February 16, 2023
Chances are you have played the ‘divine’ mobile game Candy Crush, by King Digital Entertainment.
With billions of downloads and more than $10bn in gross revenue since its launch in 2012, it is a worldwide gaming phenomenon. But was it always destined to be?
Soon after launch, new user growth (or installs) had flatlined at 15% of what became the eventual peak. Had installs remained at these lower levels, Candy Crush may not have become a household name.
Candy Crush of course was an innovative product with super strong engagement. However, the game really ignited like a rocket when we started spending upwards of $1m USD a day on marketing.
So how do you convince C-suite and the board to increase your marketing budget from roughly $15m to $350m per annum? By forecasting the future with predictive analytics.
Early 2013, Candy Crush had recently launched and its creator King was sitting on a circa $100m annual revenue run rate. I presented to the board a forecast that said that CCS was going to gross $2.03bn for the calendar year (20x higher! I swear you could have heard a pin drop in that boardroom.)
I went on to state that this could only be achieved if we were allowed to flexibly spend our marketing budget to hit strict return on investment (ROI) targets.
In short, we got the board to agree to investment parameters. Not a fixed marketing budget.
King ended up grossing $1.94b that calendar year... Ok so 4% down on forecast... but what’s $90m between friends, right?
How did we come to this “relatively” accurate prediction from the low base we were at?Firstly, we had a granular understanding of user behaviour and how much people would spend through a process known as cohort-based forecasting.
Cohort-based forecasting can tell you how big your product / service can scale but also how much you can afford to pay for customers.
(Side note: Every single business in the world has customers, and you can create a predictive model for them using only three pillars: the number of new users, how well you retain them, and how well you manage to extract money from them. It’s the same framework for pretty much every business-- it’s just variables that change. I won’t bore you with the details as it can be dry as f**k.)
Secondly, we had a good understanding of what it costs to acquire customers via paid marketing and how that cost will change as you add incremental marketing budget. We call this the price volume curve.
The combination of these two things resulted in a forecast that showed the board not only that they were going to make their marketing money back but also what each financial quarter was going to look like along the way.
Providing that sort of confidence loosened the purse strings and put King on an entirely different growth trajectory.
And here’s the thing. The Candy Crush story wasn’t a fluke. We have found repeated, game changing success in applying our approach to many different business in industry sectors.
I could tell you about the time we predicted the success of Small Giant Games when it was almost at zero in revenue to over $250m per annum. Or when we quintupled the amount of new users to the online store of a leading make up brand. The list goes on.
Today, armed with our forecasting crystal ball, we are trusted by big names in Venture Capital and Private Equity to forecast (hence de-risk) their investments.
As much as I love making investment bankers rich, the goal here at Ramp is to build a SaaS analytics platform that puts our capability into every consumer facing business.
Why? Because f***k top down management forecasts. So much bull***t happens in organisations because management pulled a forecast out of nowhere.
How many times have you ever been asked to hit a budget that is entirely unrealistic? It’s entirely counter-productive for staff and the business as a whole. It sends entire teams scurrying in different directions rather than addressing actual underlying barriers to growth.
So as our manifesto here at Ramp:
We believe budgeting and forecasting should be way more bottom up than it is top down.
We want to move from a situation where people in finance teams are ‘spreadsheet jockeys’ engaging in guesswork to one where they are empowered with data science.
We want all finance teams to be able to predict their next quarters revenue within a percentage point of accuracy.
We want their forecasting to be automatically refreshed so it is always up to date.
If the forecast changes we want to know exactly what the underlying cause was and how to fix it – if it can be fixed!
We want finance teams to be able to tell you if numbers are up or down because of something the company has done or something external like the weather.
We want the finance team to tell you if you’re wasting or under investing in terms of marketing budget (either is negligent, no excuses).
So that’s what we are building – a SaaS platform that does all of this and more.
If any of the above resonates with you, feel free to reach out. We already have our platform up and running with some amazing clients and are providing loads of value, and we’re only just beginning...