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In her Propel23 session, Alisha Hardoon, Senior Manager, Customer Success & Onboarding at Robin, shared her experience with implementing a data-driven approach to onboarding.
In this session, Alisha talked about:
Here are key takeaways from the session.
Wherever possible when it comes to data driving your process, favor answers that are based on metrics like CSAT or TTO (Time to Onboarding) so you can track changes over time and see trends.
If you're just getting started, the best way is to define the questions for which you need answers and start from there.

The CS team at Robin identified three priority questions that shaped their data onboarding approach. These questions focused on:
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The team conducted multiple in-depth discussions and feedback sessions with the team.
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The team used Figjam to do this since it made it easy to work with in-office and remote employees.
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The discussions focused on breaking down onboarding milestones, identifying what worked, and pinpointing areas for improvement. By analyzing their data onboarding trends, they prioritized the most critical pain points and created an action plan.
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The final result was an internal summary and project plan with designated owners, status, and timelines that detailed how the team was going to address the priority points.
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To understand how the customer felt about the onboarding experience, the team sent out a survey (using Google Forms) at the Onboarding Review milestone.

The feedback form included scope for both quantitative and qualitative responses so that users could give their ratings and add any additional context. In addition, this survey exercise also sought/identified product advocates for further marketing about advocacy opportunities.


The survey findings gave the team raw data that they translated into internal documentation to

The team tracked the time taken from the partnership kickoff call to the onboarding review meeting to capture the TTO (Time to Onboard) metric.

They found that their actual TTO was several months beyond what they expected (and communicated to customers).



The team’s original onboarding journey was designed to onboard customers quickly. But the data showed that they had ended up doing too much too soon at the start, and overwhelming customers. Additionally, users ended up bypassing the optional training at the later stage of the journey, which caused downstream usage issues. Lastly, the team realized they’d overlooked a formal celebration of the success of the project.
With the insights from their data, the team made the following changes to their onboarding process:

The team put together a best practices guide for Onboarding Managers that detailed the activities, tasks, and behaviors expected from the onboarding team.

These best practices had an explicit focus on enabling and empowering the team to identify and flag risks.

The Robin team also used the insights and findings to develop playbooks and best practices to deal with stalled accounts.

“Speeds up CSV importing and saves me from having to get customers to use a template file or create mapped data exports. Quick to integrate and flexible outside the happy path. We found defining workbooks and templates confusing; at a prior job it was configured through code, which I preferred.”
Source: G2 review


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70–85% utilization. 94% G2 rating.
One platform does what the entire table above tries
to split across tools.
70–85% utilization. 94% G2 rating.
One platform does what the entire table above tries
to split across tools.

70–85% utilization. 94% G2 rating.
One platform does what the entire table above tries
to split across tools.
Enterprise implementations fail because customers don’t follow the process or provide clean data on time. Most delays are purely “customer-side” issues.
Implementations fail because complex environments need real-time technical problem-solving. FDEs unblock workflows, integrations, and unknown constraints that traditional onboarding teams can’t resolve on their own.
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Companies that embed engineers directly with customers see significantly higher enterprise retention compared to traditional post-sales models — because embedded engineers uncover “unknowns” that never surface in ticket queues.

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A Forward Deployed Engineer (FDE) embeds in the customer environment to implement, customize, and operationalize complex products. They unblock integrations, fix data issues, adapt workflows, and bridge engineering gaps — accelerating onboarding, adoption, and customer value far beyond traditional post-sales roles.






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