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• A Guide to Bank Customer Segmentation

  18 juillet 2024, par Erin

  Banking customers are more diverse, complex, and demanding than ever. As a result, banks have to work harder to win their loyalty, with 75% saying they would switch to a bank that better fits their needs.

  The problem is banking customers’ demands are increasingly varied amid economic uncertainties, increased competition, and generational shifts.

  If banks want to retain their customers, they can’t treat them all the same. They need a bank customer segmentation strategy that allows them to reach specific customer groups and cater to their unique demands.

  What is customer segmentation ?

  Customer segmentation divides a customer base into distinct groups based on shared characteristics or behaviours.

  This allows companies to analyse the behaviours and needs of different customer groups. Banks can use these insights to target segments with relevant marketing throughout the customer cycle, e.g., new customers, inactive customers, loyal customers, etc.

  You combine data points from multiple segmentation categories to create a customer segment. The most common customer segmentation categories include :

  • Demographic segmentation
  • Website activity segmentation
  • Geographic segmentation
  • Purchase history segmentation
  • Product-based segmentation
  • Customer lifecycle segmentation
  • Technographic segmentation
  • Channel preference segmentation
  • Value-based segmentation

  

  By combining segmentation categories, you can create detailed customer segments. For example, high-value customers based in a particular market, using a specific product, and approaching the end of the lifecycle. This segment is ideal for customer retention campaigns, localised for their market and personalised to satisfy their needs.

  

  Matomo’s privacy-centric web analytics solution helps you capture data from the first visit. Unlike Google Analytics, Matomo doesn’t use data sampling (more on this later) or AI to fill in data gaps. You get 100% accurate data for reliable insights and customer segmentation.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

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  Why is customer segmentation important for banks ?

  Customer segmentation allows you to address the needs of specific groups instead of treating all of your customers the same. This has never been more important amid a surge in bank switching, with three in four customers ready to switch to a provider that better suits their needs.

  Younger customers are the most likely to switch, with 19% of 18-24 year olds changing their primary bank in the past year (PDF).

  Customer expectations are changing, driven by economic uncertainties, declining trust in traditional banking, and the rise of fintech. Even as economic pressures lift, banks need to catch up with the demands of maturing millennials, Gen Z, and future generations of banking customers.

  Switching is the new normal, especially for tech-savvy customers encouraged by an expanding world of digital banking options.

  To retain customers, banks need to know them better and understand how their needs change over time. Customer retention provides the insights banks need to understand these needs at a granular level and the means to target specific customer groups with relevant messages.

  At its core, customer segmentation is essential to banks for two key reasons :

  • Customer retention : Holding on to customers for longer by satisfying their personal needs.
  • Customer lifetime value : Maximising ongoing customer revenue through retention, purchase frequency, cross-selling, and upselling.

  Here are some actionable bank customer segmentation strategies that can achieve these two objectives :

  Prevent switching with segment analysis

  Use customer segmentation to prevent them from switching to rivals by knowing what they want from you. Analyse customer needs and how they change throughout the lifecycle. Third-party data reveals general trends, but what do your customers want ?

  

  Use first-party customer data and segmentation to go beyond industry trends. Know exactly what your customers want from you and how to deliver targeted messages to each segment — e.g., first-time homebuyers vs. retirement planners.

  Keep customers active with segment targeting

  Target customer segments to keep customers engaged and motivated. Create ultra-relevant marketing messages and deliver them with precision to distinct customer segments. Nurture customer motivation by continuing to address their problems and aspirations.

  Improve the quality of services and products

  Knowing your customers’ needs in greater detail allows you to adapt your products and messages to cater to the most important segments. Customers switch banks because they feel their needs are better met elsewhere. Prevent this by implementing customer segmentation insights into product development and marketing.

  Personalise customer experiences by layering segments

  Layer segments to create ultra-specific target customer groups for personalised services and marketing campaigns. For example, top-spending customers are one of your most important segments, but there’s only so much you can do with this. However, you can divide this group into even narrower target audiences by layering multiple segments.

  For example, segmenting top-spending customers by product type can create more relevant messaging. You can also segment recent activity and pinpoint specific usage segments, such as those with a recent drop in transactions.

  Now, you have a three-layered segment of high-spending customers who use specific products less often and whom you can target with re-engagement campaigns.

  Maximise customer lifetime value

  Bringing all of this together, customer segmentation helps you maximise customer lifetime value in several ways :

  • Prevent switching
  • Enhance engagement and motivation
  • Re-engage customers
  • Cross-selling, upselling
  • Personalised customer loyalty incentives

  The longer you retain customers, the more you can learn about them, and the more effective your lifetime value campaigns will be.

  Balancing bank customer segmentation with privacy and marketing regulations

  Of course, customer segmentation uses a lot of data, which raises important legal and ethical questions. First, you need to comply with data and privacy regulations, such as GDPR and CCPA. Second, you also have to consider the privacy expectations of your customers, who are increasingly aware of privacy issues and rising security threats targeting financial service providers.

