Hook Blog
Published in

Hook Blog

Why I started Hook

I’ve spent a lot of time in my career buying software. In the early days of my career when I ran IT Operations for an investment bank, we used almost every product we could find. The main challenge I faced with every new product that I bought was the significant gap between the demo and ultimately getting value out of a product.

When I moved to being a CTO of one of the world’s fastest growing software companies, seeing first-hand the challenges faced in helping customers drive adoption and get value made me very passionate about fixing it using data. I’d seen data be used effectively in the pre-sales process and in my previous journey as a buyer. Most importantly, we owed it to our customers to deliver on the promises we’d made to them and data was our answer to doing that at scale.

The main challenge I faced with every new product that I bought was the significant gap between the demo and ultimately getting value out of a product.

The Data Problem

We went through a rapid journey of re-building our Customer Success in 12 months and changed almost everything we did to become data driven including the people we hired, the metrics we used and the way we prioritised our customers. This overhaul happened whilst we grew to over $500m in ARR and involved over 120 accounts changing hands within my own CSM team. I remember my VP of EMEA at the time referring to it as “changing engines mid-flight”.

In the early days of this journey, I spent a lot of time interviewing potential candidates for CSMs and was surprised at the indicators that the industry was using to prioritise customers. NPS scores, Customer Satisfaction Surveys (CSAT), number of Quarterly Business Reviews (QBRs) came up consistently in almost every conversation. Yet, as a career buyer of software, these factors had never influenced my decision to renew or buy more of a product - that decision was almost always influenced by factors such as utilisation, stickiness and value derived.

We set out to find the leading indicators for customers who stayed and grew, and what we found was an overwhelming validation in our approach. Our data showed that in almost every metric we looked at (eg team engagement, product utilisation, contact with support, sales leads, marketing events), the level of customer engagement had a direct correlation with retention and growth of an account, and sentiment had no correlation. In other words, if a customer was using our product and engaged with our teams, it didn’t matter whether they were sentimentally happy or not — they stayed and spent more money with us.

The Biggest Unsolved Problem in Software

What amazed me in this journey was how the products on the market aimed at CS teams were solving entirely the wrong problem.

Within a year of us implementing this new approach, the Customer Success team were bringing in almost 40% of the company’s sales revenue number through expansions in existing accounts, and we didn’t churn a single CS customer. We achieved all of this by focusing on where the data told us to, and not on whether a customer seemed happy or not; in simple terms we spent more time with the quieter customers that were most likely to leave us and less time with the customers that complained.

What amazed me in this journey was how the products on the market aimed at CS teams were solving entirely the wrong problem. They were focused on creating manual tasks, running manual playbooks, or setting reminders for calls. Even where there were health scores, they were created manually based on ‘gut feel’, made up mostly of metrics like sentiment/NPS and weren’t actionable because it was difficult to understand what the scores meant.

In the months that followed, I spoke to hundreds of Customer Success and revenue leaders and the same themes kept coming up as their top priorities:

1) It was difficult for CS teams to use data to understand which customers they needed to focus on;

2) When the teams did manage to know which customers to focus on, it was difficult to understand what actions they should take; and

3) When they took action, it was difficult to do so at scale and measure what worked and what didn’t.

I set out on a mission to fix this problem by starting Hook. Our predictive platform uses your customer, product, marketing & sales, support and other data to automatically predict renewals, net dollar retention and upsells. We translate these predictions into automatically triggered actions to optimise those outcomes, letting CS teams take action at scale including gifting top users or sending nudges to inactive influencers. And we do all of this without any health scores, without playbooks and without manual tasks.

Creating the Leading Workplace for Ambitious People

I have been passionate about building ambitious and happy teams ever since I started managing people at 21 years old. In starting Hook, I wanted to build the leading workplace for the most ambitious people who enjoyed working hard but wanted to do so as part of a team. This is our primary mission. We have an amazing culture of collaboration, respect and hard work and I am extremely proud to have an exceptional team of ambitious, smart people to call my colleagues that you can meet here.

I wanted to build the leading workplace for the most ambitious people who enjoyed working hard but wanted to do so as part of a team.

If you’re interested in how Hook can help you accelerate your revenue growth by predicting which customers to focus on, please do click here to reach out and request a demo.

--

--

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store