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Data Quality Best Practices for Salesforce.com

Data Quality Best Practices for Salesforce.com

Executive Summary

An effective plan for entering, cleaning and updating the data for your salesforce.com (SFDC) system is critical for achieving success with SFDC. According to industry experts poor planning for managing the data entry/data quality issue has historically been one of the largest reasons for failure with CRM systems.

The data entry/data quality challenges faced by a SFDC customer, and the corresponding solutions and best practices to be considered will vary depending on the company sales process and size. However applying data management best practices can be instrumental for creating revenue growth and a competitive advantage with your SFDC investment.

Why Does Data Quality Matter for Salesforce.com Customers? This whitepaper concentrates on the data impact and benefits to sales and marketing users selling to other businesses. Although SFDC is used by a variety of other company functions, such as service and support, this analysis focuses on the best practice recommendations for sales and marketing.

There are two main reasons why current stakeholders in a SFDC project should have a strategy for addressing the quality of data in their SFDC system.

1) Historical Lessons Learned from Prior CRM Project Failures:

There is a growing body of research from industry analysts that "data entry/data quality" is one the top, if not the top factor determining the success or failure for a CRM project.

CSO Insights, a research firm that specializes in benchmarking sales & marketing excellence, published its annual study of sales organizations worldwide on January 12, 2004. The 2004 Sales Excellence Report, which includes responses from over 1,300 sales executives, cited the number one challenge for CRM initiatives was populating systems with accurate data and then maintaining the accuracy of that information. Another research study from the company called, "Increasing Sales Effectiveness Through Optimized Sales Knowledge Management", highlighted three key process improvements desired by the study participants tied to using technology for higher sales effectiveness.

? Dynamic Process. "Over half the organizations surveyed stated that their top improvement objective was to develop ways to manage sales knowledge delivery in a much more instantaneous, as-the-world-is-changing manner. Annual, quarterly, even monthly postings of information are not frequent enough to meet the needs of the rate of change in the marketplace."

? Easier Access. "As noted in past studies, access to information still needs to be improved?In a perfect world there would be one place to go for knowledge, and while it might pull information from several sources, the linking would be transparent to the sales team member?"

? Distribute More Easily. "?a mechanism needs to be in place for notifying salespeople when specific pieces of sales knowledge in which they are interested become available. Individual preferences can be identified by a user-defined profile?"

There was a tendency for buyers of CRM solutions in the 1990s to focus on the functionality of a CRM application and not on the sources and updating of data that would enable the users and management to achieve their CRM objectives. Sales and marketing executives with multiple CRM initiatives under their belt have indicated CRM software is somewhat like an empty spreadsheet where the true value is gained only when populated with effective data.

2) End User Satisfaction Drives CRM Success

From the author's personal experience, CRM applications have historically had a bad reputation among sales users. During the 1990's, Sales Executives were quick to adopt Sales Force Automation solutions (a subset of today's CRM market). Sales reps were subsequently required to do a tremendous amount of research and manual data entry to get each of their leads, accounts, contacts and opportunities into the CRM application. The end result of all of this manual, time consuming work was to provide sales management with pipeline and forecast reports. As a result, reps resented the CRM application because of the data entry requirement and that it didn't provide any productivity benefit to them.

In many cases companies migrated data from legacy contact management applications like ACT, Goldmine or MS Outlook without deduplicating the records and cleaning the data. This caused the users to loose confidence in the CRM application all together due to crippling data problems. Without reps entering data or having confidence in their CRM solution, many CRM projects died or had marginal success. The CRM project sponsors lost trust in the CRM vendor for the failure when the root issue was a data entry or quality problem.

Conversely, if marketing and sales end users are freed up as much as possible from the administrative part of entering, updating and cleaning data, and instead are provided accurate data and intelligence within SFDC for their deals they have an additional reason to be excited about using SFDC.

Parameters that Determine Data Quality There are numerous data management best practices we introduce later in this whitepaper that can automate getting data into a SFDC system and keeping that data accurate over time. Before we discuss these best practices let's touch on four main attributes that affect the quality of data.

? Completeness of a Record. Does the record have data for all the desired fields? Typical examples of an incomplete record include missing countries or zip codes associated with a street address.

? Accuracy of Data Elements. Is the value in the field correct? Typically examples of incorrect values can be old revenue numbers for a company, a phone number with an old area code, and a contact no longer at company. The passage of time and changes at a company account for the majority of inaccurate data about a company. Dun & Bradstreet indicates that a company record in its Worldbase database of 80M company sites gets changed on average 4.6 times a year.

? Number of Duplicate Records. The most common problem with duplicates is account records entered with different company names, ex HP, Hewlett-Packard. Unless you establish a company naming standard that is applied when creating or importing records it is easy to create numerous duplicates.

