Business Objectives and Machine Learning Opportunities

Unlocking the patterns in your data can help you to be better equipped to predict trends that can be utilised to improve the profitability of your organisation. Machine learning from Robotica Machine Learning can help your organisation to enhance its capability across a range of fields and extend the value from a spectrum of operations.

Accounts Payable Recovery

Finding the harmonious symmetry between good vendor relationships and your organisation’s cash flow requires careful planning. Automated machine learning can help you to effectively control liabilities and manage cash availability.

Advertising Optimisation

Gain insights from your AdWords data to forecast advertising tactics that will work towards delivering your goals and objectives. Present personalised advertisements according to the recipients’ predicted response probabilities.

Anti-Money Laundering (AML)

Compliance organisations within banks and other financial institutions are turning to machine learning for improving their AML compliance programs. Today, the systems that aim to detect potentially suspicious activity are commonly rule-based, and suffer from ultra-high false positive rates. Automated machine learning provides a solution to address this challenge.

Channel Optimisation

An effective channel optimisation plan, balancing coverage, focus, commitment and capability across all channels, is a proven, effective means to reduce costs and improve yield. By understand how each channel is performing, your efforts can be directed to maximise impact and revenue.


Regulatory pressures, business ethics and standards bodies all make demands on how you deliver products and services. Non-compliance can lead to fines, exclusion and reputational damage.

Credit Risk

Extending credit to customers or suppliers is a risky business, but, as the saying goes, where there’s risk there’s reward. Every miniscule enhancement in the accuracy of your risk scoring engine offers a very real improvement on your ROI and on your cash flow. False positives for bad risk could mean losing custom, false negatives losing your shirt. Credit risk prediction is a responsibility increasingly being handed over to machine learning as it can handle much greater volumes of data to unearth obscure patterns. Credit risk is also a field which suffers more than most from data drift - requiring frequent remodelling. Automated machine learning is the only effective means to keep your credit risk models relevant.

Cross-Selling, Up-Selling

Enhanced abilities to read your customers and predict their needs and propensity to buy can maximise their LTV by identifying up-selling and cross-selling opportunities whilst reducing the damage of unwanted, inappropriate sales pushes.

Customer Churn

Be able to predict the probability of churn of your customers enables you to take pre-emptive action to retain and reward your existing customers with focus and efficiency.

Customer Lifetime Value (LTV)

Understanding the sum worth a customer will bring over the entirety of their relationship is a prized instrument to shape all your interactions, pricing and support. Discovering a high LTV may facilitate targeted attractive pricing to grow your customer base.

Customer Segmentation

Grouping customers into divisions based on their attributes and habits need not be a blunt mechanism. Subtle patterns hidden deep within your data can enable you to realise effective means to talk to your customers with relevance.

Demand Forecasting

Go beyond performance benchmarks and use accurate machine learning predictive models to efficiently manage production scheduling, inventory, marketing campaigns and cash flow. Demand forecasting can have a huge impact on service levels and the reputation of your organisation and drive customer loyalty.

Fraud Detection

Fraud is a reality faced by most businesses. Fraudsters may pose as suppliers, customers or even members of your trusted staff in order to exploit weaknesses and wilfully take from you. Abnormalities may be indicators for potentially fraudulent activity. The accuracy of your fraud prediction model is critical - false negative predictions leave you vulnerable; false positives could destroy your reputation.

Inventory Management

Patterns hidden within your data can be discovered and unlocked using machine learning. Sales analysis and competitor reports may conceal underlying trends. Robotica Machine Learning’s automated, integrated platform can help you to predict when to buy and when to hold, improving cash flow and reducing waste.

Lead Prioritisation

Prioritising the right leads can be the critical factor in not just in gaining a sale but in adopting customers from your competitors. Improve the quality of your sales pipeline and win more business by making better predictions on propensity and engagement.

Next Best Action

Email, text messaging, blog posts, white papers, webinars, and discount vouchers are just a few options when it comes to marketing activities – but which one will be the most effective? Marketers need to know which activities will advance prospects further down the road to purchase without wasting their time and budget on irrelevant or unwanted communications. Next best action models determine which activities will progress each individual down the funnel to purchase, optimising communication strategies and sales.


Matching price to demand is a key activity for any product or service. Machine learning models use historical variations in price and purchase volumes to discover the optimal price to charge for different audiences at different times, optimising profit and return on investment.


Data from the technical and commercial aspects of the supply chain ecosystem can facilitate the strategic stability and flexibility of an organisation by creating predictive models to aid decision-making in selecting, vetting and negotiating with vendors.

Promotions, Upgrades and Offers

Possibly the most well-known and effective means to drive ROI is by well-targeted promotions, offers and discounts. Predictions of customer behaviour, at the level of groups or individuals, facilitates direct, focused offers without excluding the long tail or pricing too low and potentially damaging your brand as well as margin.

Response Rates

Predict the success of a campaigns to see your message reach the right people, produce a clear call to action and earn a strong response rate.

Screening for New Hires

One of the greatest investments an organisation makes is in the people it hires. How effective might this candidate be? How long will they stay? Be on top of the hiring decision process by modelling and predicting outcomes ahead of making offers.

Sentiment Analysis

Consumers often freely volunteer how they feel about a company’s products, services, and operations on social media. Sentiment analysis models predict which words and phrases are indicative of satisfaction or dissatisfaction and how that affects future purchases. This allows marketers to determine if and how customer satisfaction levels have changed over time and informs future product, service, and communication strategies.

Staff Retention

Employee churn predictions can reduce the disruption, cost and intellectual property leakage from your organisation. If you can understand who is likely to churn, you can take proactive measures to reduce the likelihood or mitigate the consequences.

Supply Durability

Quantitatively predict the ability for potential suppliers to deliver according to your scheduling, quality and pricing expectations.

Targeted Discounts

Perfecting the balance of discount to propensity can be used to amplify margins and maintain the perceived value of your offerings.

Warranty Claims Analytics

Supporting warranty claims can cost a lot of cash and reputation. Collections of information from the supply, manufacturing, sales and claims processes can be used to train up predictive models to improve processes in the product journey to optimise the warranty ratio.

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