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• Top 5 Customer Segmentation Software in 2024

  12 mars 2024, par Erin

  In marketing, we all know the importance of reaching the right customer with the right message at the right time. That’s how you cut through the noise.

  For that, you need data on your customers — even though gathering the data is not enough. You can have all the data worldwide, but that raises an ethical responsibility and the need to make sense of it.

  Enter customer segmentation software — the answer to delivering personalised customer experiences at scale. 

  This article lists some of the best customer segmentation tools currently in the market. 

  We’ll also go over the benefits of using such tools and how you can choose the best one for your business.

  Let’s get started !

  What is customer segmentation software ?

  Customer segmentation software is a tool that helps businesses analyse customer data and group them based on common characteristics like age, income, and buying habits.

  The main goal of customer segmentation is to gain deeper insights into customer behaviours and preferences. This helps create targeted marketing and product strategies that fit each group and makes it easier to predict how customers will behave in the future.

  

  Benefits of a customer segmentation software

  Understanding your customers is the cornerstone of effective marketing, and customer segmentation software plays a pivotal role in this endeavour. 

  You can deliver more targeted and relevant marketing campaigns by dividing your audience into distinct groups based on shared characteristics. 

  Specifically, here are the main benefits of using customer segmentation tools :

  • Understand your audience better : The software helps businesses group customers with common traits to better understand their preferences and behaviour.
  • Make data-driven decisions : Base your business and marketing decisions on data analytics.
  • Aid product development : Insights from segmentation analytics can guide the creation of products that meet specific customer group needs.
  • Allocate your resources efficiently : Focusing on the customer segments that generate the most revenue leads to more effective and strategic use of your marketing resources.

  Best customer segmentation software in 2024 

  In this section, we go over the top customer segmentation tools in 2024. 

  We’ll look at these tools’ key features and pros and cons.

  1. Matomo

  

  Matomo is a comprehensive web analytics tool that merges traditional web analytics, such as tracking pageviews and visitor bounce rates, with more advanced web analytics features for tracking user behaviour. 

  With robust segmentation features, users can filter website traffic based on criteria such as location and device type, enabling them to analyse specific visitor groups and their behaviour. Users can create custom segments to analyse specific groups of visitors and their behaviour.

  Presenting as the ethical alternative to Google Analytics, Matomo emphasises transparency, 100% accurate data, and compliance with privacy laws.

  Key features

  • Heatmaps and Session Recordings : Matomo provides tools that allow businesses to understand website user interactions visually. This insight is crucial for optimising user experience and increasing conversions.
  • Form Analytics : This feature in Matomo tracks how users interact with website forms, helping businesses understand user behaviour in detail and improve form design and functionality.
  • User Flow Analysis : The tool tracks the journey of a website’s visitors, highlighting the paths taken and where users drop off. This is key for optimising website structure for better user experience and more conversions.
  • A/B Testing : Businesses can use Matomo to test different versions of web pages, determining which is more effective in driving conversions.
  • Conversion Funnels : This feature allows businesses to visualise and optimise the steps customers take toward conversion, identifying areas for improvement.

  Pros 

  • Affordability : With plans starting at $19 per month, Matomo is a cost-effective solution for CRO.
  • Free support : Matomo provides free email support to all Matomo Cloud users.
  • Open-source benefits : Being open-source, Matomo offers enhanced security, privacy, customisation options, and a supportive community.
  • Hosting options : Matomo is available either as a self-hosted solution or cloud-hosted.

  Cons

  • Cost for advanced features : Access to advanced features may incur additional costs for Matomo On-Premise users, although the On-Premise solution itself is free.
  • Technical knowledge required : The self-hosted version of Matomo requires technical knowledge for effective management.

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  2. Google Analytics 

  

  Google Analytics 4 (GA4) comprehensively understands website and app performance. It focuses on event-based data collection, allowing businesses to understand user interactions across platforms. 

  Similarly to Matomo, GA4 provides features that allow businesses to segment their audience based on various criteria such as demographics, behaviours, events, and more.

