Technology that works hard, so you don't have to.

Extract the full value of your sales, media and promotion data.
Improve your Marketing ROI with Sellforte.

Advanced analytics for marketing optimization

Our modeling requires at least 2 years of sales and marketing data in order to provide the most reliable results possible
After the data has been received, Sellforte’s data scientists run an in-depth analysis before sharing the results with our customer success team

By utilizing machine learning the analyzing process is automated and the results will be updated to Sellforte’s web-UI on weekly basis.

FAQ: How it works?

How is data science used in marketing?
To put it shortly, it’s all about approaching marketing through the scientific method and using it to solve challenges in marketing. First you develop a hypothesis based on your observations and maybe intuition, let’s say it’s “TV is the best marketing channel to advertise Chocolate bars”.

Then you gather data, sales and marketing data in this case, analyse the data, develop a model of the reality, and test your hypothesis. In the end you will learn something. You can then develop a new hypothesis and continue the cycle. The key idea is to experiment, learn new things, and build on your learnings.
How AI can be used in marketing?
With the ever-growing piles of data, marketing science relies more and more on different AI and machine learning methods from Bayesian networks to random forests.

Even with all the data and numbers, it’s still important to keep the business aspects in mind: The best model is the one which best helps improve your bottom line results.
What is Bayesian inference and why should marketers care about it?
Bayesian inference is a statistical technique rapidly growing in popularity among marketers.

The Bayesian approach is popular due to a handful of reasons. First, it allows inputting prior knowledge into your models in the form of informative priors. This makes it easy to leverage any past analyses and business intuition in your model and allows you to reach rapidly reach credibly.

Second, it allows building hierarchical models which in turn allows very granular models without breaking their consistency. Instead of analyzing your weekly total sales, you can see what’s going on exactly at each specific date, product group, brand, and location.
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Lorem ipsum dolor sit amet, consectetur adipisicing elit. Nemo a, itaque esse ab veniam, autem ratione necessitatibus voluptatum optio libero dicta consequatur fugiat rerum, suscipit non illo perspiciatis aut. Explicabo.
Lorem ipsum dolor sit amet, consectetur adipisicing elit. Nemo a, itaque esse ab veniam, autem ratione necessitatibus voluptatum optio libero dicta consequatur fugiat rerum, suscipit non illo perspiciatis aut. Explicabo.
Lorem ipsum dolor sit amet, consectetur adipisicing elit. Nemo a, itaque esse ab veniam, autem ratione necessitatibus voluptatum optio libero dicta consequatur fugiat rerum, suscipit non illo perspiciatis aut. Explicabo.
Lorem ipsum dolor sit amet, consectetur adipisicing elit. Nemo a, itaque esse ab veniam, autem ratione necessitatibus voluptatum optio libero dicta consequatur fugiat rerum, suscipit non illo perspiciatis aut. Explicabo.
Lorem ipsum dolor sit amet, consectetur adipisicing elit. Nemo a, itaque esse ab veniam, autem ratione necessitatibus voluptatum optio libero dicta consequatur fugiat rerum, suscipit non illo perspiciatis aut. Explicabo.
Lorem ipsum dolor sit amet, consectetur adipisicing elit. Nemo a, itaque esse ab veniam, autem ratione necessitatibus voluptatum optio libero dicta consequatur fugiat rerum, suscipit non illo perspiciatis aut. Explicabo.
Lorem ipsum dolor sit amet, consectetur adipisicing elit. Nemo a, itaque esse ab veniam, autem ratione necessitatibus voluptatum optio libero dicta consequatur fugiat rerum, suscipit non illo perspiciatis aut. Explicabo.

AI and machine learning for actionable insights

AI. In short, that is how we do what we do. Two little letters — allowing us to not only look at everything that’s happened in your marketing efforts so far (yep, even that failed campaign you’d rather forget about) but also accurately forecast the future AND recommend the best way to get you to where you want to be, optimizing your promotions and online/offline media efforts while we’re at it.

The question is, how?

- By analyzing all of your receipt and marketing data
- Adding in external econometric factors (for example, weather data)
- Using advanced machine learning and AI algorithms to make sense of the complex relationships in your masses of data

And turning these into actionable insights for you to use every day. This is all presented in our own Sellforte web-UI, designed to be an interactive tool. No more static powerpoint reports that are going to stay unopened and forgotten about in your inbox.

How does it work?

We believe in the power of the big picture, but we also think you need to know the details — which is why we connect promotions and marketing events to individual SKUs and product groups (as well as looking at performance across the board).

Our AI looks at factors such as discounting, increased store visibility and media, among other things, for each item, using the Bayesian model to eliminate noise and give accurate results. All of this is then learned by the algorithm, remembered and utilised in the future. 

This means you can see not only what is and isn’t working for your store as a whole but also at category and individual product level. More knowledge, more power.

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