Welcome to Insycle Insiders, a series of short conversations with customers who have overcome data management issues with Insycle.
We interviewed Bill Martinez, former director of business operations at The Guarantors and current head of CRM and marketing operations for OneUp Growth.
Before turning to Insycle, lease guarantee company The Guarantors struggled with unwieldy data full of duplicates and riddled with standardization issues. The company’s data was spread across three different CRMs—HubSpot and a homegrown CRM app that pushed data to the other CRMs—which complicated efforts to fix the problems.
The local New York company offered both lease guarantees and deposit replacement services to thousands of renters in the New York area, and was working to expand its operations to other cities. But its growth was stymied by its data issues.
The multitude of duplicate records in the system caused confusion and hindered the sales team’s lead pickup times, reducing the likelihood of closing deals. Standardization issues, particularly in location data such as states, meant that some records were not picked up by their automation triggers. As a result, many leads were not routed to the appropriate place.
This is the story of how Bill and The Guarantors were able to untangle this complex web, leaving them with clean, consistent, deduplicated data across all three CRMs.
What do The Guarantors and OneUp Growth do?
The Guarantors is a rental assistance company that was expanding out of the New York area. So, like a rich uncle who might co-sign on an apartment for you or help you with a down payment, The Guarantors helps renters get into their apartments. We served B2C and B2B, working with renters and landlords as partners.
One Up Growth is a marketing consulting organization. My role in the organization is helping companies integrate primarily HubSpot and Marketo and Pardot with Salesforce.
What problems were you looking to solve at The Guarantors?
I had been tasked with overseeing our implementation with HubSpot. As part of this effort, it was my job not only to migrate the data and keep it consistent but to clean it up and make it usable, solving several problems that data issues were causing in the company’s operations.
While this was happening, the company was also expanding from the New York area into different parts of the United States, including Boston and San Francisco. This meant a big influx of data into our CRM systems from these new territories, bringing with them a range of issues.
We routed any prospects that came into the pipeline. So if a person came in, depending on what region they were from, they would be routed to a specific account executive. If data didn’t come in properly or if the logic on the flow wasn't correct, then the account executive was not notified.
”You want the account executive to get new landlords onto our product, and then you want that client success person to minimize churn. You really want to get churn down. When we started putting staff members on database maintenance, we realized that people were investing way too much time in generic maintenance.”
The biggest thing was we had multiple administrators importing into the database. They were using the out-of-the-box HubSpot import feature that doesn't really have the technology to look for duplicates, so that data would just blindly go in.
We had many duplicates in our databases. But the fact that we had to balance a homegrown CRM with HubSpot presented many challenges. The out-of-the-box duplicate feature wasn’t powerful enough.
“If the data didn’t come in properly, the workflows would not be triggered, and then sales would not be notified that a prospect had filled out a form. This led to leads being contacted late. Unstandardized data impacted lead routing.”
We also had issues with standardization—city and state fields. A state like New York may be represented as the acronym, NY, or as its full name, New York.
We needed to make sure that the data in our CRM was consistent so that our HubSpot Workflow automations could be reliably triggered when they needed to be.
If the data didn’t come in properly, the workflows would not be triggered, and then sales would not be notified that a prospect had filled out a form. This led to leads being contacted late. Unstandardized data impacted lead routing.
How had you dealt with these issues before?
We started throwing resources at it. So not only did we develop operations resources, but account executives started to become responsible for helping maintain the database. And we also started adding individuals from the client success team as well.
But these teams were unhappy and felt like it wasn’t their job. We were spending way too much time on data maintenance. Without a lot of motivation to fix these issues, we were forced to take an outside-the-box approach.
“It was countless hours of people investing time in doing things like marking a duplicate contact or using the out-of-the-box features to merge. It was time and energy that was being stolen from account executives trying to close deals. It was time and energy from our client success folks, making sure that people aren’t churning. It was my job to find a way to get time back for those folks.”
So, we scheduled a data maintenance pizza party. We’d order a lot of pies from a local pizza shop, and our sales team would get together from 6 to 9 p.m. and collaborate on data maintenance. Needless to say, they were not happy with this arrangement.
Team members would spend hours verifying that contacts were real, identifying the correct email address or phone number, and updating the data in the CRM by hand or through the standard CRM tools. It was a lot of collaboration and manual work. But even that wasn’t enough to keep up with the issues flowing into the CRM.
It was countless hours of people investing time in doing things like marking a duplicate contact or using the out-of-the-box features to merge. It was time and energy that was being stolen from account executives trying to close deals. It was time and energy from our client success folks, making sure that people aren’t churning. It was my job to find a way to get time back for those folks.
We only had two of these data maintenance pizza parties before deciding to find a better solution.
Was there a tipping point where you realized that you needed to find a solution to these data issues?
Yes. While the data-cleaning pizza parties were not hugely successful, another tipping point came from The Guarantors expanding.
“With the GDPR, duplicates are not a good thing. A person may opt-out on one of the records, but then you can accidentally send them a notification on a duplicate record.”
