“Product engagement? WTF is that?!?!?”
- Software sales veteran
The SaaS business model has long challenged the need for the traditional software salesperson. The SaaS model – and more recently the push toward Product-Led Growth with its free trial and frictionless upgrade path – has called for the death of sales.
“Why do we need a sales team if a customer can try, use, and buy my product without talking to anyone?!?!?”
Of course, this has proven to be a bit hyperbolic. A high-performing sales team is still an essential part of most SaaS businesses.
With that said, this new software model has certainly redefined the way that a software sales team operates in fundamental ways.
Most significantly, the product-first model means that it is very likely that your salespeople are selling to people who have already started using your product. These prospects are either on a free trial, using a freemium version of the product, or maybe even in a pilot. No longer are your sales people selling an abstract concept to some bureaucratic decision makers. They are selling to actual users. People who have experienced the product in some way. Hopefully seen some value – or not.
This means that for any sales team to be successful in this new world of software, they need to pay attention to things they haven’t had to in the past — most significantly product engagement.
Selling to someone who has used your product is different than selling to someone who has not. In order to sell to people that have used your product, it is essential to be intimately in touch with:
If you are selling a product with a freemium or free trial experience, this information, this data, is a new requirement in the sales process. In fact, this data is the basis for a Product Qualified Leads (PQL).
Given that factoring product engagement data into a sales process is still a new concept, we wanted to outline the five things that your sales team will need with regards to product engagement data. Whether you are building your own internal systems for this or using a solution like Sherlock, this is what you team needs:
Obviously, getting the end users – in this case your sales team — access to the essential data is a fundamental part of any data-based process. But access is one thing — easy access is another thing. You need to understand the most convenient places for your sales team to consume this data. Obviously, that’s your CRM (Salesforce?) – where your sales team spends the most of their time. But don’t overlook some other places where they may like to see this data — namely Slack (and potentially Intercom). Don’t think you can throw this data into a spreadsheet and think your team will use it. They won’t.
Having access to the data is certainly necessary. But your product generates a lot of data. You can’t dump a truckload of raw engagement data from your product onto your sales team and expect them to makes sense of it. This data need to be compiled into a format that has context and is easily consumable. You should create a methodology to score and rank your users based on how frequently they are using the most important parts of your product (learn how to do that here). Doing this will allow you deliver this data to your sales team in a format they can actually use. A simple way for them to understand who’s engaged, at what level, and how recently. Again – the more voluminous and complicated the data you give your sales team, the less likely they will use it.
This is super obvious – so much so that it’s very easily overlooked. As a SaaS business, you don’t sell software to individual users. You sell to teams, to organizations — to accounts. This means only tracking product engagement at the user level is not helpful. You need to be able to aggregate this engagement data at the account level. Without this ability, your PQL process will become more frustrating than helpful and your sales team will likely abandon it.
When working a sale, salespeople are always looking for the right “entry points” into an account. They look for people who are going to become their internal champions — someone who will help sell the product internally. Therefore, having insights into the engagement of each user on an account is essential for driving a sales process. The users most engaged with the product will become “case studies” your AEs can use when trying to sell to other decision makers. This is key, key data for your sales team.
The goal of any trial process is to drive users and accounts toward “Activation.” Every product has a different definition of Activation, but it’s generally the three, four, or five specific actions that allow a new account to experience “first value.” A good PQL process will include insights into the Activation progress for every trial account. Which accounts are fully Activated? Which ones are almost there? Which ones are way off? These are all essential questions your sales team are asking and which that should be easily answered in your PQL process.
Whether they like it or not, modern sales people at modern SaaS organizations must become very familiar (and very comfortable) with product engagement data. In fact, this data is quickly becoming the most important qualification criteria for potential customers – the basis for the Product Qualified Lead. When you are selling to people who have used the product, knowing how they are using the product is simply, essential.
But it is not easy to get this data compiled in a way that it can be effective for your sales team. We hope this list of requirements provides a good start for putting together this type of system.
Over the last several months, we have moved our knowledge base to Notion. One of the last pieces we brought over was our product data schema (we used to track it in Github, then we moved it to a Dropbox Paper doc).