Driving business results through machine learning and analytics
"There are applications of this technology [machine learning] that will deeply affect every industry. This will be a revolution as big as, or bigger than, personal computers, the internet, or mobile phones. Machine learning is the next underlying technology." Otavio Good
WHY?
Why should you use machine learning in your business?
Predict Sales
If you knew what service or product each customer was likely to order next and when, you would be able to spend less on marketing while increasing sales.
Forecast Revenue
If you could predict sales volume for each customer your forecasts would be more precise, and your inventory and logistics costs would decrease.
Keep Customers
If you knew the chances of a customer leaving you for a competitor you could take steps to keep that customer, lowering the cost of new customer acquisition.
Think about machine learning as a scientific way to drive customer satisfaction, increase sales, and reduce costs. In the process your business will become more data driven and analytical, which in turn are critical ingredients for becoming a business that improves with predictability.
SERVICES
The people, process, and technology
People
We rely on a network of professionals to bring the right expertise to the table. The team is built to drive a business result, not only to implement machine learning technology. Thus the team members' skill set will range from business strategy and change management to data science and project management.
Process
We work according to a structured process that takes you from setting your goals to achieving them, ensuring quality results every time
SAMPLES
3
ways you can apply machine learning in your business
Predict the next purchase
The objective
1
With analytics and machine learning it is possible to predict, for each individual customer, the likelihood of a customer performing (or not) an action such as buying a product, subscribing, or starting to use a new offering from your business.
The benefit
Since you know the likelihood of a customer performing a certain action, you can tailor marketing and offerings to what best suits each customer.
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Simply put: More revenue with less wasted expense and effort.
Will it work for my business?
Most likely. Analytics and machine learning require data and the more sources there are and the richer they are the better. However, almost all businesses have order, customer, and product data and that is enough to get started and to deliver results.
Customer segmentation
The objective
2
Clustering is a name for a collection of mathematical methods to organize your customers into segments based on what you know about them. This will in most cases reveal patterns and insights not visible to the naked eye.
The benefit
​A fresh view, mathematically supported by the data, of the customer segments will enable your business to devise entirely new marketing, sales, and customer support strategies based on what is important to that particular customer segment.
Will it work for my business?
The more attributes that exists regarding customers, the more ways of clustering them exists. Attributes can be "simple" data such as geographic location and age, as well as derived data, such as purchase volumes or frequency.
Customer retention
3
The objective
By finding commonalities among customers that have defected in the past it is possible to predict the retention probability for each and every customer.
The benefit
The retention probability can be used to take a wide variety of retention actions in order to retain the customer, and in the future, minimize the number of customers that need retention actions.
Will it work for my business?
If you have more than a year of customer history and you have more than a thousand customers it will most likely be possible to develop a retention probability for your customers.
CONTACT
Inquiries
Contact us. Results can be delivered in a matter of weeks. Let's talk about how we can apply machine learning in your business.
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Marcus Mollersten