  If you aim to retain and maximise customer value, respecting their privacy and protecting their data are non-negotiables.

  Regulators are clamping down on finance

  Regulatory scrutiny towards the finance industry is intensifying, largely driven by the rise of fintech and the growing threat of cyber attacks. Not only was 2023 a record-breaking year for finance security breaches but several compromises of major US providers “exposed shortcomings in the current supervisory framework and have put considerable public pressure on banking authorities to reevaluate their supervisory and examination programs” (Deloitte).

  Banks face some of the strictest consumer protections and marketing regulations, but the digital age creates new threats.

  In 2022, the Consumer Financial Protection Bureau (CFPB) warned that digital marketers must comply with finance consumer protections when targeting audiences. CFPB Director Rohit Chopra said : “When Big Tech firms use sophisticated behavioural targeting techniques to market financial products, they must adhere to federal consumer financial protection laws.”

  This couldn’t be more relevant to customer segmentation and the tools banks use to conduct it.

  Customer data in the hands of agencies and big tech

  Banks should pay attention to the words of CFPB Director Rohit Chopra when partnering with marketing agencies and choosing analytics tools. Digital marketing agencies are rarely experts in financial regulations, and tech giants like Google don’t have the best track record for adhering to them.

  Google is constantly in the EU courts over its data use. In 2022, the EU ruled that the previous version of Google Analytics violated EU privacy regulations. Google Analytics 4 was promptly released but didn’t resolve all the issues.

  Meanwhile, any company that inadvertently misuses Google Analytics is legally responsible for its compliance with data regulations.

  Banks need a privacy-centric alternative to Google Analytics

  Google’s track record with data regulation compliance is a big issue, but it’s not the only one. Google Analytics uses data sampling, which Google defines as the “practice of analysing a subset of data to uncover meaningful information from a larger data set.”

  This means Google Analytics places thresholds on how much of your data it analyses — anything after that is calculated assumptions. We’ve explained why this is such a problem before, and GA4 relies on data sampling even more than the previous version.

  In short, banks should question whether they can trust Google with their customer data and whether they can trust Google Analytics to provide accurate data in the first place. And they do. 80% of financial marketers say they’re concerned about ad tech bias from major providers like Google and Meta.

  

  Matomo is the privacy-centric alternative to Google Analytics, giving you 100% data ownership and compliant web analytics. With no data sampling, Matomo provides 20-40% more data to help you make accurate, informed decisions. Get the data you need for customer segmentation without putting their data at risk.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Bank customer segmentation examples

  Now, let’s look at some customer segments you create and layer to target specific customer groups.

  Visit-based segmentation

  Visit segmentation filters audiences based on the pages they visit on your website and the behaviors they exhibit—for example, first-time visitors vs. returning visitors or landing page visitors vs. blog page visitors.

  If you look at HSBC’s website, you’ll see it is structured into several categories for key customer personas. One of its segments is international customers living in the US, so it has pages and resources expats, people working in the US, people studying in the US, etc. 

  

  By combining visit-based segmentation with ultra-relevant pages for specific target audiences, HSBC can track each group’s demand and interest and analyse their behaviours. It can determine which audiences are returning, which products they want, and which messages convert them.

  Demographic segmentation

  Demographic segmentation divides customers by attributes such as age, gender, and location. However, you can also combine these insights with other non-personal data to better understand specific audiences.

  For example, in Matomo, you can segment audiences based on the language of their browser, the country they’re visiting from, and other characteristics. So, in this case, HSBC could differentiate between visitors already residing in the US and those outside of the country looking for information on moving there.

  

  It could determine which countries they’re visiting, which languages to localise for, and which networks to run ultra-relevant social campaigns on.

  Interaction-based segmentation

  Interaction-based segmentation uses events and goals to segment users based on their actions on your website. For example, you can segment audiences who visit specific URLs, such as a loan application page, or those who don’t complete an action, such as failing to complete a form.

  

  With events and goals set up, you can track the actions visitors complete before making purchases. You can monitor topical interests, page visits, content interactions, and pathways toward conversions, which feed into their customer journey.

  From here, you can segment customers based on their path leading up to their first purchase, follow-up purchases, and other actions.

  Purchase-based segmentation

  Purchase-based segmentation allows you to analyse the customer behaviours related to their purchase history and spending habits. For example, you can track the journey of repeat customers or identify first-time buyers showing interest in other products/services.

  You can implement these insights into your cross-selling and upselling campaigns with relevant messages designed to increase retention and customer lifetime value.

  Get reliable website analytics for your bank customer segmentation needs

  With customers switching in greater numbers, banks need to prioritise customer retention and lifetime value. Customer segmentation allows you to target specific customer groups and address their unique needs — the perfect strategy to stop them from moving to another provider.

  Quality, accurate data is the key ingredient of an effective bank customer segmentation strategy. Don’t accept data sampling from Google Analytics or any other tool that limits the amount of your own data you can access. Choose a web analytics tool like Matamo that unlocks the full potential of your website analytics to get the most out of bank customer segmentation.

