The good news about evaluating a data quality solution today compared to 15 years ago is that it was a much easier task back then. You read that correctly. It is far more complicated today to identify the best fit solution for Salesforce data management and quality – but that’s not a bad thing. Why? Because when Salesforce first emerged into the market it did more than just shift how CRM systems work – it flipped how we deal with our data on its head.
In short, Salesforce helped us see that our data has real value and that it requires and is deserving of its own set of management tools; its own niche technology that works in congruence with Salesforce’s ingenuity.
In the beginning, a couple of data management providers emerged in the market and created duplicate management solutions along with data loading and mass manipulation tools. These needs were the frontrunners of data quality and widely thought to be the only issues to address. There were only a couple of solutions to evaluate and the needs were new, so the process of vetting a solution was not complex.
Jump ahead a few years and businesses had an even deeper understanding of data and how each person who touches it, impacts its value. This forced businesses to question if there was a better way to organize their CRM workflow and if they could make it easier for their end users to work in CRM. Organizations were realizing that data quality was not just about the data but how it was obtained, who was working with it, and how it was being used. Considering the CRM user experience as an important aspect of data quality was the catalyst for the development of solutions that streamlined the Salesforce UX.
Over time, this thought process continued to evolve and even more solutions were developed to address the increased awareness of what it takes to keep business data reliable – advanced reporting, preventative tools, data verification, analytics, and additional features in existing tools. While navigating all the options available today can be a complicated and sometimes confusing experience it’s only because we know more about what we need – and that is why the increased complexity of finding a solution is good news. We have a better understanding of how to be successful, even if it means sifting through the options to find the right one.
So, how do you recognize which provider truly understands data quality, all it entails, and delivers a comprehensive solution? How do you know which provider or solution is checking all the boxes?
First, define “the boxes” or key components to obtaining superior data quality. Keep in mind that when you evaluate solutions, you now have to consider a broad spectrum of needs and some may appear to have nothing to do with the raw data.
The 4 key components of Data Quality Management
- Data Management Tools
- End User Adoption
- Data Verification
- Data Analytics
Data Management Tools
These tools are what you will rely on for getting data into a new Salesforce instance and for the daily management and nurturing of data far after implementation. The right tool will be highly customizable but also offer out-of-the-box options to jump start use and quickly deliver on ROI. Think of it as your “swiss army” knife providing access to the correct tool for the task and circumstances at hand. The tool suite should address duplicate management and prevention, import/export management, data standardization, mass data manipulation, and last but not least, automation of your data quality routines. All-star admins know that much of their success in delivering high-quality data rests in the tools they use to manage their data.
This is what drives the value of your CRM system—people logging in, entering data, and leveraging the information it provides to execute successfully in their job. There are two elements that drive adoption. The data and the user experience. The management tools will help you provide clean data (you still need analytics and verification to really hit that nail on the head) but UX can be a bit tricky. Do you revamp a page layout or create a more specific record type? Neither.
Organizations of all sizes agree, the teams that interact with the market daily are pivotal to realizing the benefits of CRM. So, for UX, focus on your sales and service teams first. Out-of-the box CRM configuration doesn’t present data in a way that expedites their daily work. It requires those in fast-paced careers to click in and out of multiple screens to access and manage the information needed for effectively engaging with a customer—it’s a slow way to work and it won’t help your adoption goal or data quality. What will? A solution that sits in Salesforce and presents field data from multiple objects (Accounts, Contacts, Opportunities, Cases, etc.) in one screen. When your sales and service users can quickly view and edit data they rely on, they will see the value in CRM and willingly work in the system. This means more accurate data for the business and better ROI in your CRM investment.
Verifying contact data is where you will find the most benefit in data verification. Afterall, if you can’t connect with a customer or prospect, how can you possibly create or build a relationship? Staying in touch with clients and being able to reach prospects in a timely manner is critical to providing exceptional experiences with your organization. What matters here is that you can verify email addresses, phone numbers, and physical addresses in bulk and at point of capture like on web forms and POS systems. Data verification also keeps you from wasting time and money sending mail to bogus addresses, and on the email side, protects your sender reputation.
To address data quality issues efficiently, you need a wide-angle view into your data. Analytics is where you will find that visibility. Instead of running multiple queries on each object looking for issues to fix, you should run one report that surfaces the issues, like duplicates and missing or invalid data, for you. This is an enormous time saver allowing you to proactively manage and consistently deliver reliable data in Salesforce. Additionally, the right analytics will show you how your data pitfalls are impacting your business helping you to prioritize your actions and support business growth.
Validity for Data Management was created to check all the boxes and fill the 4 key needs of data quality. We want to help businesses harness the intelligence in their data and deliver the best experiences for their employees and customers.
Applications that power Validity for Data Management
- DemandTools – Data Management Tools
- GridBuddy – End User Adoption
- BriteVerify – Verification
- Trust Assessments – Analytics
To learn more about Validity for Data Management, click here.