Tag Archives: duplicate data
Lockton is the world’s largest private insurance broker. Their goal is to achieve 95% client retention. The company, which operates in 60 countries, successfully adopted Salesforce to empower 4,450 associates to continually improve cross-sell and up-sell to existing clients.
To succeed, the director of operations at Lockton knew that the associates need to know who their customers and prospects are and which products and services they already have. When he investigated, he found several customer information gaps in Salesforce.
Below are five customer information gaps in Salesforce CRM that can impact sales:
Gap #1: Which customer record can I trust?
Before reaching out to a customer (let’s use fictitious client Mark Niles), the sales rep needs to access Mark’s contact information in Salesforce. Chances are Mark Niles’ customer information is spread across multiple duplicate lead, account and opportunity records with inaccuracies, inconsistencies and incomplete information. For example, potentially four records exist in Salesforce for one customer 1) Mark Niles 2) Marc Niles 3) M. Niles 4) Mark. The customer information gap becomes worse when a company has multiple Salesforce orgs. Sales dilemma: Which Salesforce customer record can I trust and update?
Gap#2: Which products and services does my customer already have?
Before a sales rep can identify which product or service to offer Mark Niles, she needs to know which ones Mark already has and if he has any outstanding issues. Chances are Mark Niles’ product information is stored in enterprise systems such as SAP, Oracle or JD Edwards ERP, customer support systems and maybe cloud applications such as NetSuite and Eloqua that are not integrated with Salesforce. Sales dilemma: Why can’t I access all relevant customer information from my Salesforce customer record?
Gap #3: What is impacting my customer right now?
Sales reps want to be up-to-date before reaching out to customers. They may need to go outside of Salesforce to get information such as credit scores and news announcements that may impact the timing of customer contact and the conversation. Sales dilemma: Why can’t relevant third-party data be included in my Salesforce customer record? (more…)
We often hear from our Informatica MDM customers about the main benefits they’ve realized from master data management (MDM)—smarter, faster decision-making and greater productivity though timely and reliable data. What’s less widely recognized is that MDM is proving to be a powerful cost-saving engine, as well.
For instance, a global investment bank saved millions of dollars by using Informatica MDM to virtually eliminate maintenance and support costs for a complex web of point-to-point integrations. If you’re using or considering MDM, it’s a smart idea to assess the costs of unintegrated data systems and examine cost-saving strategies and tactics available through a multidomain, model-driven MDM solution.
We’ve just published a new white paper, “Seven Ways to Reduce IT Costs with Master Data Management,” that drills down into using MDM to target the redundancy, waste, inefficiency, and unnecessary maintenance and licensing typical of a heterogeneous data infrastructure. A sampling of these seven critical areas includes:
- Interface costs: How you can minimize costly point-to-point integrations that support key business processes
- Redundant third-party data: How you reduce acquisition costs of duplicate data from third-party providers such as Dun & Bradstreet or Acxiom
- Data cleanup: How you can efficiently centralize data quality to eliminate expensive manual efforts (more…)
One of the most critical first steps for financial services firms looking to implement multidomain master data management (MDM) is to quantify the cost savings they could achieve.
Unfortunately, a thorough analysis of potential ROI is also one of the steps least followed (a key culprit being disconnects between business and IT).
This shortcoming is spotlighted in a new Informatica white paper, “Five Steps to Managing Reference Data More Effectively in Investment Banking,” which outlines key questions to ask in sizing up the cost implications of bad data and antiquated systems, such as:
- How long does it take to introduce a new security to trade?
- How many settlements need to be fixed manually?
- How many redundant data feeds does your firm have to manage?
- How accurate and complete are your end-of-day reports?
- Do you have the data you need to minimize risk and exposure? (more…)