  Matomo is trusted by over 1 million websites globally, including many banks, for its accuracy, compliance, and reliability. Discover why financial institutions rely on Matomo to meet their web analytics needs.

  Start collecting the insights you need for granular, layered segmentation — without putting your bank customer data at risk. Request a demo of Matomo now.

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• Révision 18876 : spip3beta dans archives

  3 janvier 2012, par Ben .

• Tracking User Acquisition and Social Media Activity with Piwik

  25 avril 2017, par Florian Hieß — Community

  Being able to monitor user acquisition and social media activity is essential for determining whether the outcome of your campaigns is in line with the business objectives. Determining the source of each website visit that gets you closer to your business goals enables you to focus your efforts in the directions that are worth it. In this article you will learn why it is important to identify your traffic sources and how you can track user acquisition with Piwik Analytics.

  Why Is It Important to Identify Traffic Sources on Your Website ?

  Since brands nowadays use multiple channels for promotion and advertising, identifying the touch points and traffic sources of a lead or customer seems to become more and more difficult. And yet, this channel multiplication is what makes the source of a purchase more important. Once you identify the traffic origin and how each source is performing you are able to increase your efforts on the best performers, both in terms of human resources and monetary investments, to attract more leads or customers in these marketing channels.

  The default referrer types are defined by :

  • Search engine
  • Direct traffic
  • Websites and
  • Campaigns

  But consider that within the “Campaigns” type, each of the following referrers is a possible traffic source for your website and can be tracked with the Piwik URL builder :

  • Google AdWords
  • Display Ads, Banners
  • Links in Newsletters, Emailing
  • Affiliate links
  • Tweets
  • Facebook Ads

  Measure your performance and conversion

  With so many options, wouldn’t you like to know which one of them worked best ? To rate channels based on their performance, you first need to establish conversion goals and attribution.

  A conversion can be anything from sign-ups or downloads to leads, registered users and even paying customers. Define conversions based on what you want people to do once they’ve landed on your website.

  

  You need to define each conversion type in the Piwik dashboard, so that the analytics platform knows what to track. As far as attribution goes, Piwik by default links the conversion and attributes to the last seen (non-direct) referrer. You are able to change that to the first referrer in the attribution line by following the instructions in this conversion attribution FAQ.

  Track Your User Acquisition Right with Piwik

  Using the Piwik URL Builder tool, you can tag each URL you promote in your campaigns using relevant keywords. Provided that your URLs are tagged, whenever someone clicks on them, the campaign will be listed as the referrer in the Piwik dashboard. Once you’ve generated trackable URLs, you can include them in your social media posts which could be planned and scheduled using a social media management tool such as Swat.io.

  

  Campaign URLs work wonders for telling which campaign helped you reach your goals faster, more efficiently and so on but they do have a downside. They only work for URLs that you’ve shared. If someone decides to share a link of yours on social media they won’t be tagged beforehands. This is where the Referrers section of Piwik comes in handy, as it acts as a backup for tracking traffic sources. The overview tab features a graph that can help you identify when spikes occurred.

  

  As well as a numerical representation of the main referrer categories for the selected time period.

  

  Switching from Overview to Websites & Social, you can see a graphical representation of the social networks acting as referrers. The visualization can be changed to bar graphs or table, and can be easily exported in various formats for reports.

  

  The websites list features not only the social referrers, but all of the websites generating visits to your website. With Piwik you should not have issues with referrer spam, as the Piwik core team has tackled this problem early on, as detailed in how to stop referrer spam. Our analytics spam blacklist is a public project on GitHub.

  

  Assuming that you’re relying only on Facebook and VK.com for your campaigns, as the above screenshot would suggest, you might want to give paid advertising a try on these two social networks. Paid ads can increase reach and engagement, can get more relevant visitors to your website and can have a snowball effect in a short period of time.

  What Social Networks Can Piwik Track ?

  Piwik’s built-in social network list is quite extensive, as it currently features 70 platforms. The entries range from popular social networks such as Facebook, Twitter and LinkedIn to more obscure ones such as Renren. However, this list is not available by default, and to see it or alter it, you would need a third-party plugin.

  How Does the Referrers Manager Plugin for Piwik Work ?

  The Referrers Manager plugin for Piwik provides access to the list of search engines and social networks that this analytics platform can handle by default. The simple plugin can come in handy when sorting out referrers. First of all, it displays a list of all search engines and social networks that Piwik can handle by default. Secondly, it enables users to disable/enable the platform’s default social network list. And using Referrers Manager, you can add custom engines or social networks to the referrers list in case they’re not already available.

  

  Conclusions

  Piwik is a very capable analytics platform as it is, but combined with third-party plugins such as Referrers Manager, it can provide even better insights on where your visitors are coming from. Remember to correlate the referrers with goals in order to determine which website or social network performs best in your context. And don’t forget to assign a monetary revenue value to each goal, in order to determine your social media ROI with greater accuracy.