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Exploring Pricing Models
5 min read

Exploring Pricing Models

In the last weeks, I have been having lengthy conversations with my co-founder and the rest of the team about changing our Prezly pricing. Those conversations are mostly about:

1) What do other (SaaS) companies do?
2) Estimating the impact on our customer base?
3) Does this fit our principles/beliefs/vision?
4) Interesting articles/content about the subject.

It's noticeable how much these conversations touch most parts of the business. Depending on which hat we put on (sales, CS, product or marketing) while debating, there are always good arguments in favour or against the currently discussed option. There is no clear winner.

Personally, I believe we give too much weight to 1) and not enough to 3).

In this post, I will try to document our conversations and explore different pricing models together with pros and cons. It will help me shape my thoughts and make sure we take enough time to think and look at this from all different angles.

Why change pricing?

As software buyers ourselves (today we use 85 subscriptions for a total of  19k/month) we are big fans of letting the product do the sales. Plus, it fit's the bottom-up sales approach.

But why now? Lately, we've been working a lot on the first-run experience as part of a larger plan to re-open trials for Prezly. We want to make sure website visitors don't disqualify themselves. At the same time, we want to encourage trialers (and customers) to invite more people into their Prezly account.

Is it time to reconsider our pricing?
A hacker news post [https://t.co/u8o50O7CJ5?amp=1] got me all wired up aboutIntercom pricing. While complaining, I realised some of our customers might feelthe same way. > We’ve been Intercom customers since October 19, 2014. Our initial bill ? 240$ Today we’re paying 1488$/month. Bumped onto …
Post about the limitations of our current pricing (www.prezly.com/pricing)

About Prezly

So at Prezly, we're offering a CRM for PR professionals with a strong focus on outreach and creating engagement. Sometimes I describe Prezly as a mix of:

  • a CMS (WordPress, Wix, Squarespace)
  • a CRM (Hubspot CRM, CapsuleCRM, Google contacts)
  • mailing module (MailChimp, Campaign Monitor, Constant Contact,..)

We know Prezly is most valuable for customers that understand they need the combination of those three modules.

Principles

Before continuing this project, I listed a few principles to stick by throughout the journey. Here we go:

  • No intention to increase prices for our customers
  • Lower entry price will be good for our acquisition strategy (assumption)
  • We don't want to lose revenue
  • It's important that we feel comfortable around the pricing model
  • Simple = better
  • Prezly USP  = all-in-one. You can't buy components separately
  • Customers that use 1/3th of the platform are not our ideal customer
  • Using Prezly 20times/month should be more expensive than using it 1/month
  • Pricing linked with company mission = good

The data : Different levers

To do the math and look at the impact on different pricing models I have compiled a list of different inputs we can use:

company_type Brand vs Agency. Manual classification but 99% correct
plan_level Current plan of that customer
user_limit User limit (Seats available)
users_used Users in use (Seats used/invited)
users_active_last_30 User# active in last 30 days (Seats that are really used)
users_active_sharing_last_30  User# with sharing algorithm* last 30 days
newsrooms Number of newsrooms
stories Number of stories published in total
stories_last_30 Number of stories published in last 30 days
contacts Total contacts in CRM
contacts_active_last_30 Active contacts in CRM in last 30 days
contacts_engaged_last_30 Engaged contacts in the last 30 days (read/open)

In the below data set there are columns with all of the above metrics. This will allow us play around with different pricing models based on one or more of those 'levers'.

*A subset of our customers are account sharing. We have a simple session counting algorithm that tries to guess (based on IP, timestamp, User Agent) how many real users are accessing their account. More about this here.

The data (1mio ARR)

I have taken a subset of our currently active customer base. The subset of that data adds up to exactly 1 million euros in Annual Recurring Revenue or 83333 € Monthly Recurring Revenue.

Please note that this is real customer and usage data exported on the 1st of December 2020. Obviously I have swapped the company names 😎

You can see the data in this google sheet.

Pricing Model - Prices
Sheet 1 - Revenue per Plan Revenue per Plancompany_name,company_type,plan_level,user_limit,users_used,users_active_last_30,users_active_sharing_last_30,newsrooms,stories,stories_last_30,contacts,contacts_active_last_30,contacts_engaged_last_30,monthly recurring revenue,annual recurring revenue...

A quick summary:

  • Annual Revenue: € 1 000 000,20
  • Monthly Recurring Revenue € 83 333

A few more breakdowns to get a true sense of the customer split which should be largely the same as our current customer base.

ARR - Per company type (agency vs brand)

Per plan:

ARR - Per plan (professional vs expert)
!!! important !!!

This is real usage data (fake company names).
It's a subset of our customer base.

The data was generated on 01/12/2020

Models Explored

In the next days I will document my experiments with these models. Every post will use the same format, applying that pricing model to real customer data and initial learnings and thoughts about the outcome.

Per User/Seat

✅ Model S-A: Price/user + minimum users
✅ Model S-B: Price/user, no minimum users
✅ Model S-C: Price/user with less account sharing
✅ Model S-D: Price/user + Price/newsroom
✅ Model S-E: Lower Price/user + Price/newsroom

Alternative Seat Pricing

🚧 Model A-A: Model B with % reward for engagement
🚧 Model A-B: Agency plan?

Usage Based

🚧 Model U-A: Tiered Price with starter plan
🚧 Model U-B: Usage pricing based on newsrooms
🚧 Model U-C: Usage pricing based on stories
🚧 Model U-D: Usage pricing based on newsrooms + contacts
🚧 Model U-F: Usage pricing based on newsrooms + active contacts
🚧 Model U-G: Model U-F + reward per engaged contact
🚧 Model U-H: Model U-F + % reward for engagement

The different models (which might change names a long the way) will be scored from 0/5 together with my co-founder. To do that we'll be looking at the data and pro's and cons listed in every post.

We will score the models from 4 perspectives:

  • How good is this model for people that want to try Prezly?
  • Does this encourage inviting more users into Prezly?
  • How easy is it to implement?
  • How well does this model align with our long term vision?