HeadsUp helps PLG sales teams understand how and when to sell • TechCrunch

For many non-technical sales teams at product-led growth companies, it’s hard to sift through the mound of data to discover the best way to approach paying potential customers. This is a problem HeadsUp, a product-led sales conversion engine, wants to solve. The San Francisco startup announced today that it has raised $8.5 million in seed funding, led by 645 Ventures (also an investor in SaaS companies such as Iterable, FiscalNote, and Panther), with participation by Wing Venture Capital, Firstminute Capital, and Character. Other investors include the founders of Drift, Algolia and Crossbeam, as well as major market potential clients in companies such as Asana, Amplitude and Miro.

Founded by Earl Lee and Momo Ong in 2020, HeadsUp clients include Unicorn SaaS companies. Lee and Ong were early adopters of Fiscalnote, a data-tracking SaaS company that went public recently.

During their time at Fiscalnote, the two built an in-house tool to give sales teams insight into how customers use the software. But even with the new tool at their disposal, salespeople had to spend hours auditing to find out the best times to interact with potential customers.

Lee told me that HeadsUp started with PLG companies because they often get a lot of usage cues before a purchase, but all SaaS sales teams need help understanding when users are ready to switch to paid plans or upgrade their existing subscriptions.

“Imagine you are a seller at a developer tools company. He told me that engineers hate being sold when they are still fixing and testing the product.” So sellers worry about annoying developers by promoting them before they are ready to buy. At the same time, you don’t want to ignore them during the small period of time when they are ready to interact with you to purchase the tool for their company.”

HeadsUp defines that window by analyzing a wealth of data collected by SaaS companies and helping non-technical sales reps decide which users are best to engage and when to engage. For go-to-market teams, this includes finding users stuck in activation and identifying opportunities to increase sales or risks of outage.

The types of data that HeadsUp analyzes to increase conversion rates include usage and billing data, CRM data, third-party data such as job titles, and the amount of money that users’ companies have collected.

It all goes into HeadsUp’s machine learning model, which is trained on data from SaaS companies. The ML model allows its clients to choose a goal, such as converting or preventing disruption, and then presents a result based on the historical data of their accounts.

Instead of showing salespeople all usage and customer data, which can be confusing, HeadsUp chooses four to five data points that highly predict conversion, scaling, and confusion. For example, this might include the amount of time users spend on an app, or the number of seats increased over the past month. It also provides contextual information, including potential champions and CEOs, and recent interactions within a product, to help sales representatives know how to handle prospects.

HeadsUp is especially suitable for SaaS companies with small sales teams and marketing budgets that need to find quick ways to monetize their user base. Ong points out that SaaS companies can have hundreds of thousands, or even millions of users, but still only convert 1% to 2% into paid users. Pay a smaller subset for upselling or cross-selling, and the monetization process can take months, if not years.

Ong gave an example of a user-to-enterprise sales pipeline in a company. If an engineer is stuck with a particular feature, the sales team can send a marketing email referring them to documents on how to use it. If they’re still stuck a week or two after sending the email, the sales team can call them and walk them through the process of using the feature. Then after they used it for months with good results and called their manager to use it, their organization might be ready to buy it.

HeadsUp conversion page

But getting to this point requires understanding how the customer uses the product and coordinating across multiple GTM teams. This means that they need to be able to access data and discuss when a customer will be handed over to another team (ie from marketing, to sales assistance and product support, to enterprise sales).

PLG companies can have up to tens of millions of users. Imagine that you need to understand when to engage with tens of millions of users, and then coordinate the interaction between extended and unmeasured means,” Ong said. “This coordination and delivery becomes impossible without tools and analytics.”

HeadsUp helps by providing insights into exactly when and how users are engaged, while coordinating customer touch points across sales, product, marketing, and customer success teams.

The startup will use its new funding to build its team. “Specifically, we are looking for strong scala backend engineers to work on our data process infrastructure, as well as data scientists and machine learning engineers for our analysis and statistics,” Ong said.

from San Jose News Bulletin https://sjnewsbulletin.com/headsup-helps-plg-sales-teams-understand-how-and-when-to-sell-techcrunch/