360° customer view
Product Qualified Lead (PQL)
Account Health Score Model
Redshift to Salesforce
Redshift to Google Sheets
Figma is a SaaS collaborative design tool that enables the entire design team’s process to happen in the cloud.
Figma is built around a freemium model - designers from all over the world get started using Figma for free and bring in coworkers to collaborate on the platform. They start paying as they use more of it.
This Product Led Growth has been at the core of Figma’s success and revenue growth since it launched in 2016. To capitalize on that rapid growth, in 2018 Figma launched their Organizations product and decided to build an Enterprise Sales team to drive its adoption.
That’s when Figma’s Sales Ops team turned to Census for help.
The problem the Sales Ops team faced was finding the right sales leads amongst their millions of users, many of whom weren't ready to buy. How could the company turn their rapid product led growth into a sales strategy?
Not knowing which features the customers were using made it complicated for Account Managers to know which accounts to educate and engage in order to prevent churn and/or create opportunities.
With millions of freemium users, it was difficult for Account Executives to know which customers to prioritize.
A lack of consistency in their user, team, and organization models made it impossible for Account Executives to understand which prospects were using Figma inside the organization, and for what purposes.
🎯 Create a unified account hierarchy
Figma set out to organize their users into a hierarchical account structure. Their goal was to group all Figma teams and organizations together into a single account so that it could be worked by an individual rep.
With Census, Figma automatically created child accounts for new teams and organizations, and associated them with a single parent account representing the company. When an individual from a new company signs up for Figma, Census triggers Salesforce automation to create a new parent account to represent the company, and a child account to represent the org or team. Opportunities and contacts are associated with a child account, but a single rep owns the whole hierarchy of accounts, opportunities, and contacts.
Figma went even further. Even though a rep was actively engaging with a particular account, the customer could choose to pay for the product at any time with their credit card, skipping the rep entirely. Figma used Census to incorporate payment data from Stripe into the account hierarchy, adding automation to create new Opportunities or mark existing ones as Closed Won when a credit card transaction occurs
⚡ Build 360° profiles and identify the most valuable accounts
A single user trying out Figma for an hour shouldn’t receive the same attention as a whole team collaborating together daily
With Census, Figma added internal product usage data and created a 360 view of their users directly in Salesforce. The Account Executives and Account Managers could now understand the level of engagement for each account at a glance and identify their ICP by looking for those users with highest levels of engagement.
🥇 Scoring Leads and Accounts to focus on high-value conversations
With potential accounts unified and enriched, the final step was to turn the data into action. Figma leveraged their new first & third-party enrichment data to build their own Product Qualified Lead (PQL) scoring model and a Customer Health Score model.
By using Census, Figma could now tweak both scoring models and immediately deploy the new formulas to every account so that reps stay prioritized on the right accounts at the right time, even as strategy shifts.
Finally, the Ops team operationalized that data in Salesforce to:
✅ Automate the routing of leads to AEs based on a configurable threshold and rules, all while respecting existing book-of-business owners.
✅ Generate reports for Account managers to identify healthy and at risk account.
✅ Notify Account Executives and Account Managers when customers achieve key events or milestones.
🕒 Less tools means a simpler and faster sales process
The investment in a data-driven sales process has paid dividends by increasing the productivity of the Sales team. This increase in both efficiency and productivity led Figma to achieve their sales target & raise their series C financing just a year later.
💰 Uncovering New Opportunities
🛠️ ️ Unified Data = Better Ops
Since the initial deployment, Figma has continued to improve their go-to-market machine. First, they leveraged Census to enable real time sales forecasting in Google Sheets instead of daily manual updates. Second, using their now-structured usage data and existing data sync, other teams such as the Marketing Ops were also able to deploy Marketo with a full list of customers and their activities in a matter of a few days instead of weeks.
And the best part, no engineers or custom code needed.
Start using Census today by booking a demo with one of our experts.
By using Census to send more data into marketing tools like Braze, Canva empowered its lifecycle marketing team to run segmentation experiments faster, resulting in a more personalized, targeted experience for its 125+ million users.
Watch on-demand: How Canva uses Snowflake as a CDP for Audience Segmentation ->
Design, SaaS, Product-Led Growth
Braze, Salesforce, Facebook Ads, Google Ads
Canva is a visual communications platform with a mission to empower everyone in the world to design anything and publish anywhere. It has had explosive growth with its freemium design product, boasting over 125 million monthly active users, across 200 countries. With a freemium business model, driving engagement in the product is key to a product-led growth strategy. As a result, Canva has been laser focused on delivering a world class user experience and has invested heavily in developing a data driven culture.
With a user base of over 125 million, sending targeted and relevant messages is a key priority. Data Analyst Cuong Duong partners closely with growth marketing teams at Canva to understand how different emails are performing for different segments, and uses that data to make recommendations around questions like “What emails do we send to our users? What segments should we send them to? What time do we send them?”
As its user base continued to explode by the millions, a strong need emerged for Canva’s product and growth teams to optimize personalization and segmentation. “We realized we were sending users the same thing, and we really needed to start segmenting more,” says Cuong.
Canva’s growth marketing teams use Braze (a Census partner) as its messaging platform. To get to the next level with its personalization strategy, the growth teams identified two key needs:
1. They needed to send more data into Braze
The lifecycle marketing team wanted to leverage their Customer 360 profiles in Snowflake to build segments in Braze, but this data wasn’t readily available or easy to get into Braze. “In order to collect this data we’d have to insert Braze tags into different parts of our products that we might not have wanted to,” explains Cuong. That data, however, already lived in the data warehouse. “Some of that user data was only coming in, or it was coming in most easily, into the data warehouse. We just didn't have the link to be able to send that data into Braze.”
2. They needed a way to build more complex segments and push those into Braze
It wasn’t just the availability of data that was hindering Canva’s personalization efforts. The marketing team was restricted by the limitations posed by native marketing and CRM audience builders. They needed a more powerful segment builder that could access and build on top of all their data.
“As you get to the more complicated segments, things that may require a little bit of machine learning, or even decision trees with a few rules, the logic inside Braze becomes really complex,” explains Cuong. Without any reliable way to sync these segments into Braze, the growth teams were forced to abandon their more complex segmentation ideas.
In order to get more data into Braze, Canva’s data engineering team considered building out integrations to tools like Braze themselves and conducted a thorough build vs buy analysis. “We always try to do it in-house first, because we have the people. But what we found was that not only was it time-consuming for our stakeholders to wait for these integrations to be built in-house, but the maintenance was not the kind of work that data engineers and analytics engineers wanted to do,” explains Data Engineer Krishna Naidu.
Cuong also recalls one of the data engineers sharing his findings that “it can take a lot of engineering effort and monitoring to maintain even something that appears simple, like sending data into the Braze API.”
Census supported all the destinations that Canva needed from day one. With Canva's large volumes of data, the data team appreciated Census’ incremental syncs since they no longer needed to worry about API rate limits. “Since Census only syncs what needs to be synced - changes, additions, and deletions - the volume of data sent back to Braze is relatively low,” says Cuong. This was also an economic benefit “since there’s often a cost involved with sending data back to the platform.” Census helped Canva aggregate user events and choose the frequency of syncs to minimize API costs.
Canva also valued Census’ observability and alerting features. “Being able to see statistics in terms of how many records are being synced and how long it's taking is useful for us to know,” says Cuong. Features like that are difficult to maintain in-house and often get dismissed as ‘nice to haves’ with internal integrations.
For the initial use case, Cuong tried out Census to send key segments built in SQL inside Snowflake, back into Braze. “Our first task was to figure out whether Census can sync to Braze in a reasonable amount of time for 1% of our users. I was involved in logging into Census and trying to figure out how to connect to Braze. But it was all just extremely straightforward and intuitive. There were really good instructions on the website already.”
Now data analysts like Cuong work with the growth teams to define segmentation models, turning the data warehouse into a source of truth for segmentation. Cuong describes this process as, “now it’s just a matter of making the right view, going to Census and then clicking sync. Once it appears inside Braze, I then work with the growth marketer to define how we'll test the effectiveness of that segmentation with an experiment.”
Cuong points to the benefits of using Census with Braze to optimize Canva’s messaging, “It’s helped us make the messaging flow a lot nicer and more targeted. We’re now able to create segments, for example 'is this user a hardcore presentations user or not,' and then send them emails that are part of a specific presentations campaign.”
