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Reason #381 to Love the Data Warehouse: It Makes Finance Strategic

Introducing Cherry Miao, our new VP Finance and Data

Kashish Gupta.

Kashish Gupta

Cherry Miao.

Cherry Miao

February 14, 2023

9 minutes

Introducing Hightouch VP Finance and Data Cherry Miao

Kashish here – I couldn’t be more excited to announce and introduce our first VP Finance and Data, Cherry Miao.

Cherry comes to Hightouch most recently as a customer (👋 what’s up Headway), with a 15+ year career in finance and data —as both an investor and operator.

Hold Up: Finance and Data…Aren’t Those Two Fundamentally Different Things?

Wait til we tell you we threw in ops, too! But in all seriousness, we’re reimagining how finance and ops teams are structured, and data is at the heart of it all. It’s perfectly meta because our core product exists because of our belief that the data warehouse is the organizational source-of-truth, and that that data should be made easily accessible to any team, anywhere.

We practice what we preach. Data is central to many of our organizational workflows, from how we optimize our PLG tactics, to how we field customer requests and automate feature flags and even how we personalize on-site experiences. These use cases are varied, but they all have one thing in common: they’re built and automated from the warehouse.

Read about our vision for making the cloud data warehouse accessible to anyone, anywhere

A New Era of Corporate Finance

Finance roles have historically been associated with bean counters in some backroom. Over the past decade, that stereotype has evolved with the emergence of “strategic finance.” Or as Cherry referred to it in our early conversations: ”forward-deployed” finance.

With ready access to customer, product, and organizational data, finance can be positioned as a partner to the rest of the business in ensuring that we know where we're headed strategically and working across the organization to ensure that we get there.

This requires visibility into how all parts of the company are performing (Data), a holistic understanding of the systems and processes that support the business and generate that information (Ops), and the ability to pull it all together to comment on past performance and predict future outcomes (Finance).

In Cherry, we couldn’t have created a better candidate in a lab for this role. I’m going to pass this post off to her to share her own experience and how an early career in finance led her to become a SQL and dbt guru and a self-described “data geek.”

A Finance Leader Falls in Love with the Data Warehouse

Cherry here 🍒👋 —

Thanks, Kashish for the kind introduction! I couldn’t be more excited to be part of Hightouch and our bold mission to help everyone take action on their data. My career is a testament to what data can unlock for a business.

I started my career in finance (deep in Excel spreadsheets and financial models), and found my way to my first operating company, Lightspeed Commerce, where I got to ride the rocket ship from 60 to 800 people (and an IPO!). As we rapidly grew, the resources we relied on as a finance team (namely Excel spreadsheets) did not scale with the business.

A fun (only in retrospect 😮‍💨) anecdote is the eye-squinting/finger-crossing/breath-holding we’d do each and every time we opened “The Big File”—our moniker for the Excel file that contained revenue and invoicing details and history for our tens of thousands of customers. As you can imagine, this file got bigger each and every day, and it was critical for revenue recognition – not something you want to ever lose access to. We had simply outgrown spreadsheets.

We needed to move faster and be able to take advantage of all our data. I decided to take matters into my own hands and taught myself SQL and Kimball’s thoughts on data warehousing, unlocking my career progression to become VP of Data.

The rest, as they say, is history.

I became an early modern data stack customer with the help of some fabulous mentors (special thanks to Scott Breitenother at Brooklyn Data and Tristan Handy at dbt Labs, then Fishtown Analytics!), building our stack with Fivetran, Snowflake, and Looker.

Saving (and Making!) Money with the Modern Data Stack

Before our modern data stack rollout at Lightspeed, a significant challenge we had was our inability to relate marketing costs to eventual sales conversion and customer lifetime value. We could see our performance marketing metrics in Google Ads, which were then pushed into Marketo with UTMs, but once opportunities were ultimately created in Salesforce, we lost the trail. So, while we could capture MQLs on Adwords, we couldn’t trace the breadcrumbs on which specific ads were resulting in pipeline and conversions (let alone whether those customers eventually churned). This resulted in inefficient ad spend and a lot of guesswork and recency bias in our campaign planning.

