From Dust to Trust: How to Make Your Salesforce Data Better
Salesforce is like a goldmine. You own it but it’s up to you to extract gold out of it. Sound complicated? With Dreamforce in full swing, we are reminded that trusted data is the key to success for any organization.
According to a Salesforce survey, “68% of sales professionals say it is absolutely critical or very important to have a single view of the customer across departments/roles. Yet, only 17% of sales teams rate their single view of the customer capabilities as outstanding.”
As sales teams are willing to change into high-performing trusted advisors, they are still spending most of their time on non-selling activities. The harsh reality is that sales people cannot wait to get clean, complete, accurate and consistent data into their systems. They often end up spending lots of time on their own correcting bad records and reuniting customer insights. To minimize their time spent on data and boost their sales numbers, they need your help to rely on single customer view filled with trusted data.
Whether you’re working for a nonprofit that’s looking for more donors or at a company looking to get qualified leads, managing data quality in your prospects or donator CRM pipeline is crucial.
Better Data Quality for All now.
Quick patches won’t solve your data quality problem in the long run
Salesforce was intentionally designed to digitally transform your business processes but was unfortunately not natively built to process and manage your data. As data is exploding, getting trusted data is becoming more and more critical. As a result, lots of Incubators’ apps started emerging on the Salesforce Marketplace. You may be tempted to use them and patch your data with quick data quality operations.
But you may end up with separate features built by separate companies with different levels of integration, stability, and performance. You also take the risk of having the app not supported over the long term, putting your data pipeline and operations at risk. This in turn, will only make things worse by putting all the data quality on your shoulders whereas you may rely on your sales representative to resolve data. And you do not want to become the bottleneck of your organization.
After the fact Data Quality is not your best option
Some Business Intelligence Solutions have started emerging, further allowing you to prepare your data at the Analytical Level. But this is often a one-shot option for one single need and not solving the fulfilling the full need. You will still have bad data to input into Salesforce. Salesforce Data can be used in multiple scenarios by multiple persons. Operating Data Quality directly into Salesforce Marketing, Service or Commerce Cloud is the best approach to deliver trusted data at its source so that everybody can benefit from it.
The Rise of Modern Apps to boost engagement:
Fortunately, Data Quality has evolved to become a team activity rather than a single isolated job. You then need to find ways and tools to engage your sales org into data resolution initiatives. Modern apps are key here to make that it a success.
Data Stewardship to delegate errors resolution with business experts
Next-generation data stewardship tools such as Talend Data Stewardship give you the ability to reach everyone who knows the data best within the organization. In parallel, business experts will be comfortable editing and enriching data within UI friendly tool that makes the job easier. Once you captured tacit knowledge from end users, you can scale it to millions of records thru built in machine learning capabilities within Talend Data Stewardship.
Data Preparation to discover and clean data directly with Salesforce
Self-service is the way to get data quality standards to scale. Data analyst spend 60% of their time cleaning data and getting it ready to use. Reduced time and effort mean more value and more insight to be extracted from data. Talend Data Preparation deals with this problem. It is a self – service application that allows potentially anyone to access a data set and then cleanse, standardize, transform, or enrich the data. With it’s ease of use, Data Preparation helps to solves organizational pain points where often times employees are spending so much time crunching data in Excel or expecting their colleagues to do that on their behalf.
Here are two use cases to learn from:
Use Case 1: Standardizing Contact Data and removing duplicates from Salesforce
Duplicates are the bane of CRM Systems. When entering data into Salesforce, Sales Rep can be in a rush and create duplicates that stay for long. Let them pollute your CRM and it will impact every user and sales rep confidence in your data.
Data Quality here has a real direct business impact on your sales productivity and your marketing campaigns too.
Bad Data mean unreachable customers or untargeted prospects that escape from your customized campaigns leading to low conversion rate and lower revenue.
With Talend Data Prep, you can really be a game changer: Data Prep allows you to connect natively and directly to your Salesforce platform and perform some ad-hoc data quality operations.
- By entering your SDFC Credentials, you will get native access to customer fields you want to clean
- Once data is displayed into Data Prep, Quality Bar and smart assistance will allow you to quickly spot your duplicates
- Click the header of any column containing duplicates from your dataset.
- Click the Table tab of the functions panel to display the list of functions that can be applied on the whole table
- Point your mouse over the Remove duplicate rows function to preview its result and click to apply it
- Once you perform this operation, your duplicates can be removed
- You can also register this as a recipe you may want to apply it to other data sources
- You also have some options in Data Prep to certify your dataset so other team members know this data source can be trusted
- Collaborate with IT to expand your jobs with Talend Studio to fully automate your data quality operations and proceed with advanced matching operations
Use case 2: Real time Data Masking into Salesforce
The GDPR defines pseudonymization as “the processing of personal data in such a way that the data can no longer be attributed to a specific data subject without the use of additional information.” Pseudonymization or anonymization therefore, may significantly reduce the risks associated with data processing, while also maintaining the data’s utility.
Using Talend Cloud, you can process it directly into Salesforce. Talend Data Preparation enables any business users to obfuscate data the easy way. After native connection with Salesforce Dataset:
- Click the header of any column containing data to be masked from your dataset
- Click the Table tab of the functions panel to display the list of functions that can be applied
- Point your mouse over the Obfuscation function and click to apply it
- Once you perform this operation, data will be masked and anonymized
When confronted with in-depth fields and more sophisticated data masking techniques, data engineers will take the lead operating pattern data masking techniques directly into Talend Studio and perform them into Salesforce within personal fields such as Security Numbers or Credit Cards. You can still easily spot data to be masked into Data Prep and ask data engineers to perform anonymization techniques into Talend Studio in a second phase.
Without data quality tools and methodology, you will then end up with unqualified, unsegmented or unprotected customers’ accounts leading to lower revenue, lower marketing effectiveness and more importantly frustrated sales rep spending their time for trusted client data. As strong as it may be, your Salesforce goldmine can easily transform itself into dust if you don’t put trust into your systems. Only platforms such as Talend Cloud with powerful data quality solutions can help you to extract hidden gold from your Salesforce data and deliver it trusted to the whole organization.
Whatever your background, technical or not, there will be a session that meets your needs. We have plenty of use cases and data quality jobs we’ll expose both in technical and customer tracks.