As part of its personalization strategy, Canva is also sending curated audience lists to Facebook Ads and Google Ads for retargeting. After the success of the Braze integration, the data team saw other opportunities for leveraging Census’s automated Data Activation to improve the processes and efficiency of the team. “We actually already had an in-house solution for doing reverse ETL for Facebook and Google Ads,” explains Cuong. “There was a Python script built by an analyst originally. No one was really managing it and no one really wanted to manage it. And so we thought "Oh, this is a prime use case for Census.”
Since that initial period, usage of Census has really taken off with teams becoming self-service for their use cases. For example when Canva’s enterprise group wanted to send product usage data into Salesforce, they knew where to go. “We noticed that Census was a very good general solution for these use cases where we needed to send information about customers back to the business platforms. And so we naturally just started to use that,” explains Cuong.
Census’ simple UI has been “a really big productivity boost,” he adds, “I think that really empowers and gives confidence to data analysts to just go in and send data to these platforms to test ideas.”
Census has also enabled the data team to run growth experiments, and put their machine learning (ML) models into use much faster. “We recently built a machine learning model to estimate the propensity that a user performs a certain conversion on the site. These models help us better understand and segment our users, but it can take a while before a model gets used inside the Canva product. Now we can immediately say, "We have these propensity scores for each user. And we’re also running Facebook ads at the moment. So why don't we just use Census to test the effectiveness of this model for targeting those ads?" And so it’s an avenue for us to test the business impacts of our insights more quickly,” explains Cuong.
Overall Census helps Canva’s data team to “activate their customer data more efficiently,“ says Cuong. “As we have matured, we have a lot of data analysts coming in who are strong at analysis and insights, and don't want to deal with all these API issues and custom integration scripts that break. Census empowers data analysts to put their insights into action, and removes the need for dedicated engineering resources or time spent maintaining custom code.”
Krishna points to the time it saves his data engineering team as one of the main benefits, since “the turnaround used to be in the order of weeks to months, whereas with Census it takes minutes to hook something up.” Data Engineers like Krisha can now spend more time unlocking value from data. Krishna shares his personal experience, “I used to spend time just working on integrations, not interacting with the business at all. I would get a brief that we need a Facebook connector, spend a few weeks building it, and then it just takes away time from improving the data experience of people within the organization, which is a huge focus now. Things like performance optimization of queries and organizing the data warehouse better."
In addition to enabling data engineers to focus on more value-adding work, Krishna describes the governance benefits to centralizing the integrations for data going out of the warehouse. “Census solves two problems for us. It removes the bottleneck to get integrations out of the warehouse. It also centralizes where we look for data going out. Now we can see all the integrations out of the warehouse, and we’ve put some process around that so that external parties can easily do an audit. So it’s given us a lot more confidence.”
More importantly, using Census has unlocked a whole new data feedback loop within Canva. “Beforehand it was just getting data out and not getting much feedback. But now we have use cases where we get data out, and sometimes it's a two step process, from our warehouse to Salesforce, and then from Salesforce it goes somewhere else like Pardot. And then we get data back from Pardot and that enriches Salesforce. So the use cases are just getting more complicated, and there's more of a virtuous circle going on that we didn't have before,” says Krishna.
In addition to continuing to experiment with segmentation, Cuong and other data analysts at Canva are also excited to scale Data Activation to as many areas as possible to further optimize operations, for example prioritizing their help tickets.
Finally, the data team would like to explore one step farther and push data from the warehouse into their products, to be able to “personalize the product experience for users based on insights from the warehouse.”
Start using Census today by booking a demo with one of our experts.
360° customer view
Sources: Redshift, BigQuery
Destinations: Salesforce, Customer.io
Clearbit is a B2B SaaS company that provides tools to improve sales & marketing efforts by aggregating public data about customers. Clearbit started by offering a lead enrichment API (taking an email address and returning data like location, job title, etc.) and has since added a number of products to its suite like lead prospecting (returning contact information for leads based on a customer's target parameters).
Because of Clearbit’s multiple products, fast growth, and large user base, they needed a way to automate a lot of their own sales & marketing and personalize every customer interaction. Specifically, they needed to have a clear picture of what all their users were doing across their suite of tools and they needed this available in Salesforce and Customer.io.
That’s when the Clearbit Data team turned to Census for help.
Making sense of millions of users
The Clearbit team was generating lots of raw product usage events but they were spread across 9+ products. Each product in the suite has its own unique user identifier, which means that activity wasn’t de-duplicated. In addition, they couldn’t correlate these user activities with the data in their marketing & sales tools so it was impossible to act on the data. Here’s some specific examples of the challenges they faced:
The data team was spending a lot of time cleaning all this data to build accurate reports but none of this work was reflected back in their sales & marketing tools. This was when they turned to Census to share their single source of truth from their data warehouse to all their other tools and give their teams internal customer data they could rely on for their processes, workflows, and automations.
Make analytics models available to other tools
The first step for the data team was to build out a sustainable architecture to ingest, store, model, and analyze all their events & data. Before they could set out to unify all their user schemas and data sources, they pulled in raw data using Segment & Stitch Data into their Redshift and Google BigQuery warehouses. On top of these raw tables, they built custom logic in SQL for de-duplicating users that appear in all their Segment sources & SaaS tools. These models also generate insights & customer attributes that are useful to the business. They leverage DBT to write these models and store them in a version-controlled repository.
With Census, in less than a week, they were able to sync this model to Salesforce & Customer.io without requiring any help from the engineering team.
Now that Census was up and running, every time the data team added new metrics or facets to their customer model, they could make it available to the sales & marketing teams directly using Census' visual mapper.
Finally, the data team keeps control of the data flow from the ETL all the way to the tools which allow them to ensure data quality and accuracy.
🔗 Multi-Touch Attribution Model in Salesforce
By syncing attribution data to a custom object via Census, the data team gave the sales reps the power to see all of the leads' touch points and where in the journey they converted to a MQL or SQL.With this information always up to date in Salesforce, the Ops team could also quickly run reports and see which offers, acquisition channels or campaigns were performing the best by tying it to actual deal closed and revenue.
🔎 Hyper Granular Segmentation and Personalized Email Campaigns
With data aggregated customer data and metrics syncing to Customer.io, the marketing team can leverage that data to build granular segmentation of Clearbit’s large userbase to send personalized email messages such as:
📇 Unified 360° Customer Profile in all the Tools
Finally, Sales Representatives don’t have to keep multiple tabs open such as internal apps, BI tools and payment providers to understand how their accounts are using Clearbit, where they came from and best to grow these accounts.
Thanks to Census and the work of Clearbit's data team, the sales & marketing teams now have more data at their fingertips in the tools they use every day to understand their customers and create powerful, personalized campaigns.
The greater benefit has been how the culture of the company has changed to be more deeply data-driven and the virtuous loop that has emerged between the data team and the rest of the organization. Now that more teams rely on live data in a way that impacts revenue growth, there’s an implicit Quality Assurance (QA) feedback loop that helps the data team improve quality & accuracy.
Start using Census today by booking a demo with one of our experts.
360° customer view
Snowflake to Zendesk
Snowflake to Intercom
For every data team, having quick and easy access to information is paramount. Yet sometimes, building the infrastructure so that data teams can get a clear look at customer data is easier said than done. That’s where Loom was until earlier this year.
Loom is a video messaging software that allows users a “more effective way of communicating” with co-workers, employees, even students and teachers. Since 2015, they’ve been providing a platform to make simple, clean videos in the hopes of removing long back-and-forths over email, and even in-person meetings.
When Loom’s data engineering manager, Buddy Marshburn signed on, Loom had just begun building out their data infrastructure and were still needing to find a lot of the right tools to help move information out of the data warehouses.
That’s when Buddy found Census, and that’s when everything changed.
When Buddy was hired at Loom, he realized pretty quickly that he needed to expand on the functionality they were currently getting from Segment. “I was looking for a tool that allows you to take data captured from our product and send it to third-party sources. With Segment we couldn’t send any information outside of pure event data, which was just limiting,” says Buddy.
“For example, with Intercom, if you wanted to send a custom message based on an aggregated count of a user doing some activity or based on a specific lead score — it can't easily be done, because Segment literally needs it to be a stream of events coming in and a stream of events coming out.”
