Some of the great organizations I have helped design and optimize their MarTech stacks.
Does your company resonate with any of the case studies below?
The Situation
A fast-growing company needed to understand who its best users were across its multiple products. They also wanted to improve the onboarding experience of the new users and increase long-term retention.
The Intervention
Ruben met with the founders of the company to help them determine the important decisions that needed to be made. He helped them sort through technology choices, different customer segments and converting data to guide decision-making.He coached the team on how to easily convert data into actionable decisions and how to maintain data accuracy over the long term. Finally, Ruben trained all relevant stakeholders on the best practices for making group decisions.
The Results
The company can now better understand who its users are and how to improve its products. They have access to better data, and more importantly, they know how to convert it into profitable decisions.
The Situation
A SaaS company wanted to know exactly what marketing campaigns were working and where they should focus their resources. They had access to high-level numbers such as total demos booked but didn’t have enough data to answer specific questions like “which of our blog posts is driving the most demo requests?” or “what pages do our users view before booking a demo?”.
The Intervention
Ruben met with the marketing team to determine what decisions they needed to make and what existing data was available. Ruben then helped them improve their implementation of Google Tag Manager and Google Analytics which weren’t being used to their full potential.Finally, Practico provided company-wide training sessions to the entire marketing team and offered ongoing support to convert data into actionable decisions.
The Results
The marketing team has successfully adopted the data, and every team member is now able to generate the reports they need without having to go through a data analyst.They are now able to see which blog posts were leading to conversions and what call to action are most effective within those blog posts. They can also determine which channels should get more resources and which should get less.Finally, they are now able to dig deeper into the specific user behaviors that drive conversions for their product.
The Situation
A mobile consumer company was coming off a successful million-dollar crowdfunding campaign and was getting ready to release its mobile apps on iOS and Android. However, they didn’t have any data to understand how their customers were going to use these apps.
The Intervention
Ruben met with the growth and engineering to understand their technical stack and what data they will need over the next 12 months. He put together a strategy that would lay the foundation for the fast growth this company was expecting while still being able to handle its short-term needs. Ruben also helped their engineering team through the technical implementation issues and coached them on properly maintaining their data infrastructure.
The Results
The client launched their apps publicly and transitioned from crowdfunding backers to public customers. They can easily understand what is going on with their product and how their key metrics are changing from month to month.Their engineering team saved hundreds of hours by properly setting up a foundation that makes it easy to share data between tools. This also allows its growth team to get the answers they need without relying on engineering resources.
The Situation
An established payment provider had recently launched a new product as part of its growing suite of offerings. However, they weren’t seeing the kind of product adoption they were hoping for and didn’t know what decisions were needed.
The Intervention
Ruben worked with the Product, Marketing, and Engineering teams to understand what their current assumptions look like and why they weren’t making the right decisions. Then, he helped them sort through their data and coached them on the best practices around decision-making.
The Results
The client was able to validate their assumptions which helped them to redesign their entire interface. They were also able to start quickly designing campaigns to engage their users and, best of all, automate these campaigns so they could run without their input.Finally, this team proved the value of data and decision-making to the rest of the company and is a critical first step in changing the company’s overall culture.
The Situation
In early 2020, the tourism industry had come to an astonishing standstill. Planes were grounded, luggage was collecting dust, and passports were stored away for another day. Then, in the middle of the fog of uncertainty, a governmental agency reached out for help. They had a firehose of information that could help them understand the pandemic, but they needed help converting it to actionable decisions—calmly drinking from it instead of being overwhelmed.
The Intervention
Ruben helped them by starting at the end. In an ideal world, how would this information change their daily decision-making? Based on that, we worked on chiseling away the irrelevant, leaving only the most relevant metrics. We were able to narrow it down to 10 metrics from hundreds. In the dashboard itself, we built different levels of depth. People could spend one-minute reading summaries and moving on, while others could spend 15 minutes working through the data. The goal was to help people discover insights, not give them more data.The
Results
There was an instant change. The agency team went from being overwhelmed to knowing exactly where to focus their energy. Community partners felt supported. They couldn’t control the pandemic but could control their response to it. The condensed metrics allowed them to make difficult decisions without being paralyzed. Data helped them see through the fog.