  Key features

  • Event-based tracking : GA4’s shift to an event-based model allows for a flexible and predictive analysis of user behaviour. This includes a detailed view of user interactions on websites and apps.
  • Machine Learning and Smarter Insights : GA4 uses machine learning to automatically detect trends, estimate purchase probabilities and provide marketing insights.
  • Google Ads integration : The integration with Google Ads in GA4 enables tracking customer interactions from first ad engagement, providing a holistic view of the customer experience across various platforms.
  • Customer-centric measurements : GA4 collects data as events, covering a wide range of user interactions and offering a comprehensive view of customer behaviour.
  • Pathing reports : GA4 introduces new pathing reports, allowing detailed user flow analysis through websites and apps.
  • Audiences and filters : GA4 allows the creation of audiences based on specific criteria and the application of filters to segment and refine data analysis.

  Pros 

  • Integration with various platforms, including Google Ads, enhances cross-platform user journey analysis.
  • GA4 has a clean reporting interface, making it easier for marketers to identify key trends and data irregularities.
  • Google Analytics has an active community with an abundance of educational resources available for users.

  Cons

  • Complexity for beginners : The wide range of features and new event-based model might overwhelm users new to analytics tools.
  • Dependence on machine learning : Reliance on machine learning for insights and predictions may require trust in the tool’s data processing and large volumes of traffic for accuracy.
  • Transition from UA to GA4 : Users familiar with Universal Analytics (UA) might find the transition to GA4 challenging due to differences in features and data models.

  3. HubSpot

  

  HubSpot is a marketing and sales software that helps businesses attract visitors and turn them into paying customers. 

  It supports various business processes, from social media posts to email marketing, sales, and customer service. HubSpot organises and tracks user interactions across different channels, providing a unified and efficient approach to customer relationship management (CRM) and customer segmentation.

  Businesses can leverage HubSpot’s customer segmentation through lists, workflows, and smart content.

  Key features

  • Integration capabilities : HubSpot offers over 1,000 integrations in its ecosystem, ensuring seamless connectivity across various marketing, sales, and service tools, which helps maintain data consistency and reduces manual efforts.
  • Segmentation and personalisation : HubSpot allows businesses to deliver personalised content and interactions based on customer behaviour and preferences, using its robust CRM features and advanced automation capabilities.

  Pros 

  • Comprehensive support : HubSpot offers a range of support options, including a knowledge base, real-time chat, and more.
  • User-friendly interface : The platform is designed for ease of use, ensuring a smooth experience even for less tech-savvy users.
  • Personalisation capabilities : HubSpot provides personalised marketing, sales and service experiences, leveraging customer data effectively.

  Cons

  • High price point : HubSpot can be expensive, especially as you scale up and require more advanced features.
  • Steep learning curve : For businesses new to such comprehensive platforms, there might be an initial learning curve to utilise its features effectively.

  4. Klaviyo

  

  Klaviyo is a marketing automation software primarily focused on email and SMS messaging for e-commerce businesses. It’s designed to personalise and optimise customer communication. 

  Klaviyo integrates with e-commerce platforms like Shopify, making it a go-to solution for online stores. Its strength lies in its ability to use customer data to deliver targeted and effective marketing campaigns.

  Key features

  • Email marketing automation : Klaviyo allows users to send automated and personalised emails based on customer behaviour and preferences. This feature is crucial for e-commerce businesses in nurturing leads and maintaining customer engagement.
  • SMS marketing : It includes SMS messaging capabilities, enabling businesses to engage customers directly through text messages.
  • Segmentation and personalisation : Klaviyo offers advanced segmentation tools that enable businesses to categorise customers based on their behaviour, preferences and purchase history, facilitating highly targeted marketing efforts.
  • Integration with e-commerce platforms : Klaviyo integrates with popular e-commerce platforms like Shopify, Magento, and WooCommerce, allowing easy data synchronisation and campaign management.

  Pros 

  • Enhanced e-commerce integration : Klaviyo’s deep integration with e-commerce platforms greatly benefits online retailers regarding ease of use and campaign effectiveness.
  • Advanced segmentation and personalisation : The platform’s strong segmentation capabilities enable businesses to tailor their marketing messages more effectively.
  • Robust automation features : Klaviyo’s automation tools are powerful and user-friendly, saving time and improving marketing efficiency.

  Cons

  • Cost : Klaviyo can be more expensive than other options in this list, particularly as you scale up and add more contacts.
  • Complexity for beginners : The platform’s wide range of features and advanced capabilities might overwhelm beginners or small businesses with simpler needs.

  5. UserGuiding

  

  UserGuiding is a no-code product adoption tool that lets businesses create in-app user walkthroughs, guides, and checklists to onboard, engage, and retain users.