Buddy knew from experience that managing this type of data flow from the warehouse (Snowflake) to Salesforce, Zendesk, or Intercom, isn’t as simple as it could be. In his experience, it often takes several people to build custom data pipelines, which then need to be maintained and monitored independently. Which as a “‘data team of one”’ neither Buddy nor Loom had the time or capacity to take on.
“Unfortunately, a large part of our process for releasing a new feature was predicated on the use of Intercom forms,” says Buddy, “and we just weren't able to get the data from Intercom that we needed to greenlight this part of our release.”
That’s when Buddy began searching for a tool that could help him bring transformed data from the warehouse to Intercom.
When Buddy started looking, he had no idea if what he wanted even existed, so he asked around. “I reached out to the dbt community about whether or not someone had looked into solving this exact problem, and I was pointed towards Census which I hadn't heard of prior to that,” Buddy says. “I quickly looked into everything and I was like, “Whoa, this is kind of like Fivetran flipped around to the other side of the data warehouse. It's exactly what I'm looking for!”
Buddy could feel the impact that Census could offer right away. He says, “My whole career as a data scientist and in data engineering roles has been about setting up foundational architecture components, so I very quickly realized the value prop Census offered. I feel that anyone looking to send data to any of the connectors Census provides will quickly see the value.”
🌊 The Problem - A Sea of Tickets
Initially, Buddy began using Census to help Loom connect data to Zendesk, which ultimately allowed them to prioritize the increased volume of tickets that were coming in. “This was critical for us, especially during COVID,” said Buddy. “At that time, we had started offering the product for free to students and teachers, which was great, but we got a massive growth in users and subsequently tickets.”
Loom wanted to prioritize tickets based on the type of plan each user had, but weren’t able to do so initially because a single user can be on multiple plans. “You can't really use Segment for this,” Buddy says. “Ultimately this requires SQL to create a list that says, ‘you're a member of all these plans.’ Now let's take this list and map it into one single value.”
Instead, Census allowed Buddy to take this transformed data, relevant for ticket prioritization and easily populate the necessary fields in Zendesk. “I think Census basically made something that was impossible before very highly functional,” says Buddy. “Before we were diving through a sea of tens of thousands of tickets and which, without Census, was basically impossible to handle. Census solved some foundational problems that we needed to have fixed.”
💪 The Solution - One tool = More People
For Buddy, one of the biggest selling points of using Census was how it eliminated the need for adding more people onto his data team, without compromising on functionality.
In his experience, Buddy says he’s seen tools like Stitch and Fivetran, that get data into the warehouse, reduce the need for one to two people for most data teams. But Buddy says, “I think that same exact thing is true on the Census side, but maybe even more so.”
For Loom, Buddy found that Census was able to organize all of their data, which saved them time and the need to bring on more people. “Census allowed us to centralize everything in a single place. We already have a transformation layer, DBT, which takes hundreds, if not thousands of tables and maps them into a subset of them,” says Buddy. “Now, with Census, we can leverage that work that already exists as a result of the transformation layer. All I have to do is create a Census specific end-point, like a ‘Census Salesforce table,’ and point Census at that table. I don't need to do any engineering or anything outside of SQL to get all this done. Typically that would require a lot of engineering work and then maintenance and monitoring overhead.”
He also points out that as data teams grow, so does the amount of effort needed to get data out of the warehouse, which also won’t be the case now that they have Census. “That's where Census is the missing puzzle piece,” says Buddy, “because you're easily able to take all the work that a few people have done and just put it in the hands of your stakeholders.”
🔭 Looking forward...
Moving forward, Buddy sees the potential that Census can offer to a wide range of teams at Loom.
“We recently released our Loom for Teams product. So as we grow the team internally, our use of Census will become more and more sophisticated.” Says Buddy, “I'm actually nervous to walk the sales team through how well Census and Salesforce play together, because I know that's going to be like turning on the fire hose. So I’m excited to see us in the next month or two, starting to use the Salesforce integration.”
Start using Census today by booking a demo with one of our experts.
360° customer view
Redshift to Salesforce
LogDNA has provided centralized log management solutions for small to enterprise-level clients since 2015, and Jeff has been their sales and marketing operations manager since 2019.
He works alongside several different teams including product managers, revenue operations, sales and marketing teams, and the data analyst team, all to provide sales insights so that they can “know what’s actually happening” in their business.
To do this, they use a range of software to link together everything from their data warehouses to their marketing tools. For LogDNA, their stack includes Redshift, MongoDB, Salesforce, Hubspot and Zendesk.
In order to provide their customers a great experience, LogDNA surfaces all of this information in Salesforce and their other business tools. Unfortunately, this wasn’t always the case.
When Jeff started at LogDNA, he knew there was a problem getting information appropriately logged into Salesforce. “I was being asked pretty simple questions like, ‘How many customers are paying us?’ or ‘How many people signed up for a trial last week?’ ‘How many of those people converted?’ and we didn’t have a standard way to answer those questions,” says Jeff.
At one point, Jeff’s CMO asked him to begin monitoring the number of trial signups they had, and it was this simple question that started Jeff on his journey toward Census.
Tasked with hunting down trial signups, Jeff began manually checking and pulling information from Hubspot and other marketing automation tools to count the trial signups. About a month later, he started comparing his invoice data in Stripe to the data in Salesforce, which is when he began noticing some discrepancies.
“I remember it was Halloween when I first noticed,” says Jeff “We were using a manual process to correlate information when I realized the trial numbers I saw in one place didn’t match with what I saw in the other. We later found out that half the people who were signing up for our product weren’t getting into our system at all because there was something broken.”
For Jeff and his team, this meant that hundreds of new leads were signing up and immediately falling through the cracks. They knew that if these problems were happening in trial accounts, that these issues would have large trickle-down effects.
As an interim fix, Jeff set up some pretty extensive band-aids. One engineer would go into MongoDB and export information on a weekly basis, and Jeff would take the export, reformat it manually in a sheet, and re-import it back into Salesforce.
After a few weeks, it became clear how unsustainable this process was going to be. Not only did the process take Jeff and his team a considerable amount of time, but it didn’t actually allow them to reach their new leads in a timely manner. Now potential clients weren’t falling off entirely, which was good, but they were being met with days of radio silence before they were able to be processed and contacted by the marketing team.
That’s when Jeff really began looking for tools to allow them to sync the information from Redshift into Salesforce.
“I was trying everything,” says Jeff. “When we got other tools, they didn’t actually solve the problem. In fact, they were just as inhibited in their analysis as I was because the information wasn’t there. That’s when we discovered Census. The use case of taking information from Redshift and pumping it directly into Salesforce was the perfect solution for what we’re looking for.”
Jeff reached out to Census about finding a solution to automate his manual work, and get LogDNA to a place where the marketing insights he was looking for could finally become readily available.
Once Jeff and his team began integrating Census into their system, it opened up a whole new world of possibilities. Gone were the days of doing a long, drawn-out process of export, formatting, and reimporting — with Census, they were able to automate the process.
Jeff began using Census’ 1-1 mapping features to connect tables from their database, to the objects in Salesforce, “With Census, as long as it hits one of our three databases, it will connect to everything else, and it is all very simple and intuitive, even for me, and I do not have a technical background, I’m a sales guy,” says Jeff.
Next, together with the sales team, Jeff began leveraging the Salesforce reports to identify which customers were growing, who the heavy users were, and implementing product scoring to help them organize and prioritize which accounts could be high-priority in the long term.
“I was finally able to use all the functionality of Salesforce reporting, so now not only are we able to capture that other 50% of people signing up for our product trial, but we could put them through marketing automations right away,” says Jeff.
Both the sales and marketing teams leverage these product scores to give them a more thorough understanding of where each customer is at in their customer lifecycle.
“This was only possible by joining the Salesforce table and the application production table in Redshift and using Census to pump it back in,” says Jeff. “Now we get hundreds of trial signups and it’s really helping us to know they’re all really being counted, and also to prioritize which ones we want to go after. This process has changed the way we work, and a lot of the elements we have access to now, I didn’t know were possible before Census.”
🚀 The Benefits of Using Census
These days, Jeff says “Census has really been game-changing for us in terms of being able to serve our customers,” and he’s seen that especially when it comes to his sales and marketing teams.
For example, Jeff saw a big change when LogDNA started to implement product scoring. “Right now, my product analyst is using this meta data and we’re pumping that directly back into Salesforce, and that’s mapping back to Hubspot,” says Jeff. “Which means that both the sale and marketing are using these scores, and that was only possible by joining the Salesforce tables and the production tables in Redshift and using Census to pump it back in.”
