Brainpool | Artificial Intelligence & Machine Learning Services

Applications & Use-Cases of AI

Churn Prediction

Customer retention is one of the oldest and greatest marketing challenges. In an increasingly competitive environment, being able to identify those customers or segments at risk of churn or turning to a competitor is more important than ever.

Fortunately, companies now have more data and tools to combat churn.
Machine learning can help identify signs of churn and determine the stage of churn, enabling you to intervene and provide incentive for customers to continue engaging with your product or service: improving customer experience, life-time value and profitability.

Industry: Retail, E-commerce, telecommunications, subscription-based service models

Sales Forecasting

Forecasting sales and revenue is fundamental to every business.
These predictions are essential to informing strategies that lead to long-term sustainable growth. It’s also an area many business struggle to perform accurately.

The problem? Traditional methods often don’t reflect the complexity and volatility of the real world such as changing customer behaviors, market conditions or competitor activity.

AI can improve the accuracy of sales forecasting by connecting the dots between the different forces that impact on your business performance.

Predictive Maintenance

Predictive maintenance involves making smarter predictions as to when equipment and machinery will need to be serviced; striking the delicate balance between costs incurred as a result of equipment breakdown versus unnecessary or over frequent servicing.

AI can monitor the condition and performance of equipment in real-time to predict anomalies, advise on repair schedules and even specific components that need to be reviewed or replaced.
All of this means reduced down-time, improved maintenance costs and more efficient operations.

Industries: Manufacturing, Construction, Technology, IT, Oil & Gas, Energy

Organisation Network Mapping

Effective communication is a challenge for every organization. Should the future of work remain decentralized as more people choose to work from home, this challenge may become more complex.

Organisation Network Maps (ONMs) may be the answer. Organisation Network Mapping can provide insight into how departments, teams and individuals communicate, build relationships, exchange information and the flow of decision-making throughout an organization.

These insights can help identify and diagnose bottlenecks and performance issues and inform cultural change initiatives and strategy.

Customer Segmentation & Insights

Effectively segmenting and targeting your customer base is a fundamental pillar of commercial success. But sometimes, it's easier said than done.

Vast, unwieldy and disconnected data sets - sometimes filled with inaccurate or irrelevant information - can make it difficult for an organisations to go beyond superficial segmentation and obtain real insights into the needs of customers and how they change over time.

AI can provide a deeper understanding of your customers by classifying customers into groups based on similar needs, profiles or purchase behaviours. These insights can be channeled into other marketing initiatives, such as targeted promotions and product recommendations.

Targeted Marketing

Artificial Intelligence does more than classify and segment your audience. These customer insights can be integrated into marketing activities to help prioritise advertising and sales efforts; tailoring offers, services and promotions to the needs of specific customers or customer segments based on their needs.

The benefits are clear for businesses and consumers. For business, AI-enhanced marketing can improve efficiency of marketing spend, deliver greater ROI and greater customer engagement.

For consumers, tailored marketing activities mean more relevant offers and promotions, less ‘noise’ and the satisfaction of feeling understood by brands.

Recommendation Systems

Every consumer is different. Recommendation systems are designed to enhance the customer experience by tailoring it to their interests, wants and needs. By analysing different data sources such as customer purchase (or viewing) history, demographics and the history of consumers with similar profiles, the engine delivers personalized recommendations to its customers.

Aside from achieving greater basket size and customer satisfaction, these insights can also provide brands with the information they need to make decisions regarding product listings, inventory levels and new product or content development.

Industries: E-commerce, retail, content streaming

Fraud Detection

With the rise of technology driving more of our banking and purchases online, fraud tactics have become increasingly sophisticated to exploit existing or find new weaknesses in defense systems. Machine Learning is one of the front-line technologies on the fight against fraud.

Its capacity to understand patterns allows it form a baseline of consumer behaviour. This baseline is used to evaluate other transactions; those that align with the pattern and are likely legitimate whereas those that fall outside the potentially indicate fraud. This all happens with milliseconds and allows companies to take action to protect their customers.

Industries: Financial Services, Banking

Supply Chain Optimisation

The key to a healthy supply chain is speed and cost-efficiency at each stage.Inefficiencies and disruptions along the chain can compound; resulting in bottlenecks that can be difficult to pinpoint and resolve without complete transparency across the scope of separate yet integrated functions and processes.

AI represents extensive opportunity to optimise supply chain operations.
From automating repetitive manual tasks, to connecting the different data points at each stage of the chain to improve transparency and real-time intelligence that enabling smarter decisions and faster reaction times.

Industry: logistics, supply chain, transportation, manufacturing, construction

Chatbots

Most people have engaged with a customer service chatbot. But their use goes beyond resolving customer service queries.Chatbots are a powerful tool that can help an organisations engage and service their customers at scale.

