The benefits of data driven growth modelling

As an operational-minded CFO, I believe Finance needs to be at the heart of the business. It needs to be focused on operations and involved in all departments to truly be able to budget, plan investments, improve and develop people, and grow the client portfolio in order to maintain its financial health. The best way to do that is by building a reliable growth model from start to finish.

How to create a sophisticated growth model

Gather data to build the model on

The way we make decisions at Ladder is based on looking into validated data. We use Growth Benchmarks, which allows us to get numerous different kinds of data from our clients, such as the cost of acquisition form, cost of registration, cost of lead, etc., and takes into consideration various parameters such as their industry, business model, where your product is based (app or website), geographical location and budget, to provide a more accurate view. These insights reveal very important growth KPIs that we then convert into a model.

Choose the right metric to start the analysis from

At Ladder, we don’t start with your typical business-relevant metric, such as conversions or registrations. Since we run a regression analysis, we start from traffic, and we prove that the qualified leads are not correlated with our paid media spend. But obviously, there is a correlation between the paid ads and our traffic, and traffic and our qualified leads.

Use the analysis to get clear predictions

We take blogs, articles we shared, subscriptions, monthly posts, paid advertisements, media fees etc., and create a regression analysis model to see what actually drives traffic to our website, and statistically approve those factors when we build our analysis. That way, we have a clear prediction of how many people will visit our website, how many of those will be converted into potential leads, how many of those are qualified leads, and how many of those will close and become our clients. The predicted values produced from the statistical models are accurate compared to the actual values to the level of statistical significance.

Observe how changing the inputs changes the outcomes

These inputs are the starting point, and because they are correlated with our top-funnel metric, the moment you change them, the outcome changes as well. It is all automated and built into our model. We can anticipate that if we invest heavily in certain areas, we can have a certain number of conversions, qualified leads, and new clients. All the models we’ve built for 2022-2025, basically our 4 to 5-year plan, are based on that.

Using the growth model to plan investments and predict revenue

At that point, it’s much easier to go into the revenue, because we know the average package we have per client, and the average price per package. We know exactly which costs are coming attached to the new clients, and the fixed costs and overheads attached to our people. The moment we change our inputs, the entire model changes based on the data and the analysis we made, and we effectively create our P&L and our growth model for the future.

Obviously, some areas are going to have a lag - for example, when we post an article, we don’t expect to have conversions right at that moment. We take the lag into consideration as well. If we change how many articles we post per month in the model, we don’t see the conversion that month, or the next, but we definitely see them down the line, and we know how much money to invest in which area.

Using the growth model for hiring

The growth model also solves the problem of finding the right balance between overhiring and underhiring. There is a very important correlation between clients and team members. Obviously, we need to have the relevant people to provide high-quality services to our clients. One element of that is the quantity and the resourcing, and the other is to have the right people for the job. With the growth model, we predicted how many clients and how much new business we will have and what impact that will have on our revenue. That automatically predicts how many people we need and what seniority they need to be, so we can be prepared for hiring.

Another thing to consider when hiring people is time zones. Where to hire people can be a strategically difficult question - a five hour time difference between clients and team members is a potential problem. By knowing where we anticipate to have our next client, we can be prepared to hire the right people in the right place at the right time - which is, obviously, well ahead of time. 

What the process of growth modelling looks like for Ladder and our clients

From Ladder’s side, this is what the growth modelling process looks like:

• We put an X amount of money into a segment
• We see how many clients we can expect to acquire
• We hire the people we need to service the clients’ needs.

When it comes to the clients themselves, the process looks like this:

• We use Growth Benchmarks to get the data for growth modelling
• We compare the data with similar companies in the industry
• We create the growth model from the data
• We create and optimize metric-focused campaigns, assets and data-drive tests
• We outperform the benchmark for the metric.

For example, a client comes in and says “I have a CaC (cost per acquisition) of $150 per lead”. We can look into Growth Benchmarks to see what the benchmark actually is, and compare it with similar companies so we can create the model. Let’s say that it’s $100 per customer. We create the campaigns, and focus the creative data driven testing on this metric. Once it’s achieved, we’ll give the benefit of the $50 to the client, which effectively becomes their gross profit margin they can invest and utilize somewhere else.

Growth modelling is at the core of what we do at Ladder, both on the client side and internally. It lets us predict outcomes with accuracy, which allows for greater control of our investments, and can be applied to any business to achieve remarkable benefits.