In the end, what Jeff found with Census was not only an easy solution to solve his exact issues, but a team of people who were eager to help him along the way. In fact, Jeff says that one of the biggest differentiators between Census and other vendors was the level of support that Census has been able to provide.
“The support alone has been absolutely exceptional,” says Jeff. “Having the slack channel, having the whole team be so responsive, it’s fantastic. It’s been a huge differentiator that I can always get feedback right away from the guys at Census.”
🤔 What's Next?
Jeff says his current project is “totally dependent on Census,” and it's been easy to find places throughout the company that can continue to evolve thanks to the functionality Census offers.
Jeff explained a little of what’s coming down the pipe for LogDNA with Census.
“LogDNA, like most apps, doesn't have that clear parent-child account hierarchy that Salesforce expects. Users just sign up for accounts, potentially multiple times and we have to make sense of it. That means calculating usage or doing billing for a single corporate entity is hard.
Census is letting me merge that information together in my warehouse and then push that into Salesforce and programmatically create the hierarchy along the way. I can make sure I'm doing the right thing and Census makes it happen in Salesforce automatically.”
By the time he’s done, Jeff hopes to consolidate all the different accounts, which are spread out throughout their system. “And when that change comes, it’ll be game-changing for us, especially on the revenue side, ” says Jeff. “I’ll be able to simplify our process and provide everyone in sales & marketing with a better view of each customer, and I’ll be using Census to do it.”
Start using Census today by booking a demo with one of our experts.
360° customer view
Snowflake to Salesforce
Snowflake to Customer.io
Snowflake to Facebook Ads
Anyone who has worked on a small team knows that time is a precious and finite resource. While small teams are renowned for their ingenuity and hustle, with only a few people to wear many hats, most teams have the need for bespoke business logic but don't have the time to build the infrastructure or maintain it themselves
For these teams, finding pre-existing tools to help is a top priority. This was the landscape that Notion, one of the fastest-growing B2B SaaS applications which integrates ‘databases, kanban boards, wikis, calendars and reminders’ together, found itself in earlier this year.
When they realized that they needed a way to sync data from their data warehouse to their go-to-market tools, they began looking for a pre-existing solution, instead of building one themselves.
And that’s how they found Census.
Notion is an application that helps small to mid-sized teams do all their work in a shared collaborative space. “It’s kind of like an all in one workspace tool,” says Jamie Quint, Head of growth at Notion. “People use it for so many different things, but I would say the most common use case is to use it as Wiki, to be a document collaboration platform. It’s really flexible that way.”
Jamie was hired in early 2019 and has been the primary person responsible for setting up data, user acquisition, and “among other things I’m the one responsible for performance marketing for the growth product side of things.”
When Jamie started at Notion, there were only 13 other people at the company, “This means, I ended up building out most of the data infrastructure on my own,” says Jamie. “Now we’ve grown a little bit, there's one data scientist in place and I hired a performance marketing lead. But, our current setup is still pretty small.”
Jamie’s small team means that optimizing for time and value for each individual and their tools is always at the forefront of his mind.
🛤 Jamie’s Journey to Using Census
Jamie said that his journey to finding Census was a little different. “Funnily enough, when Census’ Founder, Boris, initially pitched me on it I didn't actually need it, I was like, ‘Oh, that sounds interesting. It's not quite the right time.”
At that time, Jamie said he was just starting to build out their data warehouse. Jamie explained that for him, the whole point of having a data warehouse was to centralize his data in one place and answer questions that you couldn't answer when data is divided amongst several sources. “We've put a lot of effort into getting all the data into our data warehouse,” says Jamie. “Because oftentimes that means that it’s the only place that we can answer questions accurately.”
It wasn’t until a few months later when he got to a point where that data was ready to be connected into Salesforce that he started looking for a solution.
“We were setting up Salesforce and Facebook Custom Audiences at the same time,” says Jamie. “And we were needing to sync data into those two different platforms from our data warehouse, because we wanted to export some set of users, like, ‘people who have been active in the last 90 days’ for example.”
But because Jamie’s team is so small, not having to build something custom was also a top priority. So he began trying to solve the issue of utilizing his stored data without using humans to do it. “That’s when I was like ‘Oh, Census could be useful here, let me check it out again.’ And so it was clear how Census was going to be the right fit for us at that time,” says Jamie.
💡 Why Census Was the Right Solution for Notion
Jamie says that using Census was the natural solution to this problem. “For me, Census was clearly the easiest way to do this. The alternative would be to have to manually do some engineering work and convince someone on that team to build it and maintain it, or to do it myself.”
For a small team like Jamie’s the cost alone of building and maintaining some sort of alternative was “not even comparable,” he says. “Just by the fact we knew Census existed, it was pretty clear to me that that was what we should use for this. It was kind of a no-brainer.”
💪 How Notion Uses Census Today
Today, Notion is able to use Census for a lot of different use cases. “We're currently in the process of getting it integrated into customer.io , so we can build and share user segments across our tools. We have it integrated into our Salesforce workflows, which involves things like lead scoring and understanding product qualified leads.”
But, Jamie went on to explain that using Census to integrate data into their Facebook custom audiences was one of the ways they were able to save a lot of time. “We’re able to use different segments from custom audiences and easily get them into Facebook,” says Jamie. “Now we don’t have to go through a whole time-consuming process of exporting email addresses, and reuploading them on a regular basis in order to update them. That just wouldn’t have been very feasible for us. So having an automated tool to do that was pretty important.”
In the future, Jamie says he’d like to see Notion add even more integrations. “We're already doing that a bit, but going forward, I think there could even be some use cases around exporting data into Google Sheets and using that to build persistently updated growth models, which would be really interesting.”
🔭 Looking forward...
For Notion and Jamie, Census isn’t just another tool, it allows their team to save time and focus on optimizing results. “For me, if someone was unsure about using Census, I would wonder what they would be on the fence about,” says Jamie. “It's like, do you have the problem of getting data and other tools? If so, you should definitely use it. It’s great.”
Start using Census today by booking a demo with one of our experts.
360° customer view
Account Health Scoring
Redshift to Salesforce
Using the right tools can be ‘make it or break it’ for your customer success teams. High-quality software or services can provide detailed user insights to measure how likely a potential customer is to sign on, how happy they are while using your product, and can even help them solve problems before they arise.
For Atrium’s Pete Kazanjy, he had been looking for just the right customer success tool to help gauge customer satisfaction. What he wanted was something that was quick to integrate and simple to use, with lots of functionality.
What he found was Census, which was everything Pete was looking for with the added benefit of allowing him to improve both his customer success and sales teams, at the same time.
Here’s Pete’s journey using Census:
Pete co-founded Atrium in 2016, and currently leads their customer success and sales teams. “I hate the title CRO, but that’s essentially what it is that I do, so I’m responsible for marketing, I’m responsible for sales, I’m also responsible for customer success,” says Pete.
As a product, Atrium makes sales and performance software that continuously monitors KPI’s for sales teams, “It’s like an army of sales operations analysts in a box,” says Pete. “And it makes sales managers and sales operations people look amazing at what they do.”
Pete says Atrium is different because it allows users to automate and process their data in a streamlined way.
“Typically with analytics you need to prepare the data, know what questions you want to answer, get the data in a proper place, and then build a bunch of reporting. Then you have to come back and look at it,” Pete says. “Atrium automates all of that. So it's very, very easy. ”
Before Pete found Census, he explained that he had two main pain points.
First, he wanted a clearer understanding of user data at Atrium. In the past, Pete had used a custom-build tool at his last company, called ‘Batman.’ Pete likens Batman to a very, very basic Gainsight, a user monitoring tool that could help them begin to know what was going on from a customer success standpoint at Atrium.
“It was so clunky and limited, the Customer Success people hated it,” says Pete, “but it was better than not knowing what was going on from a success standpoint for our users.”
Pete’s team at Atrium had user data from Segment going into Redshift, and they were using Tableau on top of that, which gave them at least some understanding of what their users were doing, “but it was a very, very rudimentary understanding,” says Pete.
Pete’s second pain point was a little bit more elusive. Because of Atrium’s ease of use and simplicity, customers could often miss how effective it was for them.
