As companies continue to harvest more sales data, finding ways of cleansing that data at scale is becoming increasingly important. According to LinkedIn’s latest report, 56% of sales reps are leveraging data to select high-quality leads, while roughly 50% use it to inform sales strategy like which industry to target. In other words, data is deeply embedded into the sales process, and sales data constitutes a large chunk of the business data architecture (which sits at +340TB for the average company).
It’s natural to feel like all of this rich sales data is incredibly valuable and therefore should be kept available forever. You invested significant time and effort into collecting this high-quality data, so there’s an ongoing temptation to hoard all of this data thinking that it will always be useful. Unfortunately, failure to sunset old data can tax systems, distract the business both strategically and operationally, and even corrupt incoming sales data. As we round out our sales data lifecycle series, let’s touch on data archival and deletion — two overlooked yet critical components of the lifecycle.
Prioritizing Sales Data
In general, sales data in your organization falls into four buckets:
- Active data in Salesforce, buckets, blobs, and databases
- Mission-critical data requiring backup
- Compliance-driven data and possibly relevant data requiring archival
- Stale and unusable data requiring deletion
So, which data is which? How do you know when it’s time for data to enter the terrifying jaws of deletion, and what types of data make sense for archival? While it’s tempting to perform the “data lake dump,” you can’t possibly keep every bit of data you collect. Some of it has to go. As the old adage goes, “garbage data in, garbage analytics out.”
Every piece of unusable data presents a tangible challenge to your analytics platforms, business intelligence operations, and Salesforce ecosystem.
If data doesn’t solve a business problem, delete it. It’s that simple. So, let’s say you collected 500 emails from a white paper download 5 years ago. Chances are, any of the emails that have yet to respond are viable for deletion. Yes, nurturing is important. No, you shouldn’t keep nurturing a 5-year-old no-reply email that downloaded a single white paper. That email is hogging storage, impacting analytics, and creating opportunities for confusion. It has to go.
But what about customer details that could still present value but aren’t currently in play? What do you do with them? You archive them! In other words, shove them into a box for future use, but don’t keep them floating around in your primary data systems. Choosing between backup, archival, and deletion isn’t always easy. And you need to build robust data deletion guidelines to light the way. Like governance policies, data deletion guidelines are largely organization-specific. So, this is an area where you may need help. At Delegate, we provide end-to-end data lifecycle consulting, and we have years of experience building amazing sales cleanliness strategies.
4 Ways to Solve the Data Cleanliness Crisis in Salesforce
You have bad Salesforce data. Yes, you. Businesses lose $3.1 trillion annually due to poor data quality, and the average company can expect to lose over $9.7 million annually in lost opportunities due to data quality issues. When we turn our heads towards Salesforce, it’s easy to see why poor data quality is such a widespread issue despite intensive data harvesting. Missing data, duplicate data, outdated data, inaccurate data, and corrupted data cost you leads, opportunities, and revenue every single day. A few pieces of outdated data can wreak havoc on a personalization campaign, and a couple of duplicate emails can completely disrupt that hyper-targeted LinkedIn ad blast. In other words, your business has a Salesforce data problem — whether you know it or not.
Don’t panic. This is a fixable issue. Here are 4 tips to help you maximize your Salesforce data ecosystem.
1. Define a Standardized Data Deletion Plan
Standardization is everything. Without standardization, data deletion becomes a spray-and-pray madhouse. You need fine-tuned darts with autopilot engines. 70% of CRM data becomes stale each year. You need to identify this data and guide it towards safe deletion practices. Generally, this involves assigning a team to data cleansing, leveraging best-in-class data cleansing and deletion technology, annual health checks, and plenty of documentation.
We also recommend forward-thinking data capture processes (see Part 1). If you can define why data is captured in the first place, you’ll have less to delete and maintain on the back-end. This is a big part of what we do at Delegate. We often help clients develop standardized and tech-forward data cleansing and deletion processes. It’s hard to give concrete, step-by-step advice on setting this up, unfortunately. Every company is unique.
2. Understand Compliance Requirements
Certain data needs to be deleted, retained, and archived according to specific compliance requirements. These requirements may include GDPR, CCPA, LGPD, HIPAA, or a variety of other industry-related rules, laws, and standards. It’s important to note those standards and bake them into your formal data deletion plan.
We understand the complexity of adhering to these regulatory guidelines. Most sales teams want to keep data forever. It represents power, conversions, and analytics. But even high-value data can sit in the dead-center of deletion crosshairs if required. For example, GDPR gives users the right to deletion. That deletion may impact sales, but it’s not your data — it’s your users’ data.
The easiest way to approach compliance is to rethink what data means. Instead of looking at data as this faceless mass of analytical power, remember that each data point routes to a real person. And that person should have a say in how their data is handled. At the end of the day, 81% of people believe the cons of data collection outweigh the pros. Build a transparent and trustworthy business that’s willing to delete when the time is right.
3. Educate and Organize
Every salesperson is responsible for data cleanliness. Not only do salespeople need to understand how to input data in the appropriate ways, but they should be aware of the follies of duplicate data and mismanaged data. At Delegate, we always set up systems that prevent data duplication from the start — not the end of the cycle. But employees still need to understand when and why to archive or delete data. Training is the key.
In line with this thinking, keep documentation of data archival and deletion processes. Don’t let tribal knowledge sneak up on you. Yes, implementing a team responsible for data cleanliness is great. But you still need documentation to prevent frictions if they leave.
4. Perform Regular Audits
Bad data will slip through the cracks. When it does, you need to catch it. One of our favorite practices is data audits. You would be amazed at how much your poor Salesforce data is costing your company. It’s mind-blowing. Audits aren’t great at catching specific data errors (you need specific tools and processes for data monitoring), but they are fantastic at catching trends. Let’s say you have a field that isn’t properly formatted. That field will cause a cascade of poor-quality data. Audits catch those errors. Tackling the trends is huge. Most bad data comes from specific and identifiable issues. The small portion that comes from bad form fills, and spelling errors are best left to data cleansing tools.
Build a Better Salesforce Data Ecosystem
Over the course of this series, you’ve learned how to create, capture, maintain, store, analyze, report, archive, and delete sales data across the data lifecycle. Now it’s time to put it into action.
At Delegate, we help businesses build world-beating sales ecosystems. Are you ready to take the next step? Contact us today!