AI Use-cases

Discover which AI use-cases work for you

Personalize your sales and communication leveraging client segmentation

Who are your clients? More and more organisations want to personalize their interactions with customers. Understanding the diversity of your clients through a customer segmentation allows to grasp which type of marketing communication fits best for which customer.

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Churn prediction as a tool for a more efficient targeting strategy

Detecting which customers are possibly looking to stop buying from you, can help you to act before it is to late. Implementing a churn prediction tool is very helpful to be used in customer interactions as call centers or alerting mechanisms.

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Personalizing product recommendations for your e-commerce customers

Selling a product to a customer is great. Selling more products to a customer is even better. Increase your cross-sell opportunities by recommending products to customers that are usually purchased together with the already selected product..

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Optimize where to spend more Marketing budget

As marketing teams have a limited budget, applying the right marketing mix is difficult. Knowing where to spend that extra € Marketing budget is key. Through multi-touch attribution, we measure and allocate each channel with its share in the conversion process and project recommendations.

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Generate profit through customer lifetime value

Acquiring new customers can be a long and expensive process. Spending on customers without knowing how much revenue a customer will generate for your company is risky. With the use of CLV calculation you know what the maximum amount is you are willing to spend on each customer.

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Use lead scoring to identify your company’s most valuable prospects

It often is a challenge to determine which customers to target to maximize the revenue & margins for your organization. By using lead scoring, we can clearly identify the hot leads with the highest quality. Applicable in both B2B and B2C.

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Drive customer value using analytics to determine the next best action

Having the same approach for every customer might cost you a lot. As all customers are different, they have to be treated differently in order to drive customer value the most. Using analytics helps by predicting the most valuable next action for your sales and/or marketing teams.

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AI-based physical inspection for manufacturing industries

Quality control has always been a manual intensive labour and depends on the quality of the person performing the inspection resulting in inconsistencies. Leveraging AI Image recognition, we can increase efficiency and limit quality issues

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Predictive Maintenance on equipment maintenance

As a manufacturer, maintenance of your machinery is an essential part of business operations. The goal of the maintenance is to ensure a maximal uptime of installations and machines at preferably the lowest possible cost. With predictive analytics you will be able to optimize your asset usage with a minimal downtime.

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Continuously check on Safety Material with AI

Operators should wear Safety Material such as safety hat, safety jacket, shoes and gloves. Using AI Image Recognition, we can continuously check if people wear Safety Material and both alert and report on Safety Behaviour

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Increase your profitability by using price optimization

You might be missing out on sales due to a price set too high. Losing profit caused by a low price. The goal of price optimization is to avoid this. It sets a dynamic price by analysing how customers would respond to different pricing strategies of your products and services.

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Leverage Sales Forecasting to drive Sales decisions

Taking strategic and important decisions under a high degree of uncertainty is challenging. Sales forecasting is usually a very manual and time-consuming process. Therefore, estimating future sales in an automated way provides crucial information for all your business operations.

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Increasing contract fulfilment through anomaly detection

When negotiating contracts, a certain volume commitment is specified over a specific timeframe. However, during that period, actual orders are influenced by end-product customer orders, inventory management or alternative supplies because of competitive products. With predictive modelling we can accurately predict the volumes clients will fulfil compared to the actual contract.

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Predict the highest potential new prospects with Lead Scoring

Lead scoring allows you to target the right customer depending on their buying stage or interest level. It allows us to focus our sales efforts and budgets smartly thus greatly improving efficiency of (digital) sales teams.

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Cross and upselling gets you more than what you have

Selling a product to your customers is great. Using that opportunity to sell more than one product is even better. Cross and upselling is a sales technique used to get a customer to spend more by presenting alternatives in an automated way that are related to the product or presenting a superior (more expensive) product of the one in mind.

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Optimization of the supply chain through Demand Forecasting

Taking strategic and important decisions under a high degree of uncertainty is challenging. Demand forecasting is usually a very manual and time consuming process. Leveraging Machine Learning, we can extend sales data into a sales forecasting taking into account weather, trends, promotions, price and other.

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Increasing contract fulfilment through anomaly detection

When negotiating contracts, a certain volume commitment is specified over a specific timeframe. However, during that period, actual orders are influenced by end-product customer orders, inventory management or alternative supplies because of competitive products. With predictive modelling we can accurately predict the volumes clients will fulfil compared to the actual contract.

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AI-based physical inspection for manufacturing industries

Quality control has always been a manual intensive labour and depends on the quality of the person performing the inspection resulting in inconsistencies. Leveraging AI Image recognition, we can increase efficiency and limit quality issues

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Transform your regulatory compliance with predictive analytics

Internal auditors spend a lot of manual time detecting potential threats. For many organizations action is only taken under the threat of an external audit or worse still, after a warning letter has been issued. With the introduction of predictive analytics, AI does the heavy lifting for internal auditors with financial data and these threats can be spotted before they cause any harm.

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Discover fraudulent activities with pattern recognition

Discovering fraudulent activities can be difficult but picking fraudulent activities without labelling a non-fraudulent activity is even more complex. Machine learning can help recognize fraudulent patterns in real-time transactions with very high accuracy.

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Artificial intelligence eliminates manager approval of expenses

Managers spend an incredible amount of time approving expenses while they could do much more productive tasks. Also as it is quite repetitive and time consuming, managers are likely to miss the details. Therefore, using AI will automate the process as well as limit the risk of overlooking potentially fraudulent transactions.

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Gain smart guidance for financial statements with machine learning

You don’t know how to gain all insights the profit-and-loss statements data can provide you. You don’t know how to easily profit from your data without spending days for manual investigation and without still overlooking the relevant. AI helps you to be more efficient by analysing real-time P&L statements to make strategic decisions.

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Using analytics to predict cash flow

Management of accounts receivable can be challenging as it remains a manual task and because it depends on factors not controlled by the firm. With machine learning you can create an automated AR forecasting process to improve accounts receivable collections.

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Discover fraudulent activities with pattern recognition

Discovering fraudulent activities can be difficult but picking fraudulent activities without labelling a non-fraudulent activity is even more complex. Machine learning can help recognize fraudulent patterns in real-time transactions with very high accuracy.

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Next-best-training recommendation

With many employees and a lot of different training options it is difficult to optimize the use of those trainings for your employees. Suggesting a training to someone who already excels in a certain skill is pointless. You miss out on opportunities to optimize the skillset in your team.

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Lead scoring utilised in recruitment by prioritizing incoming prospects

Discovering talent is not always easy, receiving a lot of applications is already a good first step but handling and getting through them one by one is a very time-consuming task. Lead scoring helps recruiters to be more efficient by first handling the most promising candidates.

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Keep employees longer through churn prediction

Seeing one of your key employees leave your company is hard. Finding and acquiring talent is much more difficult than keeping them. Therefore, churn prediction ensures that HR can invest in the people that need it most.

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Identify the most effective treatments using AI

Most of the time, the ‘generally’ most effective treatment is given to patients. Normally, it will be the best solution but often a more suitable treatment is possible. Think of how a group with a certain condition can have other completely different health issues.

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Artificial intelligence for medical diagnostics to recognize skin cancer

Visually examining patients for skin cancer is a time consuming and manual task. The dermatologist needs to carefully examine the tissue and if he/she believes it is cancerous, then biopsy will need to confirm the findings. Automating this process by analysing images of the skin tissue will accelerate and improve effectiveness of further treatment.

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How machine learning can optimize your credit scoring

To determine how creditworthy a person/business is you have to analyse data and have financial expertise. Machine learning can automate this credit scoring process with complex and in-depth models to support decision-making.

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