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  • Matthias Hilpert

Jonas Rieke - COO, Personio



Personio was founded in 2015 by Hanno Renner, Roman Schumacher, Arseniy Vershinin, and Ignaz Forstmeier, shortly before Jonas Rieke joined the company. The scaleup offers a holistic HR software for small to mid-sized companies. In four offices, Personio employs 600 people. Personio has raised about $250 million in venture capital to date.


On organization:


Personio is structured into mission-based teams: Marketing generates leads, Sales converts leads into customers, and the customer-facing teams maximize customer value. Go-to-market functions taken together are about as many people as the Customer team.


Our Customer team counts about 125 people in the following roles:

  • Implementation (35 people): This team sets up customer accounts once they are handed over from Sales. This includes importing data, setting up the right parameters, and training the users.

  • Customer Service and Community (40 people): After the active support phase during the implementation, our service becomes reactive, i.e. our team responds to users’ tickets and calls. We continuously try to increase the automation rate for these services while keeping service quality at the same high standard that we always strived for. Lately, we are also heavily investing in a Community team which develops and operates an online community and organizes User Groups Meetups and our Customer Advisory Board (CAB).

  • Customer Success (10 people): This team works as strategic partners with the People teams of our very large customers. Customer Success provides additional services to more complex accounts to drive adoption and reduce churn risk of those bigger customers.

  • Customer Growth (20 people): They take care of traditional account management and any commercials with customers: renewals, expanion, and dealing with detractors and churn.

  • Payroll Operations and Partnerships (15 people): The team is responsible both for training and certifying tax advisors in using Personio in combination with payroll software and winning them as trusted partners and customers.

  • Product Experts: They are the interface between product and the Customer organization, facilitating beta tests and feature releases as well as reporting feedback back to the Product and Engineering teams.

  • User Education (5 people): The team owns all channels around self-served and proactive communication with customers: our help center, in-app tours, webinars, monthly product update newsletters. Additionally they organize knowledge management for internal functions.

  • Customer Data and Processes (5 people): The team aims at improving and automating processes. They closely collaborate with BI, Infrastructure and all customer-facing teams. The further develop our tool landscape and make sure that each function is able to work as data-driven as possible.


Within Personio’s teams, there is a clear cut between lead and customer. Once a lead is converted, Sales hands over the customer to Implementation and later Customer Service. The idea behind this is to create focus, to separate “hunters” (the Account Executives in Sales) from “farmers” (our Growth team). This clear cut between “hunting” and “farming” works well for us for two reasons:

  • We take great care to get the incentives right, and we measure precisely which team and person is responsible for which contribution. For example, there is a clawback for customers who churn within 12 months to prevent Sales from closing unsustainable deals.

  • In our industry, the HR sector, hunter and farmer characters aren’t actually that far apart as they might be in other sectors. Our average hunter is less of a bloodhound and more of a relationship-builder.


It’s not like service-oriented people can’t sell. When we changed our pricing structure, we had to transition all of our 1,400 customers, one by one, to the new pricing structure which also led to price increases. That’s when also less sales-experienced teams could learn how to sell. We did a lot of training before to share the necessary communication skills and take our employees’ fears away--and it worked out well for us.


On packaging and pricing:


We started out with a pricing level that was rather low and not very degressive. As a result, our Sales team often reported customers reacting to our price with “Wow, you’re really inexpensive!”. This and the investment that we put into our product (by now more than 200 people working in Product and Engineering to improve and extend functionalities), made us confident that we could ask for higher prices. Additionally, we changed the packaging structure to provide customers more flexibility for example through add-ons.


By making these changes to our product packaging and pricing, we were able to increase MRR, practically without any churn. Plus we gained references by giving discounts for early customers for whom we raised prices less in the process. It was a huge success, but we also worked hard to accompany the pricing structure change for every single customer with a lot of information and discussion. We wanted customers to understand our thinking and not just increase prices. This is key to a process like this and only works authentically if you mean it.


While our first product packaging system and pricing was rather based on an educated guess, this time we took a data-driven approach. Our goal was to use the existing data on our product to create an optimal combination of three different packaging components: Value Metrics, Plans and Add-ons.

  • A value metric is a single measure that correlates strongly with the value that a product creates for its customers.

  • Plans are bundles of product verticals, modules or features. Plans should include a well-balanced mix of must-have and nice-to-have features.

  • Add-ons are a good option to offer your customers more flexibility. Also, it can be a great source for additional expansion.

