The Standard Approach to Data Management on Salesforce

In enterprise resource management practices lately, data is the heart of anything and everything you get into. Data is the fuel to power up the Salesforce instances too. Without proper data, one cannot determine where and when to invest, how to allocate your resources, and who actually works for the company, etc. Business decision making simply becomes intuitional without data.

Salesforce administrators agree to the fact that the CRM is simply worthless without trustable data. The increase in sources of reliable customer data makes it easier for the administrators to know more about the users and thereby increase the potential results by eradicating the poorly-migrated or out-of-sync data. As the organization becomes larger, data governance becomes a crucial and dedicated job. In fact, there are many ways to tackle the data problems at the bud itself to save an enormous amount of time and money.

When it comes to data management practices, the actual focus isn’t on solving the problems but preventing them. This is true to the core in terms of Salesforce administrators at organizations of varying scales. For example, the nonprofit administrators functioning under some 501(c)(3) license may need to get some donor contacts, and perfect data management will help them to clearly understand where the money comes from and how it is spent.

All types of business decisions now largely rely on data and analytics. Secure data management is also essential to facilitate insightful decision-making. Poor quality or old data may also run your business off track. So, when you are migrating your data from the existing systems, planning territories, setting the sales quotas, or trying to reach potential customers, one should ensure that every unit of customer data is clean and accurate.

When it comes to data management on Salesforce, the first question administrators have in mind is where to start? In this article, we will discuss the key steps involved in the creation of a solid foundation for your database management by eradicating poor quality data.

Steps in enterprise Salesforce data management

First step: Evaluate and manage current data quality

Data quality assessment done by professional Salesforce consultants like is an instant and effective way to get a graphical representation of the data quality in your CRM. Doing this, you not only get reports which will help you analyze the contact, leads, and accounts, and also help gain more details about the data quality and completeness. By taking the service of professional providers, you may also set up a personal consultation with a certified data governance expert.

Data duplication maybe sometimes a human error or some other times due to flaws in the program. However, having duplication in Salesforce could be painful in the long run and ultimately end up in huge costs for cleanup. Most of the time, at the initial stages, organizations don’t even understand that their data is out of date or incomplete unless they aggregate it for reporting. Salesforce data duplication management is a key feature that will let you identify any duplication and help prevent any future duplication.

Second step: Building easy to understand dashboard based on key data metrics

On the one hand, it is important to ensure the data quality, and on the other, it is equally important to have perfect dashboards too. In order to assess the performance of your campaigns or to have a quick look into your customer base on the go, it is important to have access to a perfect dashboard. Having a customized dashboard could make the real difference between achieving the business goals and missing the opportunities. For the sales teams, the key metrics to be put on the dashboard views are:

  • Estimated time of closure
  • Opportunity pipeline
  • Forecasting by each salesperson
  • Forecasting by stages
  • Different sales activity per team members
  • Lead to conversion rates

For the service teams, key metrics may be:

  • Turnaround time for case resolutions
  • Cases based on the source
  • High priority case volume
  • Top customer-based open cases
  • The trend of the case of volume on a daily or weekly basis

The marketing teams’ dashboard metrics are:

  • Leads from difference sources
  • Campaigns by region and demographics
  • Campaign wise lead conversion funnel
  • Campaigns with top revenue generation and campaigns with the least
  • Pipeline

During Salesforce implementation, you can try and get the support from experts in terms of building and optimizing the dashboards, which will make further proceedings easier for the administrators as well as the users. These experts could also guide you in terms of the best practices followed in building dashboards and customizing the reports by taking your business goals and operational practices into consideration.

Third step: Attaining a 360-degree view

Customer data is what makes a business forward, and it could be a competitive advantage for any business. Data drives key business decisions, the scope of investments, establish sales priorities, and also impacting the quality of customer relationships. Incomplete or damaged data could be a liability to a business than as an asset.

To attain a proper 360-degree view of the customer data through the dashboard, you need to bring together data from multiple sources and combine these with third-party market data, clean and customize it for your purpose, and then process it for a single insightful overview. Initially, this could be a complex and costly initiation, which may not reflect the ease of use or scalability of the standard Salesforce applications.

However, the cloud-based data management practices of modern times could help to bring data together on cloud platforms, not only to manage the customer profiles, but also to combine the huge volume of entities together like price, products, locations, and relate them together with powerful affiliations and hierarchies. You could leverage the benefits of big data tools too for this and also combine the analytical features of social networking platforms like Facebook, Instagram, or LinkedIn to combine all the social data too related to transactions and interactions to get a comprehensive view to gain relevant insights to drive result-oriented actions.

It is a fact that building a proper strategy for data management could be daunting, so it is important to build a proper roadmap to identify the possible approach where an expert data management expert could be of help.

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