Today, I wanted to spotlight a role that connects data to business outcomes by unifying and streamlining Revenue teams and processes. Manuel Passanha is a Revenue Operations Manager at Unbabel, an AI-powered, human-refined translation software company based in Lisbon, Portugal. I had the pleasure of speaking with him to understand more about his path, his Revenue Operations world, and how he leverages data to inform business decisions and unlock growth.
When I started my career at Unbabel 3+ years ago, I was part of a team of junior analyst interns sitting within the Revenue team. We reported into the Director of Revenue Enablement at the time. We worked hand-in-hand with AEs, BDRs, and CSMs to help them more efficiently close deals through greater visibility into their leads, pipeline, active deals, and even previous closed deals and past performance.
The best way to succeed was to become an expert in our source-of-truth Revenue tool, our Salesforce CRM, and to develop the ability to quickly deliver answers to questions in dashboards and reports. Whenever the business team needed answers (back in a time when we went to the office every day), I enjoyed literally sitting next to them to understand what information was useful to them. Over time, I learned exactly what information they would want/need when they request certain data - and became a whiz at diving into Salesforce to fetch the right information to deliver as much value as possible.
This role was considered an entry-level ‘starting point’ at the company, and I’ve since seen my fellow former analysts branch out to pursue all sorts of different interests across the company: Solutions Consulting, Sales, you name it.
As for me, I had my “lightbulb moment” 4 months in, with the realization that I was right where I wanted to be. I had found my superpower in Salesforce, analytics, and helping my colleagues reach their goals with data. Salesforce is intimidating at first, but after a few months of in-depth discovery and use, I found that I was able to easily answer all the questions that came my way. I could effectively translate business questions and navigate the Salesforce maze to find that answer. I had a knack for it, and an eagerness to keep learning and growing in this path.
Now, I’m a Revenue Operations Manager, and the go-to guy people come to for business data.
My main job is to bridge the gap between the mountains of data that exist across our Revenue tools (mainly in our Salesforce CRM) and our revenue goals - supporting the revenue team in making better decisions based on data.
I’m also responsible for driving efficiencies in our sales process and ensuring high-quality data in our Salesforce CRM. These are a few of my current responsibilities:
The main metric that everyone is most concerned with is ARR (Annual Recurring Revenue), and answering the ongoing question: “what’s changed in our ARR, and why?”
Here are some other questions that I often get:
To deliver on these metrics, I leverage the reporting and dashboard features within Salesforce, complemented by Google Sheets. The Salesforce dashboard is limited to 20 reports, so Google Sheets can be more effective in certain cases.
Even though my title is Revenue Operations, I do consider myself a data analyst - I use data analysis on a daily basis to identify trends and answer questions around sales data, customer data, and other financial data. I only deal with data that’s generated across Revenue teams in Sales and Customer Success tools, which is why I focus primarily on Salesforce. My job is to unify and interlock the teams so everything works smoothly together and we have a well-oiled “Revenue machine.” While I’m data-savvy and work with numbers, I’m not technical and not a coder (no SQL).
At my company, the Revenue Operations team is separate from our data engineers who sit on the product side of the business. In addition to my manager (new Head of Revenue Operations) and myself, we’ve hired a Revenue Operations Analyst and a Marketing Operations Manager, so we’re a team of four.
On the product side, we’ve used Chartio in the past to track product usage, but we are currently transitioning to Looker as our data platform, with a BI specialist working with our data engineer to set that up. In the future, I imagine Looker will be our go-to source of truth for revenue as well, and I hope they can consolidate our data in a way in a clean, accurate way, but I’m curious how things will evolve once the transition is complete. It’s taken a while to implement, and for now, there are inconsistencies between the data I’m working from (Salesforce) and what’s appearing in Looker, so we still have a ways to go.
Maintaining data quality, which is an ongoing and oftentimes tedious process. I like to compare it to having to clean up a dirty house. If you stop cleaning for a month, or even a few weeks, the clutter will pile up. The importance of high-quality, accurate data needs no justification - without it, we may be reporting on stale, outdated, or downright wrong data. This could lead to key business decisions made around insights that aren’t backed by truth. One of the anxieties that comes with the role is: “is this data that I’m presenting to the CEO 100% accurate?” You know that you’ve done your best, but there’s so much in there, how do you ensure it’s all clean? There’s no one else to double check or verify that for you, so it feels like it’s all on you, and there’s a lot of pressure.
