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Predict better, make more profit

Growth Simulation for E-commerce

Our Growth Simulation, part of Genero’s Growth Method, sets clear financial goals by forecasting revenue and profit.

Scenario planning and forecasting service, to finally get answers to the most difficult questions:

  • How much should I spend to maximize profit?
  • Which products generate the best customers?
  • What should we focus on?
  • Why is performance going down?

More profitability with the right actions

Your e-commerce is ramping in revenue, but could it be more profitable? Most probably. Genero’s Growth Simulation is a service to forecast better.

Our Growth Simulation closes the loop by predicting the full life-cycle of customers, from the first-purchase onwards.

The service takes a look at your company’s historical data, has a look into the trends of the sales articles and makes assessments on media spend. With this data a forecast is made to guide you to make better actions.

Marketing as a tool to reach your specific financial goals.

Want to grow as much as possible?

The Growth Simulation predicts the full lifecycle of new customers, giving insight into when customers become profitable, and letting you spend based on acceptable payback periods.

Want to maximize profit?

The Growth Simulation evaluates when it’s most profitable to spend, and which levels of spend maximizes the bottom line. With this goal we set marketing spend to maximize profit.

Want to maximize cash flow?

With the Growth Simulation you can estimate and execute on campaigns turning inventory into cash.

Here’s what you get:

Simulation: P&L-level forecasting different scenarios

Actionable forecasts: Daily expectations in dashboard to quickly react to performance

Levers: Priorities based on looking forward, not looking back.  

The Growth Simulation process

We gather your historical data, and crunch the numbers, looking at both customer acquisition and retention. Together we adjust for where the data is misleading. The end result is a multi-layered model that can be used to simulate the lifetime effects of marketing: from acquisition to retention.

The Simulation

The ready made Growth Simulation is used to look at different scenarios, i.e. how different levels of spend affect revenue and profit in the short- and the long-term. Together we select a scenario that most aligns with what we want to achieve.

The Levers

From the Simulation we get expectations from the future, and we can look at bottlenecks and opportunities in the future, not in the past. This includes not only direct marketing actions, but also touches financial and product related decisions. A final list of strategic priorities is selected. 

The Forecast

The scenario selected in the planning stage is inserted into a dashboard, giving detailed expectations for different parts of the marketing. This allows for quick reactions to under- and over-performance and makes sure we’re optimizing towards the financial goals. 

The model is updated continuously, improving the accuracy and ensures learnings from tests are incorporated in the future.

Here’s the extra we bring to the table: Once we have the forecast, our goal is to break it.

How? By focusing on the things that matter.

In the endless sea of actions that can be taken, it might be hard to grasp what to do. From the growth simulation, we’re able to diagnose which reasonable levers we want to focus on.

What are levers?

Levers in this case are for example Website, Media Buying, Organic Traffic, Product, Shipping and Email to name a few. The same way when you renovate a house, it’s usually not feasible to try to make everything at once. From the simulation, a set of levers are defined to focus on to make more profitable sales and marketing. If you’ve got engaging content and your email marketing has a high open rate, but is lacking in conversions, focus on making that better.

A case is always tailor-made to your actual needs from your business’ perspective.

Here’s How It Works:

1. We touch base and go through your business case together

2. To be able to forecast, we’re going to need your business relevant data everything from product margins to shipping costs, order data and access to existing marketing costs.

3. Based on the data we create a growth simulation in 2-4 weeks together with recommendations and actions.

4. With the Growth Simulation you’re able to predict better through the right actions. Those actions are easily made into a brief, that Genero can help you with regarding growth marketing.

5. Always-package: You can get access to the simulation on a 24/7 basis for a recurring fee. The simulation pulls in data from your existing sources and therefore remains up to date and develops further.

The Genero Method

We take pride in helping our clients launch new brands and products, accelerate their growth, and expand into global markets.

As the leading growth agency in the Nordics, our mission is to help your business thrive in every way possible through tried and tested methods during the past 15 years.

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Frequently asked questions

What is the difference between a Growth Simulation and MMM (marketing mix modeling)?

Our Growth Simulation is technically multiple layers of MMM, adjusted with human judgement to correct for errors in the data that quantitative modeling completely misses. On its own, we believe this is a better way of doing MMM.

Do I need to change out my marketing agency?

Our Growth Simulation service has been developed to help deliver best-in-class strategy services to our clients. If you’re currently working with consultants to address the same types of questions, it might be a substitute for all or parts of these services.

A Growth Simulation is not a replacement for day-to-day operations such as media buying. While every single client so far has opted to involve us at least in part, in theory it can well be executed by someone else.

Show me under the hood

A Growth Simulation looks at the business with an understanding of the unique characteristics of e-commerce. It layers models of customer acquisition with retention models and is fine-tuned to account for where there are biases in the data.  

From the combination of models, it can calculate theoretical scenarios and find the best ways to allocate resources. For example, it calculates how much we should spend on ads to generate the maximum profit, accounting for the fact that these customers will come back and purchase more in the future. 

With the always-package, you also improve the model as you use it, making it better over time.