In this episode of Implementation Stories, Alex Laverty, the Director of CS at People.ai, talks about a tool called the discovery scorecard and how it has helped their customer onboarding and implementation teams document essential information and how they use it to ensure high user adoption and advocacy later in the customer journey.
Alex discussed the following topics:
Why did the need for the discovery scorecard arise?
How can this tool accelerate time-to-value for customer onboarding, implementations, CS, and PS teams?
How can the discovery scorecard help drive and codify continuous discovery?
How can you align your entire go-to-market teams around a unified deployment, which has a lot of downstream benefits, including financial benefits?
Before we jump in, let us break down the challenge into three categories:
Discovery is never one and done! It's never just one meeting, even if it's one meeting on your timeline or implementation checklist. We know that we're always learning things about our customers that are critical for providing a stellar experience for them.
The second is redundancy. We all have had that experience interacting with customers of a service or a product, and we keep having to answer the same questions. What if someone on the team has to be away for a bit? It is like going in for surgery and having to re-explain and provide all the context to all the medical professionals you are recommended to take opinions from. Imagine having to repeat this! It creates a frustrating experience where you're the person who's carrying that information between the different steps in the process.
3. Loss of information
We all face a challenge with unstructured data when capturing customer information. How do we report on this crucial concept of discovery? And then make it easy for future teams to find that data later.
What inspired People.ai to create a tool for post-sales to capture essential information?
People.ai uses the sales process MEDDIC. An acronym that stands for Metrics, Economic Buyer, Decision criteria, Decision process, Identify pain, and Champion. These six concurrent steps emphasize selling to the right people to ensure better closing rates for sales.
MEDDIC allows People.ai to capture essential information pre-sale. Simply put, MEDDIC is a collection of different areas that a salesperson is meant to quantify or qualify.
The discovery scorecard is inspired by some of the aspects of this framework, such as:
Dividing post-sales concepts into components and sections.
Quantifying different parts of their process based on the risk, e.g., the risk to the product deployment when they don’t have the right information.
Using data for coaching and reporting- creating a scorecard meant they could capture data to engineer better outcomes. They needed essential information to focus on. They could report on how deployments are going.
Anticipated benefits of the discovery scorecard
In today's business environment, time-to-value is a critical indicator of the performance of the customer onboarding and implementation team, as well as the overall strength of the organization's processes. People.ai prioritizes reducing the time it takes to onboard customers by shaving off days, minutes, and even seconds. Every customer onboarding manager is aware of their defined deliverables on specific dates and must meet them. They know that customers are most excited to be successful with a product at the very beginning, which is why they focus on reducing their TTV. The discovery scorecard is a valuable tool that can help reduce the time it takes to deliver value to customers, ensuring they achieve success quickly.
It helps prevent time spent on the wrong conversations. We've probably all had customers we've been trying to implement our offering for, but it’s human nature to get distracted. We need to drive customers towards a goal, and the scorecard would help People.ai achieve that. It would be easier to identify areas for improvement. The discovery scorecard allowed them to talk to the product team, and communicate what type of enhancements in the product could help decrease time to value.
All-round standardization- If something isn’t going right, it helps address the problem quickly. The benefits of standardization are manifold. It helps deliver a high-quality experience for all People.ai customers during onboarding and implementation, improving overall customer satisfaction.
Identifying areas of improvement: The discovery scorecard helps them practice continuous discovery. It allows them to drive and codify the concept of continuous discovery. People.ai wanted to ensure that any groundwork or pre-work to implementation was captured. They use a pre-launch checklist that every consultant will go through to ensure they capture pieces of pre-work that the onboarding and implementation team has asked them to collect on the day of the implementation.
Identify the areas that create more stickiness with your product: Understanding integrations and the interconnectedness with other parts of your go-to-market technology creates more value for the customers.
Your team is talented enough to source ideas from each other. They'll use each other's experiences, but the scorecard allows everyone to have a very transparent conversation about where they need help and what they need to bring up in conversations with the customer.
Consistency: It allows you to zero in on a specific issue and review when you’re looking at a scorecard for a particular deployment. And figure out what needs to be done next. Driving and codifying a continuous deployment within the team allows us to approach each customer onboarding systematically. It creates tremendous benefits for the organization and our customers.
Accountability: Each consultant has clear goals and objectives for completing their goals. There are plenty of instances where post-sales teams would go through implementation, and find themselves wishing they had asked the important questions two weeks or two months prior. People.ai has built its onboarding tools with an iterative process in mind, and they are in a position to share the knowledge in a much more straightforward manner with the rest of the go-to-market teams. All the information is structured and easily captured and transferred within the CRM.