“Most BI or analytics softwares are sold as a big initiative, but in our case, we can just slip in very easily,” says Pete. “Now the downside of that is that we want to prove that people are getting utility. We've also always wanted to have an easy way for sales to see which people are using Atrium successfully, for example, who is trending in the right direction, and who’s turning in the wrong direction.”
That’s where Atrium was at when Pete ran into Boris Jabes, Census’ CEO, at a conference in Silicon Valley.
When they started talking about Census, Pete said that he could immediately see the appeal for his customer success teams. “Since so many people at Atrium know how to do Salesforce reporting, I knew you could do all sorts of fun stuff with Census,” Pete says. “People could literally start building castles in the sky. And that's what we did.”
Right off the bat, Pete saw that one major advantage to working with Census was how easy it was going to be to start using it and integrating it into their current system.
“It's actually a pretty similar narrative to Atrium,” says Pete.
“The way that most organizations solve this problem is to do a huge implementation process. Census didn’t need all that.”
Other tools that Pete had worked with in the past that offered similar functionality, were extremely heavy to set up. While, “the other post-Segment, post-mParticle, post-Redshift class of CS tools are simpler than Gainsight, they’re still not super easy. And then they're all very feature limited,” says Pete.
After Pete saw the ease with which Census allowed Atrium to uplevel their Customer Success teams, he began looking for ways to apply it to other teams as well.
“Then we began using Census within our sales team as well, and for us, there have been several different use cases there.” For example, Pete says that they can use the information Census sends to Salesforce to help inform on whether or not new users are taking advantage of all of their features, or even sending alerts out if pilot users are disengaged.
This has helped their sales team stay on top of how each new user is experiencing and interacting with Atrium. It’s also given Atrium a big advantage, Pete says. “From a business impact standpoint, one thing that's extraordinarily important for our sales motion is that we can sell on prospect data and that’s a huge competitive differentiator.”
Today, Atrium has continued to integrate and iterate with Census, opening whole new avenues for them. “At this point, we're doing some super sophisticated stuff,” says Pete. “Data just flows from Census into our Salesforce, and it gets used all throughout, both our sales motion and then also our success motion as well, and then all throughout the organization.”
For Pete, many of the advantages he’s seen from using Census have come down to how easy it is to use, and how much it has allowed Atrium to do.
But he says, “The reason I am in so deep with Census right now is not because I did some big specifications beforehand. It’s because they make things very simple for people to prototype and to express their creativity, which incentives them to keep using and keep iterating with the product.”
Start using Census today by booking a demo with one of our experts.
360° customer view
Account Health Scoring
Snowflake to Salesforce
Snowflake to Marketo
Correctly utilizing and managing customer data is an important part of managing customer relationships for any business.
And for a company like Fivetran, that responsibility is shared across many different people, teams, and tools, all working together to make sure that those customer relationships are fostered as best as possible.
From the get-go, Fivetran has sought data management tools to get the right information in the right places, with minimal hassle. As a data management tool themselves, you could even argue that it’s part of their DNA. That’s why when it came time to begin moving data from the warehouse to Salesforce they began using Census.
Here’s the story of how.
Fivetran is a fully managed and automated data integration provider. “We move data from any of your applications or databases, into a data warehouse where you can perform analytics,” says Garegin Ordyan, Head of Analytics at Fivetran.
“Fivetran is fully managed where we can handle all of the schema changes, any updates, basically everything under the hood, and you just get to have your data delivered to your warehouse without worrying about your pipeline breaking due to changes in the source.”
Garegin has been at Fivetran for the last three years, and has been using Census for almost all of that time, but he isn’t the only one.
Garegin’s fellow Fivetran team member, Saurabh Kapadia, Lead Salesforce Architect, also has seen Census open up a lot of doors for how Fivetran is able to use customer data to better serve their interests. Together, they represent the different ends of the spectrum for how Fivetran uses Census.
And, together, they have seen countless ways Census has brought more visibility and ease to data management at Fivetran. “Before, it was like we had a bicycle and then we got upgraded to a rocket ship with Census” says Garegin.
Fivetran prides itself in being one of Census' first customers. But before they found Census, they were using an in-house solution to move their data. “It was extremely minimal,” Garegin says. “Back in the day we used a tool that literally did one job — load the account ID, and then everything was triggered based on that. But because of that, everything happened in a very suboptimal way.”
Garegin says that while they were “able” to load whatever records they could get, it ultimately came at a cost, “We would have to cannibalize the engineering team to write some job that was just super limited. There were a lot of simple inserts, and updates were not processed properly causing duplicates. It was a broken system.”
Taylor Brown, co-founder and COO at Fivetran, brought Census to them to help get the data into Salesforce and their other applications more easily. “Taylor knew the founders of Census. He just came in one day and said, ‘Hey, we need this data in Salesforce and here's a tool that does it.’ That's how we discovered Census,” recalls Garegin. “So we started writing queries and loading a lot of data into Salesforce. And that’s when things shifted. Suddenly, we could have someone who wasn’t an engineer set up a job any way they want.”
Saurabh chimes in, “From my perspective, even though I didn’t see how the process used to work, I know that I have a lot more visibility as we are receiving data in Salesforce. Before, how the data that was flowing to Salesforce couldn’t have been very transparent. And now Census gives me a good dashboard that the same job is working and shows all the records it's bringing in.”
In fact, the increased visibility with Census is a huge benefit for Saurabh, which he touts as one of his favorite things about using the tool. “Census can tell me exactly what might be wrong,” says Saurabh. “It could be a Salesforce trigger or not having permission to a certain field. With all that information and all those records, specific details are captured in Census, which means it's easier to go and troubleshoot that data. Even people who are not as close to the data can still go in and look at what might be wrong, because Census provides a good layer of transparency into how the data pipeline is feeding the data.”
Right now, Saurabh is using Census to send data from the warehouse into Salesforce. “We use it for lead creation. For us, we need to gather and enrich the lead a little more before we can insert it into Salesforce. So, in our process, the user signs up and we refine that data before we use Census to load that lead in.”
For Garegin and Saurabh, using Census allowed them to add new functionality to Salesforce. Garegin explains that while nothing was impossible before, “It's just so much better now. The analogy that I like to use is let's say there's a store, and it’s five miles away. Before, we were walking to get to the store. It was possible, but it was a really long walk, and it was really painful. Now, with Census, we have a car. Now we can just drop by the store, even two or three times a day — it just doesn't matter. With Census we can load the whole trunk with everything we want.”
And this difference he says comes down to a similarity that Fivetran and Census share. As Garegin explains, in many ways, Census is similar to Fivetran but with the opposite functionality. Where Fivetran moves data from applications to the warehouse — Census moves from the warehouse to the applications.
“It's the same thing just in the opposite direction,” says Garegin. “But in addition, our philosophies are very similar as well. We both take something that is very complicated to do and make it extremely easy. You just set up the job and click ‘schedule,’ and then it knows what to do. It knows the difference between an update and an insert. All of the details are extremely well thought through where the user doesn't need to worry about it. I just have to click the button and I can trust that Census is going to do the right thing, even if I don't explicitly know what the configuration is off the top of my head.”
Since Fivetran has been with Census since the beginning, they’ve seen the transformation of the product throughout the years. Garegin says, “We've definitely seen a lot of progress from when we started using Census to now. They hear their customer and really think from a customer's point of view, and develop a product in a very thoughtful way.”
Garegin and Saurabh both feel that this relationship with the Census team is what really took their experience to the next level. “I've just noticed how the team at Census has been super eager to help and is always available to answer questions,” says Garegin. “If we ever don't understand something, or something needs to be changed, Census will help us resolve the issue.”
“Absolutely,” says Saurabh, “and in cases where we have identified a feature that wasn’t already there, or if we needed help in any way, Census was ready to jump in and was able to deliver that support in a very timely way. So that really helped us not only to rely on the software, but also the team.”
And that support from Census continues to help the team at Fivetran open doors to greater innovation and opportunities.
Start using Census today by booking a demo with one of our experts.
With Eric Bloedorn, Director of Product Management at Bold Penguin
With easier access to customer and product data, Bold Penguin created automatic alerts that enabled its Customer Success team to act quickly on common issues, reducing response times from 24 hours to 30 minutes.
Operational Slack alerts
Salesforce, Intercom, Slack, Mixpanel
Bold Penguin is an insurtech company supporting commercial insurance carriers and agents. They offer a quoting platform paired with a commercial insurance exchange that helps agents match businesses with “the right quote in record time.”
