Alexa, CEO of Pocus, hosts Product-Led Sales (PLS) AMAs with PLS experts to share best practices, frameworks, and insights on this emerging category. These AMAs are an opportunity to ask PLS leaders any question - ranging from hiring to sales compensation to tech stack - in a low-key, casual environment.
The PLS AMAs are for members of the product-led sales community, the go-to-place to learn, discuss, and connect with GTM leaders at product-led companies. The goal of the community is to bring together the most thoughtful and innovative GTM leaders to build the next generation of sales together.
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James is a sales strategy & operations leader at MongoDB where he owns sales account strategy, sales intelligence, and sales data governance functions. James' team is responsible for building custom tools for sales teams and using data to make sales as productive as possible.
MongoDB made the switch from a largely on-prem software to a true Product-Led Growth (PLG) juggernaut over the last 5+ years. The success MongoDB has seen in the last few years is in large part due to their Product-Led Sales strategy enabled by James’ team. They are responsible for building solutions to ensure the sales team is focusing on the most valuable accounts and that the GTM resources are interfacing the right way.
Going from On-Prem to SaaS Model
MongoDB wasn’t always the PLG darling it is today. Not too long ago, the company’s primary go-to-market motion was selling an on-premises product which limited the ability to understand product usage. Over the last 5+ years, the company is now over 50% SaaS with plans to continue increasing cloud subscription revenue share.
So far James and his team have been successful at making shifts with big impacts, like:
- Migrated to a consumption & credits billing model instead of commits
- Converted sales compensation plans from ACV to ARR
- Created a closer partnership between sales and product
GTM and pricing changes impact on sales culture
Like other SaaS businesses in their space, MongoDB realized the value in PLG early and started making strategic decisions to move them towards a Product-Led model. They eventually made the shift to product-led through a new cloud product that was truly SaaS, except for one problem - their pricing model didn’t align. So James and his team had the difficult task of moving Mongo from a bookings and commits based model to a true SaaS approach with ARR as their key metric.
How did they do it? By refocusing their key metric from commits to consumption instead. James mentioned that this had a big impact on sales culture - the incentive changed from getting spend commitments to instead prioritizing getting customers on-board to the platform.
Getting buy-in on this change required a lot of education on why this is better for everyone in the long run. Customers are happier because sales are incentivized to add value and be helpful instead of just selling. Sales teams are happier in the long run because their success is now aligned with the customer's successful experience with the product.
Building bridges between sales and product
James spent time understanding what the sales teams needed to be successful with Product-Led Sales and selling Mongo’s enterprise cloud products. The answers were all the things you would expect - MongoDB wanted to:
- Acquire customers
- Retain customers
- Expand customers
- Understand the health of customers
- Know what features customers are adopting
James knew he had the data to support these initiatives and could really impact the sales team’s goals. Initially, there were thoughts of sending all free tier leads to sales; however, after reviewing with the growth and product teams they realized that they could be more efficient.
The realization was that the product had a series of aha! moments - the milestones that users hit determined whether they’d be happy customers or churn. This was a KEY learning unlocked by building a closer relationship with the product team. Had James gone and sent all of that data to sales without first aligning to these milestones, the sales team would have gotten overwhelmed and developed alert blindness to all of this data.
By working with the product team James was able to define a customer journey for sales that is more conducive to adding value for customers than just trying to reach the sales outcomes.
PLG + Multiple Customer Stakeholders
While PLG has all of the benefits we know and love (less friction, better products, etc.) there are some trade-offs. One of those tradeoffs is the benefit of understanding the complexity of an account and its various strategic goals.
For example, in a typical outbound process, sales teams have the benefit of running a discovery call where they can uncover a variety of stakeholders and strategic goals. On the flip side, in PLG, sales teams get the benefit of a user going straight into the product - gets value and in return, the sales team gets access to valuable product usage data. But, in the PLG scenario, the sales team misses the qualitative understanding of the custom’s strategic goals and stakeholders.
So, how does MongoDB think about this problem? Are they targeting a less complex buying center with fewer stakeholders? Are they solely using the product data to prioritize outbound efforts?
Prioritization and goal setting across customer-facing teams
James’ short answer to the above questions - it’s definitely NOT going after less complex buying centers. He says “it’s complicated” but it comes down to having clear roles, with clear goals, and equipping the sales teams with the right data to prioritize efforts.
At MongoDB the customer-facing teams are split into 3 buckets:
- Sales Team
- Customer Success Team
- “The Cloud Team”
Each team has an overriding goal that gets to the heart of the question here, which is how do you manage both a PLG go-to-market and complex enterprise sales within one organization.
The nature of the MongoDB product is that sales teams can’t force any customer to use more database consumption than they need. That is not sales’ goal here - the sales team at MongoDB is always focused on finding and acquiring the economic buyers within an account, finding the key product champions, and trying to uncover where there could be workloads for MongoDB.
Sales is focused on the acquisition goal and Customer Success picks up the retention goal. CS is more focused on customer health, how customers use the product, and their overall satisfaction.
The Cloud Team
The Cloud Team was born when MongoDB built out its SaaS business and PLG motion. This team is focused on expansion. They work with customers across the vicarious phases of their MongoDB journey but focus on both:
- De-risking churn for new customers to make sure they are set up and enabled to use the product properly
- Identifying proactively more mature customers who could need more help with their MDB implementation
Finding high potential customers
One of the longer topics of conversation from James’ AMA was how to find these golden opportunities, especially with an open-source product.
Uncommon ways to uncover high-value customers
In addition to product data there were some other interesting ways James’ team was able to identify prospective customers.
James suggests looking for these signals:
- Companies with job descriptions that contain skills requirements for MongoDB or similar products
- Companies with a high ratio of developers/engineers to total employees
- Data on stealth startups (use a tool called harmonic.ai) who may need to start spinning up databases and heavy workloads soon.
Identifying PQLs and routing
Should all PQLs go to all sales reps or is there a way you should segment them for the sales team’s consumption?
James and his team see it a little differently. Their sales team, as mentioned above, is segmented based on which part of the funnel is their focus. So if certain PQLs fall into a certain part of the funnel, that will determine how the lead gets routed.
Today this information is routed to the sales team via Salesforce or Tableau dashboards. James and the team are always experimenting with this data and how to best surface it to the sales team. James and his team work directly with the data team to make it all happen. The CRM is their home today and a lot of this is built into Salesforce but he admits that they are moving faster than Salesforce can accommodate.
- Partnering with Product early on can be an asset to sales leaders when making the switch to PLG. Sales leaders need to understand the value moment in the product so they can look out for the right signals in the data (and avoid data overload).
- When selling a complex product or to multiple stakeholders, PLG can still work as a GTM motion, but you have to shift your mindset from doing upfront discovery to using data to inform how you drive value for customers long term.
- Having clear charters and goals for your customer-facing team will help you better define the data they need to prioritize their accounts.
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