In 2014

99%

of companies claimed to have a

data quality strategy in place.

91%

of those with a strategy still

struggle with contact data quality.

Common

Complaints

0 20 40 60 80

Incomplete or missing data

Spelling mistakes

Outdated information

Duplicate Data

Typos

Data entered in incorrect field

Inaccurate Data

Other

None

Don’t know

Common data errors in customer/prospect/citizen data:

% of sample

“Data is the life blood of a CRM system. The quality of the

data directly relates to the overall health of the system.”

Rowland Dexter, Managing Director, QGate

Data Quality

“The era of quantity over quality data is well and truly over”.

Experian Data Quality

In 2014

38%

of companies use software to check

data for errors at the point of capture.

34%

use software that cleans up data

after it has been collected.

1. Lost Income and

Increased Costs

The average organisation loses 12% of its

income because of bad contact data. This

includes wasted marketing spend, wasted

resources and lost productivity.

If you send out 10, 000 catalogues but

10%

are

incorrect

15%

are

duplicates

25 % of

catalogues are out

there getting you

NO ROI

1. Lost Income and

Increased Costs

Is the solution to spend money on data

cleansing tools that identify duplicates and

other errors?

Yes but that is only part of it.

If you don’t know how the bad data is entering your system, paying to

cleanse the data won’t fix your problem in the long run.

You’ll have wasted money on a stopgap solution that won’t save you from

other pitfalls of poor quality data.

Like…..

“Data is the most visible part of your system visible to

customers, it is the element your credibility is built on.”

Kerry Travers, former Senior Business Consultant, BBC

2. Lowered Customer

Satisfaction

Bad data doesn’t just cost you money. It can be a major hit to

your brand.

26%

28%

21%

67% of companies report problems delivering email.

of those are left unable to communicate with customers.

said their customer service suffered as a result.

suffered reputation problems.

2. Lowered Customer

Satisfaction

Imagine being Andrew Smith…

He gets marketing and other materials addressed to

Andrew Smith, Andy Smith and Drew Smith.

Do you think that makes you look like a competent and

professional organisation?

Sales and marketing think 30% of their contact data is incorrect.

2. Lowered Customer

Satisfaction

3. Inefficiency and

lack of productivity

“The first rule of any technology used in business is that

automation applied to an efficient operation will magnify the

efficiency.

The second is that automation applied to an inefficient

operation will magnify the inefficiency.”

Bill Gates

Organisations collect contact data from an average of 3.4

sources.

Including: Websites, Call Centres and Face-to-face Sales.

Differing data sources lead to inaccuracies and duplicates in

CRM.

3. Inefficiency and

lack of productivity

For example, two salespeople talk to Antonio Andreas and

enter him as a contact in CRM without checking for duplicates.

Both sales reps add notes to their version of Mr

Andreas.

A third rep needs details on Mr Andreas and doesn’t

know which version is correct.

Now imagine that’s the case with hundreds of

records. How can you track engagement with your

company?

3. Inefficiency and

lack of productivity

Bad contact data undermines confidence in your CRM

system or database, slowing productivity and user adoption.

Plus, you have no real idea of what is going on with your

customers and leads.

3. Inefficiency and

lack of productivity

Data is supposed to let you know more about your business so

you can make informed decisions.

But what if your data is inaccurate or duplicated?

80%

40%

29%

of organisations who use their data for business

intelligence have problems generating meaningful

analytics.

blame inaccurate information.

blame insufficient data.

4. Less Informed

Decisions

Decisions made based on inaccurate data may as well be based on

guesses and assumptions.

Poor quality data is one of the most common causes of low

user adoption.

Your CRM and other data management systems could be the

best around with user friendly and intuitive functionality, but if

the data is not current, correct and duplicate free then users

will see that very quickly and not trust it.

5. Decreased User

Adoption

60%

of companies cite human error as a

reason for bad data quality according to

Experian.

5. Decreased User

Adoption

Employees need to be using systems correctly and taking

care to prevent mistakes for your business systems to be

reliable at producing insights and tracking the state of your

business.

There are four steps to cleaning up your dirty data:

How to fix it

1.

3.

2.

4.

Identify – use a data profiling/audit tool to identify data

defects.

Resolve – use a cleansing tool to clean data, remove

errors and fix basic problems.

Prevent – use real-time safeguards to prevent new

errors from entering the system.

Maintain – appoint a data steward for long term

monitoring and management of data quality.

How to fix it

Only

30%

of companies have a data steward, and you

should be one of them.

By crafting a data management strategy that covers all four

of these areas, you will set the best course for clean data and

business success.

Don’t let bad data ruin your business. Take a few minutes to find out more about the data quality tools that can identify and resolve data issues.

Blog LinkedIn Twitter | |

Data De-duplication Duplication Prevention