Alignment: A lot of thought goes into showing different pieces of information. Take a car dashboard, for instance! We've tried to incorporate many of these concepts into our discovered scorecard by weighing our options on how we display it. Everyone in tech knows that creating dashboards is a really important piece, not just for executives or managers, but for everyone on the team to be able to focus on the right KPIs. The discovery scorecard aligned all the go-to-market teams on unified deployment.
Behind the scenes of implementing a discovery scorecard
Every week, the People.ai team has a discovery forecast call. They walk through the discovery scorecard for an account. They dive into the specifics, and review it together. Alex insisted that when it comes to cadence regarding reporting, it's really about customizing it for the team. You'll know the heartbeat or the operating rhythm of how your team works. The most important part is that you tailor the use of the discovery scorecard to your organization's or your team's unique heartbeat, whether it is to run it by the customers or something internally.
What helps a team believe in unified deployment?
Creating a common language around constant discovery. At People.ai, it allowed everyone to understand what the goals of discovery are. There are definitely times when you might have your pre-sales teams thinking that they're asking the same questions that you are, but maybe there's a different depth. Maybe they're just using different terms. And so it results in different answers that aren't actually transferable across the team. Using common language ensured frictionless collaboration between pre-sales, implementation, and customer success.
Reducing the number of blinks when a handoff occurs. This means that you can avoid disjointed customer experience that can immediately have a negative impact on the excitement that they have. As Donna Weber mentioned in her book Onboarding Matters, the first 90 days of using your customer’s journey are crucial. Reducing the disjointed experience or those blinks just benefits our customers and us.
The People.ai team is fanatical about getting just a little bit better every day, Not letting our ideas of what it means to be perfect get in the way of getting 1% better each day. And so, by learning and making adjustments to the scorecard itself, they could influence behavior even quicker across the go-to-market teams. When they get a piece of feedback, they would go in, change the template of the scorecard, and it would immediately show impact on everyone across everyone who's filling that out.
The roll-out of the scorecard
One of the accessories to make the adoption of the Discover Scorecard successful was creating a facilitation guide. Alex says that the time they get to do a deep-dive discovery with their customers is precious. Alex usually prefers a 90-minute meeting with the customers, but having that leeway for an elaborate call might not always be possible. Some customers bristle at the fact of giving 90 minutes of their day away. So sometimes the team gets just 60, and sometimes 30! Making the most of this time is crucial for them.
When they’re running a discovery, they recommend facilitating it as an open conversation. They then transfer that information into the scorecard. An important point Alex calls out is that the discovery scorecard is not meant to be how you interact or talk about it with the customer directly. It’s just a checklist of what you need to collect from them in the order that onboarding and implementation consultants think is the best way to approach it.
The ingredients of success
Everyone in the industry is focused on reducing churn.
Now, Alex says, their team has the ability and are equipped with the right tools because they’re quantifying discovery to understand how discovery and implementation directly impact churn.
Making the scorecard fit the purpose: The People.ai team has come up with three tenets of discovery. They iterate the scorecard according to these guiding principles to ensure that discovery is not linear. They want to be able to revisit things and make it a continual process.
Being reciprocal: One of the key components of their team is their experience and knowledge in recommending best practices. So the more they learn about their customers, the more they learn about their stack, and how they're going to market so that they can provide better guidance and consultation.
The results speak for themselves: One quarter into implementing the discovery scorecard, Alex said, the results speak for themselves! They needed to have these early indicators to know they were headed in the right direction.
With their ongoing deployments, they’ve seen a 35% decrease in the time spent on discovery. One-eighth of their customer base now has the scorecard. They’re able to create more precise upsell opportunities for the customer success team. This unified approach to discovery is proving to be helpful for them downstream.
A word of caution from Alex
Everyone across the company must be on the same page about why the discovery scorecard was built. From the beginning, People.ai was clear that the discovery scorecard was not meant to be about how they interacted with the customer directly.
The scorecard is on Salesforce. It's a native Salesforce application that they install. It has tracking mechanisms within it. They can see who modified the scorecard and track it at a granular level within each of the questions. There are ways to annotate it with notes.
Make sure that the tools you build on the platforms have these capabilities, or in cases where they don’t make sure that there is a workaround to figure out how to keep logs.
Documenting learning and information is an effort that needs to be recognized internally. While it depends on your company and the culture you prioritize, at People.ai, we’re given goals, and are trusted and enabled to figure out a way to get to those goals. So, we build, iterate, and believe in the solutions we’ve built. While we do, we’re also extremely open to feedback. Feedback significantly contributes to the results that the discovery scorecard shows.
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