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In this session of Implementation Stories, we spoke to Tami Titheridge, Product Engagement & Support Lead at Kapiche, an analytics product that helps customers make sense of customer feedback data to improve decision-making and positively impact their bottom line.
Tami talked about:
... and more.
In the rest of this article, we share the key takeaways from the session.
Kapiche is an AI-based analytics product that helps companies understand large volumes of unstructured customer feedback at scale.
The CS team at Kapiche currently comprises three roles: a CS director, a product engagement and support role, and a technical account manager to handle technical consulting, analysis, etc.
Customer onboarding at Kapiche is a high-touch process. It depends largely on the needs of each customer and the datasets each customer uses to collect feedback from their customers.
Typically, the goal is to get a new customer up and running in 30 days (though some companies can complete onboarding in less than a week).
The three stages of a typical customer onboarding journey at Kapiche are:
The biggest challenge was navigating the different responsibilities within the team to maximize efficiency and avoid any overlaps. The best way to do this, Tami recommends, is by understanding the workflows and having different parameters for different responsibilities.
Knowing where each team member’s time is spent and identifying the areas that need specialization can help identify exactly how the team needs to grow.
To dig deeper into adoption, the Kapiche team worked on developing a Product Engagement Score. To do this, they focused on:
For three months, Tami spent two hours every week manually validating users on a spreadsheet using the FullStory tool to pull the metrics of each customer and pop them into different elements of the product.
This was later refined into a dashboard that pulls different metrics for each customer to analyze them at both company and user levels.
Each analyst using the product at the customer end gets a score. The exercise also highlights the parts of the product that aren’t being utilized effectively.
It helps the team fill gaps by creating hyper-targeted messaging for users. For instance, a video informs them of the features they’re not using, what they can use them for, and how to use them.
Over time, this exercise has helped the CS team understand which accounts have account management issues beyond specific product area issues and need attention.
An effective way to find the right tools for the job at hand is by focusing on identifying exactly why you're looking at a tool instead of looking at a tool and seeing where you can use it.
Once you’ve had a look at the requirements, classify them as ‘must-have’, ‘nice-to-have’, and ‘can compromise’ before you look at tools.
Next, understand the key tasks that team members are involved in, and specifically, are facing challenges with. This could help the team:
a) Understand the roles they need to hire for
b) Find the right tools for themselves
Here’s what Tami recommends:
Lastly, Tami recommends applying the ‘hire slow, fire fast’ approach to tools. Don’t hesitate to get rid of a new tool if you don’t find that it works for you—even if you’ve done intensive due diligence before investing in it.
4 Ways Rocketlane Makes Customer Onboarding Smoother, Simpler, Smarter
Besides scaling the team and making product changes to reduce the onboarding duration, the team also has some specific ideas on the challenges they want to address for customers. This includes building visibility to understand:
Like what you read? Join our private, invite-only Slack community and attend the next Implementation Stories session. You will also gain access to peers and share knowledge on customer onboarding, implementation, and customer success.
“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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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.





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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