At Bold Penguin, the Business Intelligence (BI) unit supports teams like Marketing and Customer Success by getting them the data they need to operate effectively. As their company grew, they needed efficient ways to move and manipulate data. The company, which aims to reduce friction in procuring commercial insurance, was experiencing significant friction with making their data accessible to the teams who needed it.
The BI team at Bold Penguin was spending too much time maintaining tooling to move data out of their warehouse. Changes happened frequently on both their warehouse and operational tools, so they frequently needed to update configuration on both sides of the flow.
This left the Bold Penguin team with some challenges:
Bold Penguin’s BI team needed to get rolling without a big implementation project. They found that Census was easy enough to set up that they could do it themselves, quickly.
It was important to the BI team that other groups be able to access data and set up new connections themselves. They’d seen requests to their team become a bottleneck and wanted data access to be as self-serve as possible.
Bold Penguin values that Census “just works” for them, especially since they are trusting Census to sync business critical data to teams who depend on it. “We've asked for a couple of feature enhancements here and there, but it just works with almost no support,” says Eric.
The pricing for other tools didn’t work for a mid-sized company like Bold Penguin. They weren’t quite big enough for enterprise pricing to make sense, but needed more seats and connectors than were available with non-enterprise plans.
Census’ pricing was “very fair” and enabled Bold Penguin to get started and grow without getting a giant bill at some arbitrary breakpoint.
When a client doesn’t get a perfect outcome on the Bold Penguin platform, the Customer Success & Sales teams needs to act quickly.
Before using Census, the Sales team relied on a weekly report from Stripe to find out about a subscription renewal issue or incomplete invoice. Bold Penguin’s Product team has been able to set up live operational alerts in Slack based on logs in the data warehouse. Now, when a payment fails, account managers automatically receive a Slack notification so they can follow up and resolve the issue.
It wasn’t just the Sales team that benefited. Customer Success also gets an alert for Agent Terminal errors. By finding and resolving issues in near real time, Bold Penguin is able to ensure top notch customer satisfaction.
Bold Penguin serves clients across many different verticals – the audience for Cyber insurance isn’t the same as Commercial Auto. By syncing product usage and partner data to enrich user profiles, they can create targeted marketing campaigns that resonate with specific types of clients.
Pulling together product usage data from both their insurance quoting platform and their insurance Exchange, Bold Penguin is able to segment users based on their level of activity and the type of business they’re doing. Feeding those insights to Intercom allows them to send more relevant content and messaging to users. Eric explains, "You can go into our Intercom instance and say ‘for people with this level of activity, let's send this content. And people below that threshold are going to get different content. Census enables us to easily vary content across a variety of factors.”
As Bold Penguin scaled its Agent Terminal platform, getting accurate data to Customer Success quickly became critical. Some issues could take up to 24 hours to resolve, and much of that time was not having the right data, in the right hands, at the right time. With operational Slack alerts to team members, Bold Penguin has cut that response time to just 30 minutes.
Business users can now set up their own data connections, feeding data from the warehouse into their tools. With self-serve data, they no longer need to wait for someone to build them a connection, reducing the time before they can take action on that data. And with Census, business users can adapt their processes to new datasets on the fly.
With user segmentation done automatically using SQL, there’s no more tedious manual data entry or cleanup. The Marketing team is freed up to focus on campaigns, not tagging customer records in a CRM.
With Max Caldwell, Senior Growth Lead and Frances Fang, Senior Data Engineer
With Census and Braze, HOVER improves customer engagement through targeted messaging, finds new sales opportunities, and lives up to their values of honest and transparent communication.
SaaS, Home Improvement, Property Insurance
San Francisco, CA
Product Qualified Leads
Personalized support outreach
Braze, Mixpanel, Salesforce, Intercom
HOVER is a leading property data platform that supports homeowners, property insurance carriers, and contractors alike. With HOVER’s key product – a mobile app – homeowners can build a fully interactive 3D model of their home exterior with just a few photos taken on a smartphone.
HOVER values engaging its customers through honest and transparent communications, and wants to partner with their business customers to help them deliver the same. One focus for that has been driving homeowner engagement for their insurance customers by helping homeowners visualize projects and understand damage claims.
Running this level of customer communication requires the right messaging tools. That’s why HOVER’s Senior Growth Lead, Max Caldwell, chose Braze as their centralized messaging platform:
“It’s great to have a centralized place to send push notifications, to do in-app messaging, to send emails, but also, we’ve made really extensive use of custom HTML in-app messages and webhooks so we can go out and create customer experiences in ways that you might not normally expect.”
Improving customer engagement requires data. Senior Data Engineer Frances Fang and Senior Growth Lead Max Caldwell had partnered on this for many years. Although HOVER had a culture that encouraged data access for business teams, their data stack just wasn’t scaling to meet their needs.
Without a tool like Census to help, data engineers were relying on custom code and Airflow pipelines to get data into key tools like Braze. Not only did it take weeks to build a new integration, the team was saddled with the work of maintaining those integrations. Their Airflow integration had become difficult to manage. At one point, they completely turned it off and Max resorted to manual CSV uploads into Braze.
Although HOVER’s business teams relied on data, they couldn’t get access to new attributes on their own. Instead, they had to depend on data engineers to write new custom code. And once the custom code was in place, business teams couldn’t monitor the sync status or know if the system was working, so they needed to rely on the data team for that as well.
The data team turned their focus to building a self-serve data platform on the modern data stack using dbt, Snowflake, and Census. With a new data platform, they also invested in training, teaching business teams to add new customer attributes in tools like Braze. Unlike the custom data pipelines they were using before, the new platform is easy for everyone to understand and use. Nobody needs to write Python code in order to access data.
Even integrating Braze with Census was simple enough that it didn’t require the Data Engineering team to be involved. Max was able to connect Braze to Census himself in less than a day without writing any Python code.
Great marketing responds to customer needs. As Hurricane Ida hit the East Coast of the US, team members at HOVER noticed an uptick in people requesting 3D model measurements, a first step toward repairing storm damage.
The Marketing team wanted to reach out to customers in affected areas and let them know how HOVER could help. At that point, though, some of the data attributes they needed weren’t available. Using Census, Max and Frances had that data synced to Braze by the end of the day, enabling Marketing to launch their campaign quickly.
A major KPI for HOVER’s growth team is sales meetings. Braze was already allowing HOVER to send communications to users based on product usage milestones, but the Sales team didn’t always have the full picture because sales information didn’t flow through automatically. They were stuck manually uploading data to see which users were already assigned to a salesperson and if there were any interactions with a specific user.
With Census handling that data sync, the Sales team has the information they need at their fingertips. What’s more, they’re able to try new ideas and iterate more quickly on these communications.
That effort is paying off: HOVER has almost doubled the number of sales meetings happening on a monthly basis.
Instead of bombarding everyone with upsell messaging, HOVER targets the users most likely to upgrade. Before using Census, accessing product usage data to identify those users was a challenge. Now, they’re able to quickly and accurately identify users with a certain number of product transactions. They can then use Braze to send a targeted message highlighting a relevant upgrade feature.
Replacing all of the custom code and Airflow DAGs with Census has allowed everyone to focus on strategic work that drives their business forward. The Data Engineering team used to spend a lot of time fixing broken integration code and responding to requests for new data attributes. Now, they’re free to focus on optimization that supports the business as it grows.
There’s also more bandwidth for strategic work in marketing now that data is easily accessible and less effort is going into troubleshooting.
HOVER is already loving the way Braze lets them proactively reach out to customers based on product usage behavior. Enriching their data set in Braze using Census could lead to even more personalized outreach and drive additional growth metrics.
Right now, when new users sign up, HOVER doesn’t collect data to identify their professional role, even though that data would be a valuable way to target messages. Implementing a change to the signup process is a major endeavor, but some of that data exists elsewhere in HOVER’s data set. HOVER’s growth team is exploring ways to both get that data into Braze using Census, and also to collect that data through in-app messaging using Braze.
With Michael Lorenzos (Substack), Head of Ecommerce Growth at Bleach London
With Census sending up-to-date data to their marketing tools, Bleach London can run cross-platform promotions that target exactly the right audience segments, reducing cost per acquisition (CPA) by 20% for their prospecting campaigns.