  UserGuiding facilitates customer segmentation by enabling businesses to create segmented onboarding flows, analyse behavioural insights, deliver personalised guidance, and collect feedback tailored to different user segments.

  Key features

  • In-app walkthroughs, guides and checklists : UserGuiding has multiple features that can promote product adoption early in the user journey.
  • In-app messaging : UserGuiding offers in-app messaging to help users learn more about the product and various ways to get value.
  • User feedback : UserGuiding allows businesses to gather qualitative feedback to streamline the adoption journey for users.

  Pros 

  • User-friendly interface
  • Customisable onboarding checklists
  • Retention analytics

  Cons

  • Need for technical expertise to maximise all features
  • Limited customisation options for less tech-savvy users

  What to look for in a customer segmentation software 

  When choosing a customer segmentation software, choosing the right one for your specific business needs is important. 

  Here are a few factors to consider when choosing your customer segmentation tool :

  1. Ease of use : Select a tool with an intuitive interface that simplifies navigation. This enhances the user experience, making complex tasks more manageable. Additionally, responsive customer support is crucial. It ensures that issues are promptly resolved, contributing to a smoother operation.
  2. Scalability and flexibility : Your chosen tool should adjust to your needs. A flexible tool like Matomo can adjust to your growing requirements, offering capabilities that evolve as your business expands.
  3. Integration capabilities : The software should seamlessly integrate with your existing systems, such as CRM, marketing, and automation platforms. 
  4. Advanced analytics and reporting : Assess the software’s capability to analyse and interpret complex data sets, without relying on machine learning to fill data gaps. A robust tool should provide accurate insights and detailed reports, enabling you to make informed decisions based on real data.
  5. Privacy and security considerations : Data security is paramount in today’s digital landscape. Look for features like data encryption, security storage, and adherence to privacy standards like GDPR and CCPA compliance. 
  6. Reviews and recommendations : Before making a decision, consider the reputation of the software providers. Look for reviews and recommendations from other users, especially those in similar industries. This can provide real-world insights into the software’s performance and reliability.

  

  Leverage Matomo’s segmentation capabilities to deliver personalised experiences

  Segmentation is the best place to start if you want to deliver personalised customer experiences. There are several customer segmentation software in the market. But they’re not all the same.

  In this article, we reviewed the top segmentation tools — based on factors like their user base, features, and ethical data privacy considerations.

  Ideally, you want a tool to support your evolving business and segmentation needs. Not to mention one that cares about your customers’ privacy and ensures you stay compliant. 

  Enter Matomo at the top of the list. You can leverage Matomo’s accurate insights and comprehensive segmentation capabilities without compromising on privacy. Try it free for 21-days. No credit card required.

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• How to Increase Conversions With Form Analysis

  30 janvier 2024, par Erin

  Forms are one of the most important elements of your website. They are also one of the most difficult elements to analyse and improve. 

  Unlike a webpage, forms aren’t all that easy to analyse with standard web analytics tools. You need to learn how to conduct form analysis if you want to improve your forms’ conversion rates and increase revenue. 

  In this article, we’ll explain what form analysis is and why conducting a thorough form analysis is so important. 

  What is form analysis ?

  Form analysis is a process that measures the effectiveness of your forms. Form analysis uses several tools and techniques like a form analytics platform, heatmaps, and session recordings to collect user data and understand how visitors behave when filling in forms. 

  The goal is to improve the design and effectiveness of your forms, reducing abandonment rate and encouraging more users to submit them. 

  There are plenty of reasons visitors could be having trouble with your forms, from confusing form fields to poor design and lengthy verification processes. Form analytics can help you pinpoint why your form’s conversion rate is so low or why so many users abandon your form halfway through filling it in. 

  Why is form analysis important ?

  Website forms have some of the highest bounce rates and abandonments of any website element. By analysing your forms, you can achieve the following outcomes :

  

  Reduce form abandonment

  When it’s tough enough to get users to start filling in your form, the last thing you want them to do is abandon it halfway through. But that’s probably what your users are doing more than you’d like to think. 

  Why are they abandoning it ? Even if you’re humble enough to admit you didn’t create the greatest form the world’s ever seen, it can still be incredibly difficult to pin down why users give up on your form.