All of a sudden, we are in new territories with new laws. We have CAN-SPAM and GDPR compliance to take into account. With the GDPR, duplicates are not a good thing. A person may opt out on one of the records, but then you can accidentally send them a notification on a duplicate record.
Brand reputation was another concern. We partnered with landlords. Their tenants were customers of our customers, and we wanted to treat them with the utmost respect. If you were a high-value tenant—and New York City rental prices are very expensive—we wanted to ensure that we were not sending out messages that would frustrate the landlords.
We needed to ensure that our data was accurate and reliable.
How did you discover Insycle?
I reached out to HubSpot, and I was like, “Hey. I need a tool to do this. What are the recommended tools out there?” Our HubSpot rep got back to me pretty quickly and Insycle was on that list.
“One of the things I like about Insycle is that you can schedule a template to run continuously, or you could run it in real-time. You could run the template on one specific scenario, or you could run it on all your cases at the same time. So you have that flexibility. You can cherry-pick what happens.”
Then we evaluated Insycle and signed up for the trial. I remember when the health assessment came out. I was so excited to evaluate the health of the database. We tested the trial and signed up, and I am still a customer to this day. Love it.
How did you use Insycle to solve these problems?
Deduplication is one of the biggest features that we use. What I like is that you can schedule the operations to run when you would like. So it's not like an admin has to go in there and build out the logic for the deduplication each time. Scheduling and getting a report on every merge that takes place—that's amazing!
One of the things I like about Insycle is that you can schedule a template to run continuously, or you could run it in real time. You could run the template on one specific scenario, or you could run it on all your cases at the same time. So you have that flexibility. You can cherry-pick what happens.
We also run previews, where you generate a CSV file report that tells you what the winning master record would be. I also use it for normalizing data—New York, New Jersey, abbreviations versus spelled-out states. That can be scheduled as well.
I also like that Insycle not only connects with HubSpot, it does Salesforce and it does Marketo. It's very impressive.
“Unfortunately, sometimes in the homegrown app, our team will accidentally enter a company with the same name and the same address, just with small alterations. So it's a human-made accidental duplicate. But we can't delete it from the CRM because this homegrown app pushes data to the opportunity and contacts in the CRM, and removing it breaks the integration. But through Insycle, I can fix this problem.”
I mentioned earlier that we integrate through a homegrown CRM app, and that homegrown app has a special key. What'll happen is, if we merge two records, and those two records have unique IDs in the homegrown app, it'll break connectivity. So when our homegrown app tries to talk to the CRM, it won't be able to update the record.
To merge records, we tell Insycle, "if this ID exists, don't merge these records,” because our homegrown CRM needs this information. Then I'll create a report with those duplicates and we'll audit it manually instead of merging in bulk.
Unfortunately, sometimes in the homegrown app, our team accidentally enters a company with the same name and address, just with small alterations. So it's a human-made accidental duplicate. But we can't delete it from the CRM because this homegrown app pushes data to the opportunity and contacts in the CRM, and removing it breaks the integration. But through Insycle, I can fix this problem.
You can build what fields are important to you. Let's say you're trying to merge an account—a “sold” account versus one that’s not active. You can evaluate your fields and prioritize which are most important, and then design a definition of the ideal company that should be the primary record.
Some of the rules we use to determine winning records in merges is how many contacts are associated with the company, how many other companies are associated with the company, or how many deals are associated with the company. The more deals and contacts, the more activity history they have. We view that as the ideal gauge of a winning record in a merge.
How does data maintenance help improve revenue operations?
I think from a revenue operations perspective, it impacts downstream systems like our homegrown CRM. We talked earlier about our homegrown app, and I think it allows us to continue to clean the database, but put those safeguards in so that we're not recklessly updating data.
As an administrator, if my sole mission is to merge duplicates, Insycle allows us to build in safeguards that say, “In these specific conditions, let's not merge them. Let's evaluate them. Let's see if we can go to the source system and merge them.”
Because what happens is that if we delete a company in our homegrown app, those deals can't be associated to that company in the CRM. There's a risk that our sales folks may lose that deal because there’s just no transparency to it. So it really is hard dollars that we are saving. It’s a long-term strategy.
How did your teams feel about the improved data quality?
Our sales team was happy because there were fewer duplicate records in the database. And the product team is worried about getting deals and opportunities into the database. Improved data quality protects them because it allows them to continue to do their job.
“Keeping a clean database as your system of record is critical for reporting and analytics. Having this data cleaned up in the CRM is also important because when we’re making decisions for the business, with the way our economy is going, it is more important than ever to tackle this situation head-on versus letting it continue to pile on.”
There's also the marketing side of the house. When you're doing lifecycle tracking of a contact but have duplicate records, then you never have an accurate record because it’s split up among duplicates.
Any data management best practices to share?
Data management is more important than ever due to budgets shrinking. Everyone knows in 2023 money is going to be a little bit tighter. Having your data buttoned up impacts things like how quickly leads are being picked up so that you close deals.
Keeping a clean database as your system of record is critical for reporting and analytics. Having this data cleaned up in the CRM is also important because when we’re making decisions for the business, with the way our economy is going, it is more important than ever to tackle this situation head-on versus letting it continue to pile on.
