maintaining clean product data for customers - lorraine mott, eaton crouse-hinds

© 2013 Eaton. All Rights Reserved.

Our Journey to Platinum: Finding the Gold Nugget

Lorraine Mott, Project Lead Ecommerce

Eaton Crouse-Hinds

EBiz Forum 2013 “Dream it, Do it, Let the Innovation Begin”

Orlando, FL

2 © 2013 Eaton. All Rights Reserved.

What does these two items have in common?


Times have changed

Arpit Dhariwal


Why Are Distributors Asking for MORE Data?

• Satisfy customer demand

• Enhance existing customer relationships

• Support more sales channels & reach new

customers

• Reduce catalog management and distribution

• Reduce order processing and customer

service costs

• Drive competitive advantage & differentiation

• Speed time to market


Voice of Customer

What our distributors are saying:

• Normalize your descriptions, attributes

• Need searchable information

• UNSPSC, long description, images, spec sheets and

attributes will help you differentiate your products on

the features, not solely on the price.

• Print catalogs are out of date sometimes even

before they are published….


Why did we make this a priority?

WRONG INFORMATION

and its IMPACT

RISK


Negative Impact

• 90% of buyers get lost before checkout

• 33% didn’t find enough product information

• Returns – products that can’t meet expectations

• If your customer can’t find what they are looking

for, or they don’t understand how your product

meets their needs – they won’t buy it!


Remember this…..

No Data

No Decision

NO SALE

No Data

No Decision

NO SALE


Bottom Line

“Rich, accurate, searchable data can serve as a

catalyst for enhanced customer relationships,

lower selling cost & give stronger competitive

advantage”. - TDWI Research

• Reach your business objectives with best product content

• Increase conversion and lower return sales

• Lower manual processing costs

• Build customer loyalty


Where to Start

• DISCOVERY

• What information was required

• What information did we have

• Identify where flawed content is

• Who was responsible for providing content

• Incentives to provide the data???


Steps Taken

• Data verification

• Data validation

• COLLABORATIVE EFFORT

• Workflow for creating, reviewing, approving,

publishing & enforcing


Success

Requires

Change


Things we initiated

• Lockdown the data

• Sharepoint site established

• Created a glossary

• Established a process flow with standard work

• Designed a form for NPN (New Product

Notification), applicable to legacy as well

• Implemented data quality tools of IDW


Master Data Defined


Field Definitions


Description Example


CHALLENGES

• Sheer volume and complexity of data

• Creating/gathering data

• Maintaining

• Need a strategy and all responsible parties’ buy in

• Multiple systems and departments have the information

• Ability to handle all forms of information

• Having the solution in ONE place

• This is the task that never ends……


Ongoing

• No launches until all data in place

• Addressing acquisitions

• Constant process to keep updated.

• We have complete control over our data – it is

our responsibility to ensure it is accurate


What it Will Come Down to

• Need rich info – videos, attributes, images,

360 degree view, unique selling points

• Who has the best descriptions, images, videos

• The companies that INVEST in their data will

have the competitive advantage


“Product content management has come to the

forefront as a critical function of ECommerce”

– AMR research

• Companies will reach their business objectives with best

product content

• Increase conversion & lower return sales – customers get

right information

• Lower manual processing costs

• TRUSTED PRODUCT INFORMATION IS THE #1 DRIVER

FOR BUSINESS

Why is this the Right Thing to do?


Information

closes

the deal

means

more

profit


Getting clean and Staying clean

• Data cleansing

• Using IDW, SCA & DAC as master data

management tools


CHECKLIST

• Get business buy in

• Develop & implement your standard operating procedure

• Purge old product info – if obsolete greater than 6 mo, remove from IDW

• ONE storage place!!!

• Prioritize products - clean up high sellers first

• Legacy data – attack by product family and use full NPN process

• Normalize – use best practice description white paper, product life cycle,

marketing codes, etc.

• DMP Scrubbing rules – CORRECT ERRORS!

• IDW errors – CORRECT ERRORS!

• DAC – obsolete, duplicates, UNSPSC, unpriced - CORRECT ERRORS!

• SCA – great tool to find inconsistencies

• Send data regularly

maintaining clean product data for customers - lorraine mott, eaton crouse-hinds

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