  That’s unless you conduct a form analysis. By analysing metrics and user behaviour, you can pinpoint and rectify the issues that cause users to abandon your form. 

  Improve the user experience

  Best practices will only take you so far. How users behave when filling in a form on your website may be completely different to how they behave on another site. That’s why you need to use form analysis to understand how users behave specifically on your website — and then use that information to optimise the design, layout, and content of the form to better suit them. 

  If one field is regularly left empty, for example, you can delete it. If users spend several minutes filling out a form with a high abandonment rate, you could shorten it. 

  The goal isn’t to make the best form ever but to make the best form for your audience. 

  Increase conversions

  Ultimately, form analysis helps you improve your form’s most important metric : conversions. Reducing your abandonment rate will naturally lead to more completions, but so will taking advantage of other optimisation opportunities that only become clear with form analysis. This can include optimisations like :

  • Moving the form higher up on the page
  • Shortening the form
  • Changing the heading and CTAs
  • Renaming field labels 

  A thorough form analysis process can ensure your forms generate as many conversions as possible. 

  Why do users abandon forms ?

  Are you already suffering from high form abandonment rates ? Don’t worry, you’re not alone. Marketers regularly make the same mistakes when creating forms that cause users to give up halfway through completion.

  Here are some of the most common reasons for form abandonment :

  • There are too many steps. If you’re telling users they’ve just completed step 2 of 12, you can bet they won’t bother finishing your form. 
  • They ask for too much information. No one wants to fill out a long form, and often, users won’t have the information on hand if you ask for too much. Just look at the rate left blank from the Unneeded Fields report in the screenshot below :

  

  • The form is confusing. Unclear form fields or directions can put users off. 
  • All the fields are free text and time-consuming. Filling out forms with long text fields takes too much time. To speed things up, use dropdown options in the fields, but keep the options to a minimum. This not only helps users finish the form faster but also makes it easier to analyse the data later because it keeps the data format consistent so you can organise the information more efficiently. 
  • Users don’t trust the form. This is a particular problem on checkout pages where users are entering sensitive information.

  How to conduct form analysis

  You need to collect user behaviour data to effectively analyse your forms. But a lot of traditional website analytics tools won’t have the required functionality. 

  Matomo is different. Our web analytics solution offers comprehensive web analytics as well as additional features like Heatmaps, Session Recordings, A/B Testing, and Form Analytics to provide all the functionality you need. 

  Now if you don’t use Matomo, you can try it free for 21 days (no credit card required) to see if it’s the right tool for you.

  Whether you use Matomo or not is up to you. But, once you have a suitable tool in place, just follow the steps below to conduct a form analysis. 

  Check your analytics

  Tracking and analysing specific form metrics should be the first place you start. We recommend collecting data on the following metrics :

  • Form starter rate : the percentage of visitors who actually start to fill in your form
  • Completion rate : the percentage of visitors who complete the form
  • Form abandonment rate : the percentage of users who gave up filling in your form
  • Time spent completing your form : the average length of time users spend on your form

  Let’s look at these metrics are in Matomo’s Form Analytics :

  

  The dashboard shows an overview of these metrics over a given period, allowing you to see at a glance whether there are issues you need to rectify. 

  Next, deep dive into the performance of each form to see things like :

  • Drop off fields
  • Unused fields
  • Entry field
  • Most corrected fields 

  You can even use Matomo’s visitor log to see who’s behind every submission.

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  Use a heatmap

  A heatmap is a colour-based graphical representation of data. A heatmap will show what users to do on your website, including : 

  • How far they scroll
  • Which buttons they click on
  • Where they focus their attention

  When used on a webpage with a form, you’ll be able to see how often users interact with your form based on the heatmap colour, with warmer colours representing greater engagement levels.

  Let’s look at a heatmap in Matomo :

  

  This heatmap is showing us how far down users have scrolled. It’s clear that only 63% of visitors are reaching the point above our call to action to see all features. We might want to consider moving that call to action up in order to get more engagement. 

  A heatmap is a great way to see whether your form’s placement gets the level of attention you want from visitors and to what extent visitors interact with your field.

  Record user sessions

  Session replays go even further than heatmaps, recording a real-life user interacting with your site. It’s like looking over a visitor’s shoulder while they use your site.

  

  With Matomo, you can record any sessions where the user takes a certain action (like starting to fill in a form), allowing you to build a rich library of qualitative data. 