To find good feature candidates for different packaging components, we first created a structured documentation of all of the components of our product (product verticals, modules, features, sub-features, etc.). Each of these components has different properties: for example, how users interact with it, how users perceive its value and whether it depends on other features. We analysed this data using statistical methods to identify meaningful value metrics, suitable features and modules for plans, and features for add-ons.

After analysing our product and evaluating different value metrics, we aggregated our insights and drafted packaging models. Visualising a prototype pricing page helped to challenge different models with our team. This was also the basis for coming up with reasonable price tags for our packaging components.

Finally, it was important to us that our go-to-market and customer-facing functions were able to tell a comprehensible and exciting story around our new packaging. Thus, the creative and last part of the packaging exercise was to gather a cross-functional team from Product Marketing, Design, Sales and Customer Success and create a profound story around our packaging.

I have described our packaging framework in detail in this Medium post: https://medium.com/inside-personio/developing-a-data-driven-packaging-for-your-saas-product-703a67648dc4


Especially bigger companies work with budgets, which had two important implications for our pricing:

  • Staying below a threshold of €100,000 ACV seems to help close deals easier and faster. It doesn’t involve as many stakeholders within the company, and you can always expand later.

  • Companies want to make sure they will stay within their budget and planability, which is why usage-based pricing made little sense for us. Instead, we offer add-ons for higher usage beyond a certain threshold we derived from the data across all of our customers. For example, if we find that the majority of our customers use 20 e-signatures per month, we include this in the standard package and sell an unlimited add-on to those companies who regularly use more than those 20 e-signatures - a share of the additional value they derive from more heavy usage.


It’s hard to define usage-based revenue as recurring revenue. We follow the policy of “recurring first”, because the valuation of these revenues is higher.


On customer’s success:


We strongly over-invest in our customer-facing organization: every customer can talk to us as much and often as they want. I can highly recommend this approach. Especially in the beginning, when your product is still developing, you can compensate with excellent service, proactive check-ins, and just by caring. Even now, we still derive a lot of value from our customer success efforts. For example, we generated more than 70 references from our existing customers in one quarter, which helps for expanding to new markets.


To save costs, we try to automate as much of our service process as possible. In Implementation for example, we already achieved a plus of 30-40%, measured by the number of additional projects an Implementation Manager can complete per month. We believe it’s realistic to gain another 20-25%. However, our service will never work without human contact -in fact, we wouldn’t want that. That’s just not who we are. And as long as the metrics and margins are good, we’ll keep it that way.


Growth and Customer Success Managers can access “health score” data for each customer in their portfolio from our data warehouse. The health score includes indicators on adoption, service and financial data. This way, we can keep a close eye on what’s happening with each of our customers, and can intervene in case something is going on. For example, we received a data alert that the recruiting usage of one of our customers had suddenly dropped by 20%. What was going on? They had just hired a new recruiter who hadn’t worked with our tool before, so they didn’t know how to use it. Because of our monitoring, we were able to intervene, offer training and even achieved an upsell to this customer in the end!


We have a clear process to deal with churn. First of all, we call the customer to find out the reasons behind the churn. Then we categorize them into a matrix with the dimensions “foreseeable” and “preventable”. Most of our logo churn is not preventable, for example because our customers grow out of our solution, or go bankrupt. Only 1.6% are actually preventable, and we do work hard to analyze the problem through post mortems and eventually to win them back with the help of the Sales team.


On upselling:


There are tons of benchmarking studies on net dollar retention. Our guidance for net dollar retention from our upsell and customer success efforts is 115%. This might seem low in comparison to land-consume-expand models, which reach up to 200%. But our business is very front-heavy because we build and sell the HR Operating System which is the entire system, not single modules. You can only reach those high net dollar retention goals if you start small and then have a lot of upsell potential. Since net retention or growth from existing customers is crucial for a healthy SaaS, we regularly analyze the potential for upgrades and upsells. This helps us to plan Customer Growth capacities and early on plan upselling campaigns. But a golden rule for this team is to upsell sustainably and only if we see a benefit for the customer - we play a long-term game and seek trusted partnerships with our customers.


On tools:


In retrospect, I wish we had implemented an external subscription management system earlier. Before we did that, it was such a pain to find out simple things like: how much Expansion MRR on a specific feature did we actually have that month? It was really hard to get the basic data right and track them over time with our own improvised tools. Also the migration of historic data is a lot of work. So, invest in proper subscription management early on.


In the beginning, everyone was super excited about all kinds of tools and metrics. But then we figured out that it’s fairly easy to implement the basics, but then you need an entire team to maintain, develop and actually use them. In retrospect, I would recommend strictly focusing on a small number of most significant metrics you need to manage your team and leave the rest for later. You can always expand on top of a strong foundation.


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