Audience sync across platforms
Klaviyo, Facebook Ads
Bleach London began as the world’s first color-focused salon, based in London. By the start of 2020, it had expanded to several locations and a wholesale business. As in-person businesses slowed down with the start of COVID-19 lockdowns, they expanded again with direct-to-consumer hair color kits. With that shift came the need for a data stack to support the growing DTC business.
Although Bleach London was creating segments, their CRM tool couldn’t integrate with Facebook directly. That meant those audience segments weren’t available to their primary promotional channel, Facebook Ads. Instead, their Head of Ecommerce Growth was stuck uploading data manually to Facebook.
Since they weren’t ready to change CRM providers, what they needed was a way of automatically keeping segments in sync between their segmentation tool and Facebook Ads. And with Census syncing directly from the database, they can get sophisticated with the lists they send to Facebook Ads.
With manual uploads happening every two weeks, the audience and segmentation data in Facebook Ads wasn’t as up-to-date as it could be. This left the Growth team without the data they needed to run their campaigns. All their user data, however, was already in BigQuery for analytics in Looker.
When Bleach London started using Census, they set audience and segmentation data to sync automatically from BigQuery to Facebook. Now, instead of waiting up to two weeks for new data, Facebook receives the data every 15 minutes – and more frequently when there’s a change.
Bleach London saw some problems with relying on their email provider to create segments: the segmentation was based on only data from the email system, not the robust, cross-channel data that lived in their data warehouse. With Census keeping data synced across applications, they established their data warehouse as the single source of truth. When it comes to segmentation, they can now trust that segments are built using all the relevant data.
Although Census worked just fine with Bleach London’s existing email provider, they were ready to move to a different email marketing tool. The fact that Census already supported Klaviyo as a destination gave the team peace of mind. Since they’d already established the data warehouse as their single source of truth for segmentation, migration was straightforward. When it came time to migrate, Census integrated seamlessly.
By looking at customer purchase data and segmenting their audience, Bleach London is able to provide product recommendations and promotions that are more relevant. One way that their Growth team does that is by targeting campaigns based on the type of hair color a customer has purchased in the past, for example, by not sending promotions for vibrant pink hair colors to blond-only purchasers.
When Bleach London runs a win-back campaign, they want their message to reach its audience everywhere. They do this by aligning audience segments across channels – using the same audience data in email marketing as they use for Facebook Ads. That’s easier for them to do now that segment and audience data lives in a single place (their data warehouse) and syncs automatically to marketing tools.
Identifying an audience of “lookalikes” (LAL) lets Bleach London market to new customers who resemble their existing audience, expanding their reach. With better data collected from more sources, and synced to their other marketing tools, it’s easier than ever. They’re using that data with Facebook’s campaign budget optimization to scale audience testing, slicing up the customer list in new ways to create and test LALs from customer seed audiences.
With access to self-serve data, marketers can spend their time coming up with novel ways to reach their audience and creating campaigns. With Census, data is more accessible to their team than before – meaning they can self-serve rather than coordinating with a data engineer to get the data they need. Anyone with basic SQL knowledge can create a new model in Census, so there’s no lag time when the Growth team wants to look at new data or try a new segmentation idea.
With better data access and quick data syncing, Bleach London is looking ahead to even more possibilities. Their Head of Growth, Michael Lorenzos, plans to run new, creative segmentation experiments. As he says, “The possibilities for segment creation are endless.”
Learn more about Michael Lorenzos by following his substack on marketing.
With Ethan Rader, Senior Product Manager at Coalition
For Coalition, everything is about balance. Teams need access to customer data without risking data security. They need the flexibility to try out new tools and systems without costly custom integration work. Census helps them achieve that balance.
San Francisco, CA
Sync product usage data to Salesforce
Clean and deduplicate data from a variety of sources
Support new tools and systems
Coalition helps businesses address digital risk. In addition to insurance coverage, Coalition offers active monitoring and alerting to help businesses stay ahead of digital risks including ongoing scanning for vulnerabilities, personalized alerts, and 24/7 access to security experts.
That full policyholder platform generates plenty of customer usage data. The goal of their Business Systems team is to help teams access and make sense of that data in order to build excellent customer experiences.
With data coming in from a variety of sources, Coalition needed a way to clean and deduplicate data, as well as a way to sync data to the tools that each team used. This concern wasn’t only about the quality of data. Coalition also wanted to control costs associated with data integrations and avoid unnecessary API calls.
Security is another concern for Coalition: internal users need access to customer data in order to react to customer needs, but incorrect access to data poses a security risk. Simply opening up access to all customer data through their platform wasn’t an option – the relevant data, and only that data, needed to flow into other systems in order to provide appropriate access control.
Customer data is messy. For Coalition, this data comes in from a variety of sources and formats, resulting in duplicate records. Rather than syncing raw, unusable data, Census allows the team at Coalition to clean up their data and sync only what’s valuable.
In addition to cleaning up raw data, Coalition also used Census to calculate new metrics. This gives their downstream teams insights that they can act on quickly.
In any security-conscious company, deciding who gets access to systems is a big deal. Although Coalition has a robust internal platform for customer support, that platform grants more access than a salesperson needs. At the same time, salespeople need context for their interactions with customers – context that they didn’t have outside that internal platform.
Coalition solved this challenge using Census. Now, they pull out the customer information that Sales needs and sync it to Salesforce. They can continue to limit access to sensitive systems, but still get data to the team members who need it, balancing security and data access.
Every API works differently. At a company like Coalition, there aren’t dedicated administrators for each of their tools. Investing a lot of time in learning the most efficient way to build a Salesforce integration simply didn’t make sense. Census, on the other hand, is all about data integrations. Coalition could trust that a Census connector for Salesforce or any of their other destinations would be efficient and well-designed. Even apart from their team’s time investment, Coalition saved money by not making extra API calls to Salesforce.
Coalition has eliminated the need for salespeople to go back-and forth with Customer Support to get critical information. The Sales team at Coalition now has important customer data that it needs in the tool they use every day. With this data available, they’re able to talk directly to their customers’ and prospects’ needs, resulting in more effective sales calls.
Census has helped Coalition keep its Business Systems team lean and efficient. Instead of needing an entire team to build and maintain the data pipeline, Ethan Rader, Senior Product Manager at Coalition relies on Census to help him manage it himself. He receives regular, automatic updates from Census, helping him support many different use cases without constantly playing catch-up.
In a fast-growing business like Coalition, teams need the ability to choose and implement tools quickly. Whether they’re just testing out some new software or migrating to a new system, agility matters. Without Census, the Business Systems team at Coalition would need to constantly confront the challenge of how they could build integrations with each new tool. With Census, that challenge is off their shoulders.
Recently, Coalition has been evaluating whether to continue with Intercom or move over to Zendesk. Knowing that Census could support data sync for both meant that they could instead focus on other factors for the decision.
As Coalition grows, certain infrastructure will need improvements. One of those pieces is the search in their internal application. Today, Customer Support team members can’t always find the records they need because of limitations with search. Ethan Rader, Senior Product Manager at Coalition is considering how Census could be part of their updated search solution. Using Census to push new data into their search index could minimize downtime and keep the search service performant, without expending engineering resources to build that sync from scratch.
With Matt Carter, VP Marketing at Docker
As Docker pivoted its business, Census helped the team revamp its data stack to support its new direction. With a 360-degree view of their users, they’re uncovering opportunities to drive growth and customer success.
Palo Alto, CA
Support product-led growth with usage data
Identify upsell opportunities
Docker provides a platform that allows developers to collaborate without the need to build identical development environments on each machine. With their freemium model, developers can upgrade to support larger-scale applications and access advanced features like parallel builds and granular access control.
In late 2019, Docker sold the enterprise portion of its business and pivoted to a focus on the application developer audience. That pivot included a shift to product-led growth that required robust systems to process the massive quantities of data and help them learn from their customers.
With millions of active users every month, lack of data was never a problem for Docker. However, after selling the enterprise portion of their business and pivoting to product-led growth to developers, they were left with a data set that didn’t reflect their current customer base. What’s more, their custom-coded data integrations weren’t flexible enough to support new use cases.
The team at Docker knew that a solid data pipeline would be critical for their future success as a product-led growth organization. They needed to create new data integrations but didn’t want to divert engineering resources from Docker’s main mission: building software and services that help developers do their jobs well.
Teams at Docker deal with a lot of data. Not only does Docker have well over 10 million users in its product, but there’s also a wealth of marketing and developer relations activity generating engagement data across a variety of channels.