  You can then replay a recorded session at your leisure to understand exactly how users interact with your forms.

  Segment users

  If you really want to understand how visitors use your forms, then it’s essential to segment your data. 

  You can segment all Form Analytics reports by over 100 pre-built segments in Matomo.

  

  One way to segment your data is by comparing the average time on form of those who completed the form with those who abandoned it. 

  If users abandon a form quickly, that could indicate your form is irrelevant to this audience or too long. If users spend a lot of time on the form, however, it’s probably safe to assume that it is relevant but there is something wrong with the form itself. 

  Looking at the Field Timings report will help you pinpoint which field visitors are spending the most time on and causing frustration. 

  

  The Field Timings example report in Matomo above, it’s evident that the “Overview of your needs” field takes up the most time (avg. time spent is 1 min 40s). To improve this, we might want to change it to a dropdown field. This way, users can quickly select options, and if necessary, provide additional details.

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  Another way is to segment data by traffic source and compare each source’s conversion rate. This will show whether one traffic source converts better than another or if one source isn’t interested in your form at all.

  How to optimise web forms

  Want to implement what you’ve learnt from your form analysis ? Follow these steps to optimise your existing web forms. 

  Define your form’s purpose

  The first step in optimising your existing web forms is to give a clear and definitive purpose to every single one. 

  When you have a defined goal, creating a form users will complete is much easier. After all, if you don’t know why people should fill in one of your forms, how would a visitor possibly know ?

  Take a look at one of our forms below :

  

  The purpose of this form is to get users to sign up for a free trial of our web analytics platform, and every element works towards that goal :

  • The headline directs the user to take action
  • The copy explains that it’s a free trial that doesn’t require credit card details
  • The green call-to-action button reinforces the action and benefit 
  • There is validation to support this under the form – “Trusted on over 1 million websites in over 190+ countries”

  Our clear instructions leave users no doubt about why they should fill in the form or what will happen. 

  Choose the right type of form

  You can use several forms on your website, each with different designs, form fields, and goals.

  For example :

  • Registration forms are fairly minimalist and designed to collect the least amount of data possible. 
  • Contact forms are concise so that it’s easy for potential customers to reach your team. 
  • Checkout forms balance a need to collect important data with a streamlined design that doesn’t put users off.
  • Lead generation forms are compelling and usually include qualifying questions so sales teams can score leads.

  Make sure you are using the right type of form to avoid abandonments and other issues. For example, requiring users to fill in a lengthy lead generation-style form when you want them to sign up for a free trial will probably kill your conversion rate. 

  Test form elements

  If your form analysis has shed light on one or two issues, you can use A/B or multivariate testing to trial new elements or designs and see how they compare.

  There’s no shortage of elements you can test, including the form’s :

  • Headline
  • Placement
  • Design
  • CTA button
  • Colour-scheme
  • Length
  • Form fields

  

  Matomo makes it easy to create and run A/B tests on your website’s forms. 

  Move your form above the fold

  One of the simplest ways to optimise your web form is to move it above the fold — that’s the section of the screen users see when they load your page. 

  Why ? Well, the more people who see your form, the more people will fill it in. And when it’s above the fold, users can’t help but see it.

  Conclusion

  Forms are one of the most important elements on your website, so why not treat them as such and regularly run a thorough form analysis ? By doing so, you’ll identify ways to optimise your form, improve the user experience, and improve conversions. 

  Matomo is the best platform for conducting form analysis. Our combination of web analytics, Form Analytics, Session Recordings, and Heatmaps means you have all the tools you need to learn exactly how visitors interact with your forms. 

  See just how powerful Matomo’s tools are by starting a free 21-day trial, no credit card required. 

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

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• How HSBC and ING are transforming banking with AI

  9 novembre 2024, par Daniel Crough — Banking and Financial Services, Featured Banking Content

  We recently partnered with FinTech Futures to produce an exciting webinar discussing how analytics leaders from two global banks are using AI to protect customers, streamline operations, and support environmental goals.

  Watch the on-demand webinar : Advancing analytics maturity.

  Email

  By providing your email and clicking “submit”, you agree to receive direct marketing materials relating to Matomo products and services, surveys, information about events, publications and promotions. You can unsubscribe at any time by clicking the opt-out link provided in each communication. We will process your personal information in accordance with our Privacy Policy.