How can chatbots help support your business? alleviate strain on limited human resources by managing a part or the entire customer engagement help identify and prioritise business-critical problems resolve low-complexity problems and provide faster problem resolution help customers troubleshoot and solve problems themselves.

Industries: Travel, Banking, Insurance, Technology, IT, sales, healthcare

Credit Decisions

Credit decisions involve a delicate balance between the lender fulfilling their regulatory responsibilities with the ethical duty to extend credit to applicants able to service the loan.

This process can be more complicated by insufficient data relating to credit history, risk profile and human bias in the decision-making process.

AI can help make faster, better and fairer credit decisions by classifying new applications based on historical similarities and distinguishing applicants at high risk of default from credit worthy applicants.

Industries: finance, banking

Process Automation

Technology enables organisations to streamline processes, performing them faster and more efficiently. Organisations are packed with processes, so there is ample opportunity for businesses to benefit through process automation. The challenge is identifying which processes should be optimised, the role of technology in the new workflow and rethinking the role of humans. After all, the benefits isn’t just for organisations. Process automation can liberate the workforce from performing repetitive and un-stimulating tasks that can be performed reliably by machines. That means people spend more time on tasks humans excel at, such as critical and creative thinking, building relationships and solving complex problems.

There are many different names and approaches to automation, such as Robotic Process Automation (RPA) and Business Process Automation (BPA). But they all aim to achieve the same thing; effectively integrating tools, people and processes to achieve better business outcomes.

AI-Driven Design

The ability to appreciate and be inspired by beauty to shape our environment is part of what makes us human. So it’s no surprise that design is also an area being rapidly transformed by AI.

How AI-driven design can be applied will depend on your industry. But the central theme is that AI can augment human creativity: enabling more personalised, cost effective and impactful designs, delivered faster and at scale.

Industries: construction, manufacturing, graphic design, advertising, website and software development

Content Creation

Does your marketing team spend hours agonizing over copy and spend hours striving to craft the right message to cut through the noise, capture audience attention and motivate action?

Content creation can be made faster, easier and more tailored using AI. AI can be used to generate and curate content across multiple channels and consumer touchpoints such as social media, email, newsletters and even chatbots. In the future, AI may even be capable of more complex language generation enabling it to write novels, films and even company earnings reports.

Document analysis

The amount of text information that people need to manage can be overwhelming. Natural Language Programming (NLP) is an area of AI that can manage this data inundation to process documents faster and more accurately than humans alone.

Document analysis can analyse, interpret and understand documents at scale by extracting the key themes and concepts, transcribing technical clauses and jargon into simple language and summarizing text.

That means less time trying to search for vital information in towers of documentation or trying to interpret and explain complex jargon and concepts, and more time acting on information that’s readily understandable and actionable.

Industries: law, medicine, healthcare, business

Dynamic Pricing

Dynamic pricing has traditionally been popular in industries such as travel or hospitality, where pricing is based on seasonality (e.g. summer) or time (i.e. weekend peak periods). The move to online and the evolving capability of technology has driven the growth in popularity of this pricing model as businesses are able to more data that helps them understand market needs and demands.

Dynamic pricing tools can help reduce waste, be more competitive and respond to market demand and help consumers find great value offers.

Industries: airlines, ride sharing services, gig economy, utilities (gas, electricity), hospitality, events, retail and e-commerce

Logistics Optimisation

Logistics is an industry on the edge of radical transformation driven by AI. From the introduction of robots capable of completely automating picking and packing to the eventual use of self-driving trucks on our roads, the future of logistics looks to be firmly in the proverbial (and possibly literal) hands of AI.

But the value add of AI for logistics isn’t in the next 5-10 years or dependent on smart new hardware requiring huge CAPEX investment. The opportunity is now - and focuses on doing the basics better, smarter and more efficiently. From selecting the best locations for new warehouses and storage facilities, planning more efficient routes to decrease travel time and ensuring that fleets are packed to optimum capacity every time.

AI driven Business Intelligence

Business Intelligence (BI) is a term that encapsulates the use of software and applications to collect and analyse data to derive insights that inform action and help business leaders make data-driven decisions and gives them an edge against competitors.

Traditional approaches to BI have focused on descriptive analytics – analysis of what happened in the past – to understand how certain factors resulted in certain outcomes. The predictive power of machines heralds the dawn of a new for BI and a shift in focus from the past to the future; from what was to what will be. The driving force behind these are the rise of predictive and prescriptive analytics; the ability to predict future scenarios and events and providing advice on the best course of action through better understanding why these events will occur.

AI isn’t about replacing business intelligence, it’s about creating a whole new set of capability that will change the way we do business.