MANAGER TRAINING COURSE
LEARN ABOUT ARTIFICIAL INTELLIGENCE
Using artificial intelligence (AI – Artificial Intelligence) in business is no longer just the domain of technological giants from across the ocean, but is also becoming an everyday reality in Polish organisations. Our 5-hour training course will prepare key employees in your company for this revolution.
The knowledge will be imparted by a practitioner with over 20 years of experience, while the topics of AI, big data and machine learning will be presented in a comfortable online format. We guarantee a range of study materials tailored to the chosen industry and answers based on the specifics of the Client’s circumstances.
BENEFITS OF THE TRAINING COURSE
4 KEY BENEFITS
You will master specialist AI terms and issues so you are prepared for the digital revolution.
You will communicate much more freely with Clients, analysts as well as artificial intelligence solution providers.
You will learn examples of AI applications from the speaker’s experience, which inspire to automate processes in your own area.
You will learn to manage a hybrid working environment, made up of humans and algorithms, requiring learning, testing and refinement.
AI PROJECT IMPLEMENTATION
DISCOVER THE BUSINESS POTENTIAL
Potential analysis is addressed to organisations that are aware of the potential of artificial intelligence and would like to use it to solve business problems. We support not only corporations with extensive databases that do not know how to start benefiting from them in practice, but also smaller companies that have doubts as to whether they have sufficiently valuable data.
Organisations that have already identified areas for AI yet have had difficulty with implementation also opt for analysis. Based on interviews with managers and data audits using statistical and machine learning methods, we create initial recommendations (quick wins), which ultimately result in an AI project plan.
ANALYSIS BENEFITS
THE 5 MAIN EFFECTS
REDUCTION OF OPERATING COSTS
through data integration and process automation.
PERSONALISATION OF CUSTOMER SERVICE
as a result of anticipating their needs and expectations
INCREASED SYSTEMS SECURITY
thanks to alerts on suspicious user behaviour
MAKING THE RIGHT DECISIONS
based on trends discovery and forecasting
INCREASE IN REVENUE
through the reduction of churn and additional sales based on x-selling and up-selling models
SPECTRUM OF POSSIBILITIES
CHECK OUT SOLUTIONS FOR YOUR SECTOR
churn prediction
usage prediction
x/up-sell
sales forecast
campaign targeting
sales performance
failure prediction
behavioral segmentation
image recognition
conversion increase
credit scoring
dynamic pricing
churn prediction
usage prediction
x/up-sell
sales forecast
campaign targeting
sales performance
behavioral segmentation
fraud detection
conversion increase
dynamic pricing
churn prediction
usage prediction
x/up-sell
sales forecast
campaign targeting
sales performance
behavioral segmentation
fraud detection
conversion increase
churn prediction
usage prediction
x/up-sell
sales forecast
campaign targeting
sales performance
behavioral segmentation
image recognition
churn prediction
usage prediction
x/up-sell
sales forecast
campaign targeting
sales performance
behavioral segmentation
fraud detection
image recognition
dynamic pricing
churn prediction
usage prediction
x/up-sell
sales forecast
campaign targeting
sales performance
failure prediction
behavioral segmentation
fraud detection
image recognition
conversion increase
credit scoring
churn prediction
usage prediction
x/up-sell
sales forecast
campaign targeting
sales performance
behavioral segmentation
image recognition
churn prediction
usage prediction
x/up-sell
sales forecast
campaign targeting
sales performance
failure prediction
behavioral segmentation
fraud detection
image recognition
credit scoring
churn prediction
usage prediction
x/up-sell
sales forecast
campaign targeting
sales performance
behavioral segmentation
fraud detection
image recognition
conversion increase
dynamic pricing
INSPIRATIONS
TELECOMMUNICATIONS COMPANY
The challenge: A limited number of a new product to be tested by potential customers.
The solution: Classification and probability estimation made it possible to determine the highest possible performance indicator, i.e. the percentage of people who will buy the product after testing.
The result: As a result of implementing the predictive model, the propensity to purchase the product after testing in the group indicated by the model was 4-5x higher than in the random group.
A SERVICE COMPANY
The challenge: Planning the next year with the revenue forecast in mind.
The solution: Based on historical revenues, macroeconomic data and internal data, including information on new projects, a forecast was created using the regression method.
The result: Using this method, Y2Y revenue growth was achieved every year for 5 years in a row, and the level of achievement of annual sales plans fluctuated between 101% and 113%.
A LOAN COMPANY
The challenge: Establishing the value of new customers (CLTV).
The solution: Using historical data, demographics and lifestyle variables, a machine learning model was built to determine this value per customer. This resulted in a higher number of safe contracts that could be concluded and, consequently, an increase in the company’s profit.
The result: The number of contracts signed went up by 21% Y2Y and profit by 43% Y2Y
BUSINESS SERVICES
The challenge: Costly outreach to customers with a new product offer.
The solution: Based on randomly offering the product to 5% of customers, 30% of customers most similar to those who have already decided to buy were identified.
The result: Thanks to the campaign using the model described above, sales of the new product increased by 74% over a comparable period.
AN ONLINE BOOKSTORE
The challenge: Increase the value of the shopping basket.
The solution: After analysing similarities in customer behaviour, bundles of 2-3 books were created at a cheaper price per item. As a result, there was an increase in sales due to cross-selling.
The result: Sales of the sets created in this way increased total book sales by 17%.
DEVELOP CURRENT APPLICATIONS
Sometimes companies are already taking advantage of artificial intelligence solutions but are not convinced that the model or algorithm used is the best possible. Other times the models were implemented many months ago and already need to be refreshed or rebuilt in order to continue to provide high performance.
We offer design testing and optimisation using all machine learning methods, such as: naive Bayes classifier, logistic regression, SVM support vector machine, k nearest neighbours method or neural networks.
We also use methods that are a composite of classifiers derived from, among others, the above methods (random forest, gradient boosting and AdaBoost). The results obtained are fully described, defined and compared with previous results. Based on these data, we recommend further actions.
BENEFITS OF OPTIMISATION
4 IMPORTANT REASONS
You will reduce the risk of potential threats by verifying the model you are currently using.
Zredukujesz koszty operacyjne za pomocą ulepszonego modelu, popartego monitoringiem jakości.
You will improve process efficiency by refreshing data and rebuilding algorithms.
You will start to get more out of AI and understand how the outcome of the model depends on individual variables.
MODELLING PROCESS
PROJECT STEP BY STEP
WHO ARE WE?
A FEW WORDS ABOUT ABR SESTA
ABR SESTA is a certified full service research agency with entirely Polish capital. Since 1996, it has been helping the largest domestic enterprises and international corporations to make the right business decisions by using a full range of qualitative and quantitative surveys and introducing the latest technological solutions. The company was founded by Sebastian Starzyński – a futurist and promoter of such trends as gamification, AI and big data in the business world.