  
  
  
  
  

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  Meet the expert panel

  Roshini Johri heads ESG Analytics at HSBC, where she leads AI and remote sensing applications supporting the bank’s net zero goals. Her expertise spans climate tech and financial services, with a focus on scalable analytics solutions.

   

  Marco Li Mandri leads Advanced Analytics Strategy at ING, where he focuses on delivering high-impact solutions and strengthening analytics foundations. His background combines analytics, KYC operations, and AI strategy.

   

  Carmen Soini Tourres works as a Web Analyst Consultant at Matomo, helping financial organisations optimise their digital presence whilst maintaining privacy compliance.

   

  Key findings from the webinar

  The discussion highlighted four essential elements for advancing analytics capabilities :

  1. Strong data foundations matter most

  “It doesn’t matter how good the AI model is. It is garbage in, garbage out,”

  Johri explained. Banks need robust data governance that works across different regulatory environments.

  2. Transform rather than tweak

  Li Mandri emphasised the need to reconsider entire processes :

  “We try to look at the banking domain and processes and try to re-imagine how they should be done with AI.”

  3. Bridge technical and business understanding

  Both leaders stressed the value of analytics translators who understand both technology and business needs.

  “We’re investing in this layer we call product leads,”

  Li Mandri explained. These roles combine technical knowledge with business acumen – a rare but vital skill set.

  4. Consider production costs early

  Moving from proof-of-concept to production requires careful planning. As Johri noted :

  “The scale of doing things in production is quite massive and often doesn’t get accounted for in the cost.”

  This includes :

  • Ongoing monitoring requirements
  • Maintenance needs
  • Regulatory compliance checks
  • Regular model updates

  Real-world applications

  ING’s approach demonstrates how banks can transform their operations through thoughtful AI implementation. Li Mandri shared several areas where the bank has successfully deployed analytics solutions, each benefiting both the bank and its customers.

  Customer experience enhancement

  The bank’s implementation of AI-powered instant loan processing shows how analytics can transform traditional banking.

  “We know AI can make loans instant for the customer, that’s great. Clicking one button and adding a loan, that really changes things,”

  Li Mandri explained. This goes beyond automation – it represents a fundamental shift in how banks serve their customers.

  The system analyses customer data to make rapid lending decisions while maintaining strong risk assessment standards. For customers, this means no more lengthy waiting periods or complex applications. For the bank, it means more efficient resource use and better risk management.

  The bank also uses AI to personalise customer communications.

  “We’re using that to make certain campaigns more personalised, having a certain tone of voice,”

  noted Li Mandri. This particularly resonates with younger customers who expect relevant, personalised interactions from their bank.

  Operational efficiency transformation

  ING’s approach to Know Your Customer (KYC) processes shows how AI can transform resource-heavy operations.

  “KYC is a big area of cost for the bank. So we see massive value there, a lot of scale,”

  Li Mandri explained. The bank developed an AI-powered system that :

  • Automates document verification
  • Flags potential compliance issues for human review
  • Maintains consistent standards across jurisdictions
  • Reduces processing time while improving accuracy

  This implementation required careful consideration of regulations across different markets. The bank developed monitoring systems to ensure their AI models maintain high accuracy while meeting compliance standards.

  In the back office, ING uses AI to extract and process data from various documents, significantly reducing manual work. This automation lets staff focus on complex tasks requiring human judgment.

  Sustainable finance initiatives

  ING’s commitment to sustainable banking has driven innovative uses of AI in environmental assessment.

  “We have this ambition to be a sustainable bank. If you want to be a sustainable finance customer, that requires a lot of work to understand who the company is, always comparing against its peers.”

  The bank developed AI models that :

  • Analyse company sustainability metrics
  • Compare environmental performance against industry benchmarks
  • Assess transition plans for high-emission industries
  • Monitor ongoing compliance with sustainability commitments

  This system helps staff evaluate the environmental impact of potential deals quickly and accurately.

  “We are using AI there to help our frontline process customers to see how green that deal might be and then use that as a decision point,”

  Li Mandri noted.

  HSBC’s innovative approach

  Under Johri’s leadership, HSBC has developed several groundbreaking uses of AI and analytics, particularly in environmental monitoring and operational efficiency. Their work shows how banks can use advanced technology to address complex global challenges while meeting regulatory requirements.