Data quality always has to be top of mind as inputs can be misleading, such as someone creating a Salesforce Opportunity a couple days before it was closed-won, even though their actual sales cycle for that deal was 5 months. You have to manually exclude that as an exception or find a way to not have it mess up your average sales cycle.
At first, it can be really nerve-wracking, but over time, you start to create automations that can prevent “messy” data from piling up. A small example: there was clunky data in Salesforce around the business teams inputting an account’s HQ country in different ways. We’re currently working on implementing a formula field where every time someone writes one of the country name variations, it auto-populates as one consistent format. This way, we’ll be able to ensure clean data without asking business users to change their behaviors.
Cleaning up data can be a very manual job, and for that reason, it’s given to interns and analysts that tend to be straight out of university. I think that’s why there are so many entry-level analyst roles. When you’re suddenly having to deliver data that informs key business decisions for the CEO, however, it’s a bit mind boggling that it’s not treated with higher importance.
The more familiar you are with the data, what’s going on in Salesforce, and the initiatives you’ve done to automate, the more confidence you gain. Don’t forget that you’re the Revenue data expert here, and you really are the only one with answers, so you’re doing your best with the tools that have been given to you.
Another tough aspect of the job is that it’s highly reactive**,** and there’s always more work to do than you’re able to take on. ****I’m eager to make progress on some of our bigger projects and initiatives (data cleaning, strategy, or reviewing the efficacy of our tech stack), but there are weeks where we don’t have the time or bandwidth to touch them. What comes first is always business requests. Particularly if it comes from leadership, I drop everything to work on their request. After all, the data may help with a critical business decision.
Firstly, there’s a new challenge every day! It’s like I’m in a video game, where every day presents a new obstacle that I need to solve to get to the next level. One issue we had was how to ensure that a lead is always connected to an account within Salesforce. This is a manual process that’s often not filled out by the business team. I solved this issue by auto-populating the account name based on the lead’s email address. When you prevent even a small future headache, that’s a win. Looking at the things that are now put in place to drive efficiencies vs. how things were in the past is definitely satisfying.
Secondly, I love bridging the gap between data and business growth. We all know that the gap exists. As the cliché goes: “If you’re a people-person, you’re not a numbers person, and vice versa.” I take pride in truly embodying both. Some data teams are stuck in the weeds, and don’t have a comprehensive understanding of the business goals or context. I enjoy being the person that can always explain the data from a business POV, and is super close to the AEs and their deals. I also happen to be someone that enjoys the social component. I love getting on calls to problem solve collaboratively, and don’t shy away from it.
Lastly, this is both tough and satisfying, as many achievements are. As one of two Revenue Operations members at the company, a lot of where I am now is self-taught, which is rewarding and motivating. I still have a lot to learn, but it makes me proud of where I am. I now get to work cross-functionally with Sales, Customer Success, Marketing, HR, and Finance, and oftentimes, get to ‘save their day’ with the work that I deliver. It feels super impactful and appreciated.
It’s absolutely critical to understand the business context of everything. Otherwise, there’s no value to your analytics. Don’t build anything without understanding what you’re working with (metrics, definitions - what they mean), and the purpose of the request/question. If you don’t have a close or collaborative relationship, work on building that open line of communication. If they need data from you, have them explain ‘what’ and ‘why’ around their request. Then, it’s up to you to figure out the ‘how.’
I’d love to have a bigger team so we have enough bandwidth to consistently handle the never-ending flow of requests from business teams, while also making steady progress on our strategic initiatives that will positively impact the business, or drive overall efficiencies.
While I enjoy working this closely with the business teams, having an intuitive and self-service analytics tool would also be a great way to free up some of my time, so I can focus on the bigger initiatives I mentioned.
Lastly, there are moments where I find myself thinking, “If only I was here from the very beginning of when we started using Salesforce…this would be so much less painful.”
Eventually, I would like to build a Salesforce CRM from scratch, so I can think about every single field and how to enrich and automate it, as well as understand the impact of it.
At the moment, I'm really satisfied with the impact I have in my current role, and I'm looking forward to continuing to learn and grow every day!