1

• Decision was made to save money and, at the same time, “go green”

• All holiday cards would be electronic• Marketing Director had low confidence

level in email data in their CRM• Initiated concerted effort to focus on

cleaning only duplicate email data• Results: Overall duplicate records went

from almost 15% to .1%.

Data Health Associates, LLC

Simplify Your Data Structure

• Reduce the amount of information tracked in each record

• Eliminate unused categories• Eliminate unused lists• Eliminate unused queries and reports

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Clean Data That You’reGoing to Use

• Find out who is using what data

• Find out what data is being used most frequently

• Groom that data first• Identify Questionable Records and Make

Them Private

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Simple Steps to Minimize Risk

• Don’t roll out your CRM until the data is ready

• Roll out in manageable groups• Careful de-duping• Track mail status• Avoid SPAM

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Canadian Anti-Spam Legislation

• Add a minimum # of fields for tracking

– When did you ask for consent?– When did you receive consent?– Why did you ask for consent– How did you ask for consent?

– When will consent expire?

• Demonstrate an intent to comply– Protection should you become the target of

litigation– Shows good faith

Data Health Associates, LLC

Firm Case Study #2

• Large firm decided to implement a CRM system in a serial approach

• Initial data added from marketing “database”

• Marketing data had been pre-cleaned to high level of data quality

• Attorney Outlook Contacts folders were synchronized in groups of 10 or 12.

• As each group was added, duplicates were rectified and records cleaned

• Results: High number of attorney contacts added over time with little perception of dirty data

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Simple Tactics and Tools

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Firm Style Sheet and Conventions

• Contact naming conventions

• Company naming conventions• Master Company List• Acceptable Address Formats• Rationale for private fields

• Protocol for keeping records private

• Keep the number of required fields manageable

• Focus grooming on new records

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Track Ongoing Metrics

• Continue simple ongoing maintenance• Keep your fingers on the pulse• Know how your data is trending • Run statistic each time you groom the data –

before & after• Watch for irregularities • Watch for programmatic problems• Use metrics to communicate the worth of data

quality activities

Data Health Associates, LLC

Firm Case Study #3• Large firm completed initial data

grooming “triage”, reconciling all possible duplicates

• Focus on new contacts that have been automatically flagged as new

• Concentrated on reducing distinct company names

• Converted abbreviations to full words• Fix incorrect address data entry issues –

entire address in one address field

• Result: Breaking up the data grooming into discreet tasks kept the process from being overwhelming to the data stewards.

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Let History Be Your Guide

• When was the data last changed?

• How often has it been changed and by whom? • Previous edits made by Data Steward(s)

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Conclusions

• Dirty data in CRM systems is inevitable

• Dirty data poses real risks• Simplifying data grooming methodologies can

substantially reduce risk and provide quicker return on CRM investment

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Questions

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Contact Information

John WoodData Health Associates LLCjwood@Data HealthAssociates.comwww.DataHealthAssociatesToll Free: 855-342-3282Direct: 401-433-4778