? Record Linkage. Our definition of record linkage means obtaining related data elements of value from the account record. Examples of linked records include contacts, credit reports, or other global sites within a corporate family tree such as a Johnson & Johnson. Providing the linked attributes around account records enables marketing to define and report progress in target markets and sales to better qualify prospects and determine decision-makers.

Pyramid of Data Quality Issues

SFDC offers a very scalable CRM solution that can be used effectively by companies with 5 to 5000 users. The data entry and quality issues vary considerably though for companies based on how data intensive their sales methodology is, and the volume of records. The later point assumes a company with lots of sales users and groups will have a larger volume of records. As a result there are corresponding different data management best practices for each tier.

Small SFDC Customers:

(Simple sales cycle and low volumes of data, typically 100s to 10k records)

Challenge: Getting data into SFDC. As pointed out earlier, you should avoid having your sales or marketing users manually enter data into SFDC as much as possible, especially for basic account data. The users will resent the time required for data entry and perceived low marginal benefit to them.

Best practices:

? Load as many current and complete account records as possible during the initial SFDC implementation. Typical sources for these records are your internal billing or financial system as well as existing contact management systems like ACT, Goldmine, Outlook or even Excel spreadsheets from marketing or other functions. If the records are believed to be old, say greater than 18 months old, or substantially incomplete, then a decision should be made on their value and whether to import them or not. The SFDC import wizards do a good job entering batches of records.

? If you have account data coming from multiple sources then you should consider applying deduplication logic to avoid migrating redundant records into SFDC. You can license deduplication software tools from SFDC partners like Demand Tools, RingLead, and Active Prime, or you can use project oriented services such as InsideScoop's Customer Cleanse service if you don't want to maintain software over time. Customer Cleanse can also match account records to the D&B DUNS # (see description below) which will add any missing record data elements, update the latest data on revenues and employees, and append (add) additional account records to your criteria. The result of these efforts is a critical mass of complete, unique, and accurate account records.

? Another solution for consideration is to automate how lead, account and contact data is viewed and saved within SFDC by the end users. Sales users are often asked to conduct research on Internet based websites, such as Hoovers, and then copy/paste desired data into SFDC. InsideScoop's Customer Connection service is sForce certified against the SFDC API and provides data from market leading data providers such as D&B within the SFDC screens. With one mouse click users can save lead, account or contact data they wish directly into SFDC. All background research about accounts and contacts is now provided within SFDC providing large time-savings and account intelligence to sales. In addition all the standard SFDC lead, account and contact fields can now be consistently filled in with data to assure 100% record completeness. Marketing can now get data attributes such as SIC codes and industry categories filled in automatically for lead records by having integrated data sources.

Medium SFDC Customers:

(Moderate sales cycle complexity and record volumes, typically 10k to 50k records)

Challenge: Cleansing account and contact data coming from multiple sources. Companies with this range of users typically have lead or account records coming from former contact or CRM applications like ACT, Goldmine, or Siebel when deploying SFDC initially, or a billing/ERP system, a web site, and purchased lead lists while in production. As a result the prevalence of duplicate records increases significantly especially after a few years of accumulating data. Manual procedures for deduplicating records one at a time do not scale well when you have 20k to 150k account records to manage. Matching redundant account records using a company name and address can be difficult given different legal, "doing business as" names, or trade names in use for a company site.

Best Practices: Implementing an account naming data standard and an automated process to eliminate duplicate records will enable a SFDC customer to manage the record redundancy issue for large volumes of records. One of the best data standards for company names, addresses and related information on a global basis is D&B. They spend $250M a year to manage and update a "DUNS Number" for 80M organizational sites globally.

The DUNS # is a unique 9 digit number associated with an organization's name and address. This number has become the de facto standard amongst businesses for tracking organization sites, much like the social security number is the unique ID for US citizens. There are DUNS #s assigned for companies as small as a 2 employee private startup up to the entire site hierarchy for the world's biggest public companies, governments, non-profits and educational organizations.

D&B is able to track from the DUNS # both legal and tradestyle names for a site, the physical and mailing addresses, economic metrics like revenue, employees, SIC codes and industries, as well as corporate linkage to provide a few examples of company data available. The corporate linkage feature can indicate the level in a family hierarchy, ex, global ultimate, headquarters, division, etc., and pull together as many tiers as needed under the global ultimate site. Hewlett-Packard has 761 linked sites within their US operations alone! Interested parties can see how corporate hierarchies look in SFDC through the white papers or free trials of Customer Connection offered on our website, www.insidescoop.com.

There are several benefits to using the D&B DUNS # data standard:

? Companies using the DUNS # can link related company names together, ex the legal name with various tradestyle names, ex HP, and have the option of using one naming convention going forward.