  Environmental monitoring through advanced technology

  HSBC uses computer vision and satellite imagery analysis to measure environmental impact with new precision.

  “This is another big research area where we look at satellite images and we do what is called remote sensing, which is the study of a remote area,”

  Johri explained.

  The system provides several key capabilities :

  • Analysis of forest coverage and deforestation rates
  • Assessment of biodiversity impact in specific regions
  • Monitoring of environmental changes over time
  • Measurement of environmental risk in lending portfolios

  “We can look at distant images of forest areas and understand how much percentage deforestation is being caused in that area, and we can then measure our biodiversity impact more accurately,”

  Johri noted. This technology enables HSBC to :

  • Make informed lending decisions
  • Monitor environmental commitments of borrowers
  • Support sustainability-linked lending programmes
  • Provide accurate environmental impact reporting

  Transforming document analysis

  HSBC is tackling one of banking’s most time-consuming challenges : processing vast amounts of documentation.

  “Can we reduce the onus of human having to go and read 200 pages of sustainability reports each time to extract answers ?”

  Johri asked. Their solution combines several AI technologies to make this process more efficient while maintaining accuracy.

  The bank’s approach includes :

  • Natural language processing to understand complex documents
  • Machine learning models to extract relevant information
  • Validation systems to ensure accuracy
  • Integration with existing compliance frameworks

  “We’re exploring solutions to improve our reporting, but we need to do it in a safe, robust and transparent way.”

  This careful balance between efficiency and accuracy exemplifies HSBC’s approach to AI.

  Building future-ready analytics capabilities

  Both banks emphasise that successful analytics requires a comprehensive, long-term approach. Their experiences highlight several critical considerations for financial institutions looking to advance their analytics capabilities.

  Developing clear governance frameworks

  “Understanding your AI risk appetite is crucial because banking is a highly regulated environment,”

  Johri emphasised. Banks need to establish governance structures that :

  • Define acceptable uses for AI
  • Establish monitoring and control mechanisms
  • Ensure compliance with evolving regulations
  • Maintain transparency in AI decision-making

  Creating solutions that scale

  Li Mandri stressed the importance of building systems that grow with the organisation :

  “When you try to prototype a model, you have to take care about the data safety, ethical consideration, you have to identify a way to monitor that model. You need model standard governance.”

  Successful scaling requires :

  • Standard approaches to model development
  • Clear evaluation frameworks
  • Simple processes for model updates
  • Strong monitoring systems
  • Regular performance reviews

  Investing in people and skills

  Both leaders highlighted how important skilled people are to analytics success.

  “Having a good hiring strategy as well as creating that data literacy is really important,”

  Johri noted. Banks need to :

  • Develop comprehensive training programmes
  • Create clear career paths for analytics professionals
  • Foster collaboration between technical and business teams
  • Build internal expertise in emerging technologies

  Planning for the future

  Looking ahead, both banks are preparing for increased regulation and growing demands for transparency. Key focus areas include :

  • Adapting to new privacy regulations
  • Making AI decisions more explainable
  • Improving data quality and governance
  • Strengthening cybersecurity measures

  Practical steps for financial institutions

  The experiences shared by HSBC and ING provide valuable insights for financial institutions at any stage of their analytics journey. Their successes and challenges outline a clear path forward.

  Key steps for success

  Financial institutions looking to enhance their analytics capabilities should :

  1. Start with strong foundations
     • Invest in clear data governance frameworks
     • Set data quality standards
     • Build thorough documentation processes
     • Create transparent data tracking
  2. Think strategically about AI implementation
     • Focus on transformative rather than small changes
     • Consider the full costs of AI projects
     • Build solutions that can grow
     • Balance innovation with risk management
  3. Invest in people and processes
     • Develop internal analytics expertise
     • Create clear paths for career growth
     • Foster collaboration between technical and business teams
     • Build a culture of data literacy
  4. Plan for scale
     • Establish monitoring systems
     • Create governance frameworks
     • Develop standard approaches to model development
     • Stay flexible for future regulatory changes

  Learn more

  Want to hear more insights from these industry leaders ? Watch the complete webinar recording on demand. You’ll learn :

  • Detailed technical insights from both banks
  • Extended Q&A with the speakers
  • Additional case studies and examples
  • Practical implementation advice

   

   

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  Watch the on-demand webinar : Advancing analytics maturity.

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