The modern data stack changed that for us. With detailed insight into ad performance and conversions (all funneling through Snowflake!), we ended up saving 40% of ad budget by decommissioning ads that didn’t have attractive customer conversion rates. This is just one example of many on how we used data to optimize our operations.

Once we completed our Looker rollout, the biggest ask I was getting from the business was, “How do I see this in Salesforce or Zendesk?” People loved the insights, but wanted them inside the systems where they were working. Outside of allocating outsized engineering resources and becoming experts in dozens of SaaS APIs, we straight up could not do this. (So we didn’t.)

That’s where I had my first “aha” moment that business teams are hungry for a bridge between BI and action, but I couldn’t see a way to get there outside of building and maintaining a bunch of disparate API integrations.

Enter: Reverse ETL (and My New Status as “Superhero” to All of My Stakeholders)

After leaving Lightspeed, I had a stint back in investing as a VC, but ultimately realized I loved operating too much to sit out for too long. I joined one of our portfolio companies, Headway, as employee #31 leading the Finance and Data teams. We didn’t waste any time building out our data stack (with a familiar cast of characters: Fivetran, Snowflake, dbt Labs, and Looker), but we still hadn’t solved the “activation” problem in an automated way.

Then, one day a team member came to me and said, “I think this Hightouch thing could help us a lot—it helps push data from Snowflake back into operational systems and it takes minutes to set up.”

A lightbulb went off in my head from my experience at Lightspeed. Finally! Something existed to solve this incredibly powerful problem. (Little did I know I was Hightouch’s 13th customer!)

Fast forward a few weeks later, and Hightouch was improving life for teams across the business:

  • Our sales team stayed on top of buying signals and we leaned on the warehouse to power our sales commission calculations
  • Our support reps were able to easily access a “one pane of glass” view into customer history, drawing in information from production databases, Stripe, Salesforce, and Zendesk itself
  • Our data team was unlocking this massive strategic investment we had made (the data warehouse) into every corner of the business, while streamlining workflows so they had time for more strategic work

The best part is that it all stemmed from our warehouse, reaffirming our investment in our data warehouse as the single source of truth and capitalizing on the work we had already done to empower the business with analytics. Hightouch made it so simple to sync that data back to the business teams that needed it, exactly where they were used to doing their work.

It felt like cheating. All we had to do was connect Hightouch to our warehouse and our business teams were magically empowered with actionable customer data. This thing we straight up could not do at Lightspeed was accomplished in minutes because of Hightouch.

If you’re a fellow data professional reading this post, you probably get pitched a new data product every week. I know I did (and do!). But with Hightouch, something was different. The pain point of delivering actionable data across the business in a scalable, streamlined way was a well-established organizational goal since my time at Lightspeed. And in minutes, Hightouch solved that problem with an MVP use case. In the world of B2B software, this is virtually unheard of.

Ultimately, I couldn’t unsee what I saw and knew that the Hightouch team was onto something truly special, so when the opportunity arose to join, I couldn’t pass it up.

From Early Customer to Employee

As an early Hightouch customer, I was impressed by a few things:

  • Speed of iteration: This team seemingly did not stop. We’d give feedback and then it would just… appear in the app. The long-held idea that enterprise SaaS was a black box of red tape was discredited daily with Hightouch.
  • Customer focus: The entire company—from customer support, to product, to marketing, and the executive team—consistently demonstrated incredible empathy for our problems and translated that into a level of support and service that I had not experienced in my career.

Being on the inside, I can now see first-hand how the company’s culture and core values are integral to how we deliver these experiences for our hundreds (and growing!) of customers.

It’s incredibly exciting to be building a “forward-deployed” finance team, and to be doing it in an organization that has centered all of its workflows off of the data warehouse. Bolstered by ready-access to customer and product data, we have the resources we need to help guide the business where it needs to go (versus being pigeonholed into analyzing our historical performance.) In addition to building out my team, we are hiring across various engineering and go-to-market roles.

If you want to share ideas about strategic finance and the modern data stack, I’d love to talk! Feel free to reach out at, or find me on LinkedIn.

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