? The DUNS # provides a unique ID for driving the deduplication process before importing batches of records as well as by looking at the lead, account and contact records already in SFDC.

? A company selling to Fortune1000 global conglomerates like General Motors, Deutsche Bank, and Sony Electronics can now get access to the 1000s of sites reporting into the global ultimate site, with the hierarchy viewable within SFDC.

? Contacts and related financial or installed base data can now be linked to a specific site within SFDC. The linking of data attributes tied to the same site enables creating composite records of valuable customer intelligence for marketing or sales use.

InsideScoop's Customer Cleanse service is based around the D&B DUNS #, and can be used for cleansing data before it's entered into SFDC, or cleansing existing data within a production SFDC system. The service maps and transforms data from D&B so the data is meaningful to SFDC users. For example, existing account records can now be linked together to view corporate families within SFDC. Lead records that are added from D&B can be applied against territory mapping rules to determine the lead owner, as another example.

Large SFDC Customers:

(Complex sales cycle and large record volumes, typically greater than 50k records)

Challenge: Companies with years of CRM program experience strive to gain a competitive advantage through their Salesforce.com investment.

These companies realize that having access to the right data is a key ingredient for achieving this competitive advantage. If marketing defines a target market or set of accounts for sales to concentrate on, they can embed the prospect records for that market within SFDC. This allows sales to focus on selling into accounts that will be most receptive to your product or service. With the prospect records for a target market loaded into SFDC, management can generate penetration reports demonstrating the progress being made into these markets.

This sounds like a logical process, but executing this process has challenges. A database provider will sell you a file with these prospect records then you or some expensive consultants have to figure out how to map the data to the proper SFDC fields. Even companies with large budgets have not been able to solve this process easily.

Best practice: Marketing and sales management need to identify the common attributes behind those customers where your sales force is gaining momentum selling your product or service. These attributes should be used to define a target market and the prospects in that market that are mostly likely to be receptive to your product or service. The common attributes used to define these prospects are their size (ex, employees or revenue), industry (ex, SIC or NAIC code), geography, or corporate linkage (ex, divisions of Johnson & Johnson). Market leading database providers like D&B can supply the prospect records to these sort criteria. They can also "suppress" the customer records you already own so you only purchase incremental records of interest.

Here are two examples of what D&B can supply for prospect records:

? All public and private companies in the pharmaceutical industry with revenues > $100M in the US and Canada.

? The global, domestic ultimate and subsidiary sites for IBM in the top 13 industrialized European countries.

Let's imagine two divisions of IBM in Europe have bought your product or service. With these other IBM sites in SFDC you can now cross-sell and get the decision-makers at the other IBM country headquarters and subsidiaries within the European countries you are targeting.

InsideScoop, which resells D&B data, also provides software and services in its Customer Cleanse offering necessary to transform and process D&B data into a customer's SFDC system. The DUNS # is used as the unique account ID to determine what new records are desired from an external datasource like D&B while suppressing the existing account records already owned by the customer. New lead or account records can be applied to territory mapping rules so the leads are assigned properly.

The D&B corporate linkage feature can be leveraged to build named account hierarchies using the SFDC parent/child relationships. The SIC codes from D&B can be mapped to the industry categories used within SFDC. The Customer Cleanse process dedupes and merges/purges new records relative to the existing lead, account and contact records already within SFDC. Once new records are properly loaded into SFDC then penetration reports can be run for target markets or accounts identifying the progress or gaps that sales is making into these markets.

The combination of Customer Cleanse and Customer Connection creates a complete data management solution to clean data at hand, keep it clean over time, as well as create composite intelligence about customer sites using multiple data sources. SFDC customers who are interested can get a complimentary data quality audit of their data or a free trial access of Customer Connection by contacting InsideScoop sales, sales@insidescoop.com, or going to the InsideScoop website, www.insidescoop.com. If readers of this whitepaper would like to share their data challenges or best practices with us at InsideScoop please contact the author at cbadger@insidescoop.com.

Chris Badger, CEO and cofounder of InsideScoop, has over 20 years of sales and marketing experience working for high tech firms. He was one of the first sales personnel at Clarify, an early CRM market leader, and subsequently held sales management positions for Clarify and gForce/Docent. Chris has led or participated in 5 internal CRM deployments including a salesforce.com implementation at gForce in 2001 and InsideScoop in 2003, in addition to selling CRM solutions to Hewlett-Packard, 3Com, Sony America, and Siemans Electronics. He holds an MS in Engineering Management from Stanford University and a BA in Engineering Sciences from Dartmouth College.

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Data Quality Best Practices for Salesforce.com

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