To make the most of all that data, Docker pulls it into Snowflake, their data warehouse. Once all data flows into Snowflake, their teams can count on having a single source of truth from which to pull reliable customer data.
Docker has an outsized impact on its industry. Despite its reach, it is still a small, fast-growing startup. Development teams are laser-focused on serving users and resources are limited. Lack of data access limited those teams’ ability to act on new ideas, review, and iterate.
To ensure that teams like Marketing and Developer Relations have data when and where they need it, Docker chose Census. They used to wait weeks or even months for engineering capacity to pull requests or create a new integration. With Census, a new data connection is just a few clicks away, and nobody needs to write custom code. Docker’s VP of Marketing is looking forward to creating a culture of experimentation where his team can “get good at failing smart.”
At the core of Docker’s mission is the desire to make users successful. Carter points out, “We’re not trying to sell them something that they don’t need. We’re trying to help grow their capabilities in a way that’s valuable and relevant.”
Knowing the users well enough to provide relevant recommendations depends on having a 360-degree view of each user. And each time users have another opportunity to engage, whether it’s at a conference or on their laptop, more behavioral indicators flow back into their data warehouse, further enriching the dataset.
Beyond helping the Marketing team, improved access to data also helps the Sales team. A complete view of product usage gives Sales the ability to identify upsell opportunities that are beneficial to users and have more authentic conversations.
Instead of trying to sell every user a solution that doesn’t make sense for their use case, Sales can be smart about approaching the right customers. If, for example, they identify that a certain team is frequently hitting its maximum number of concurrent builds, the Sales conversation can revolve around the customer’s real, demonstrated needs.
Without data, it’s impossible to know what works and what doesn’t. One place that Docker wanted better reporting? Its Developer Relations efforts. Docker’s single biggest Developer Relations project in a given year is DockerCon, its annual conference. In 2020 and 2021, the conference had over 80,000 registrations. Instead of letting conference information live in its own system, Docker built their conference systems to tie data directly into Marketo. With this integration, they have a much richer view of both users and prospective users.
Adding conference information to customer data profiles helps Docker see how their investment in Developer Relations affects product usage, subscriptions, and other customer behavior. They can then use this data to make smart decisions about where they invest to ensure their Developer Relations projects are driving growth.
Today, customer insights flow into Marketo and Salesforce, helping the Marketing and Sales teams experiment and make smart decisions. With the updated data stack providing a rich view of their customers, Docker is hoping to use data to drive decisions about the product itself. Using data to know their customers better will help them invest in the features that will mean the most to users.
With Matt Nicosia, Director of Growth at Crossbeam
Before finding Census, Crossbeam relied on a hacked-together reverse ETL solution that needed many hours of maintenance per month. With the switch to Census, they’re not just saving time and thousands of dollars per year in Zapier usage fees. They’re also pushing out personalized messaging to users and helping their Sales team approach the most exciting prospects with better offers.
Personalized automated messaging
Identifying upsell opportunities
Snowflake, Amazon Redshift, Google Sheets
Google Sheets, Intercom, Salesforce, Hubspot
Crossbeam helps companies make the most of their partnerships. With Crossbeam’s account mapping capabilities, its client companies gain better access to partner data. Leveraging that data can drive effective co-marketing campaigns, prioritize product roadmaps, and identify sales leads.
An example of how Crossbeam uses data activation and reverse ETL to help their sales team have more personalized conversations 👉
With Benjamin Lewinsky, Director of Sales Operations
Before discovering Census, Culture Amp struggled for years with an in-house reverse ETL solution. To move at the speed they wanted, they needed a new way of syncing data — one that made it easy for teams to access the insights that would grow their business.
Google Sheets, Amazon Redshift
Google Ads, Salesforce, Intercom, Google Sheets, Front
Culture Amp provides an employee experience platform that aims to create healthier, happier, and more productive workplaces. At Culture Amp, data is critical. With it, they provide insights to help their customers gauge employee performance, predict turnover, and understand how to build an inspiring company culture.
Ben shares that he's excited to create more advanced scoring “mini products” in addition to Culture Amp’s existing lead scoring – like churn prediction and account scoring.
With Ryan Chan, CEO
Adding reverse ETL to their data stack was a game changer for Upkeep. Better data insights drove improvements across teams, but the biggest impact was to Customer Success. Access to real-time customer usage data empowered the team to have proactive conversations with customers, increasing subscriptions and reducing customer churn.
Asset Operations Management, SaaS
Google BigQuery, Google Sheets, Postgres
Upkeep offers an asset management system for maintenance and operations teams. They offer mobile and desktop applications for logging equipment issues, tracking preventative maintenance tasks, and issuing work tickets, helping customers reduce downtime and improve facility conditions.
Ryan Chan, CEO at UpKeep, shares how his customer success team is able to prioritize conversations by leveraging a customer health score.
SaaS, Product Analytics
SaaS, ML Ops
SaaS, Productivity tools
SaaS, Productivity tools
Internet Services, Software
Braze, S3, Snowflake, dbt
Unifying customer data was one of Zip’s biggest challenges. Zip’s growth team was already segmenting audiences in Braze, their CRM tool, but they weren’t able to serve the same segmented offers in the Zip app.
Additionally, Zip’s merchant customers requested more granular targeting that they weren’t able to provide. For example, merchants wanted to run cashback offers but only to granular segments of customers.
After implementing Census, Zip was able to supercharge the marketing team with access to all their 360° customer data in Snowflake. Now, marketers only needed to build audiences in one place, and Census would automatically keep every audience fresh with scheduled syncs.
The growth team uses Census Segments, a visual audience builder, to segment customers then sync those audiences to all their marketing tools. The simple point-and-click UI makes it easy for non-technical users to activate customer data without a single line of code.
Better access to data also made Zip’s segmentation more granular and powerful. Zip can now offer detailed user audiences to their merchant customers, making their payment platform more robust and driving higher user engagement with targeted offers.
From a technical perspective, the team had these key requirements for a Data Activation tool:
✅ Sub-3-hour updating of 4 million records in Braze
✅ Robust updating of only records that have changed (Braze charges per data point updated so this is a must for cost efficiency)
✅ Friendly UI to empower product and marketing teams to control what data ships where
To model data for activation, Zip’s data team leverages Census Entities. Entities are a simple way to define trusted models in the warehouse, ensure data governance, and expose important data for business action.
Zip’s Sr. Product Manager Moss Pauly worked with the Data Engineering team to modernize their data platform and build a fit-for-purpose modern data stack. As Zip’s team was evaluating data solutions, their top priorities were seamless integration, cost scalability, and real business use cases.
Zip built out a best-of-breed modern data stack with Snowflake, dbt, Snowplow, Fivetran and Census. One of the biggest benefits for Zip was that each of these tools were the best-of-breed in their domain, yet they had tight integrations with the other components.
As compute and storage are the core of the modern data stack, choosing a data warehouse was Zip’s most critical decision. They evaluated multiple solutions extensively and ultimately decided on the Snowflake Data Cloud. Over the past 18 months of using Snowflake, Zip’s data team has been very satisfied with its ease of use, performance, and seamless integration with dbt.
Zip needed to store business logic and transforms to build data models in a scalable, future-proof way. Dependency management and documentation were both significant pain points of their previous transformation stack. They chose dbt cloud and haven’t looked back, with 1000+ models in production after 18 months. The cloud based IDE has been a game changer, and they’re also diving deep into the power of macros and incremental models.
With millions of customers, Zip’s previous stack was unable to deal with their sheer volume of raw events. Snowplow appealed to the data team because it was open source, flexible, and didn’t have a SaaS cost tied to Events/Month. Zip’s data team was explicit that they did not want a solution where cost concerns would limit what they could track, and they wanted to retain first-party ownership of their events.
With their first-party event collection solution solved, Zip knew they needed a solution for third-party data ingestion. They didn’t want their engineers spending time wrangling third-party data APIs and wanted to capitalize on standard models in dbt for third-party data sets where possible. They evaluated a few options in this space, but Fivetran clearly came out ahead. They had coverage for all their third-party integrations, thorough documentation of data structures and pre-packaged dbt transform availability.
For more, read Moss Pauly’s blog on Building a fit-for-purpose modern data stack.
No more engineering favors or tickets. Stop waiting weeks for customer data that will drive revenue.