Web analytics data in financial services: 15 best practice tips

Web analytics data in financial services
Web analytics in the finance sector helps improve application rates, reduce call-centre costs, improve retention, and enable retargeting. This how-to guide will teach you how to support your team towards profits. Tips will include how to resolve seven common tracking challenges in banking and how to systemically deal with small problems before they become future emergencies with eight key strategies.
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The finance sector is known for being both traditional and innovative. The traditional part comes from being long-established, underlied with strict regulation and often built on systems that originated years or even decades ago. On the other hand, big investments and great industry thinkers also made it an innovative sector, constantly trying to attract both banking new-comers and established savers and loan-takers.

When looking for the latest strategies for improving the bottom-line, digital technologies offer many opportunities. The company website is often the first point of interaction, the place where banking customers buy products and services and also manage their accounts and transactions.

As customers’ expectations for digital experiences grow, the finance sector needs to keep up. According to a recent Salesforce Research report, after analysing 8000 consumers and business buyers, they found that “the customer experience stakes have never been higher,” with 84% of customers equating the importance of the experience a company provides with its products and services.

To implement these innovations, web analytics is the important first step. With so much data, it’s not easy to get it right. In my career, I’ve worked with brands like Ocean Finance – a popular UK loans provider, and Assurant – a Fortune 500 insurance provider for the banking sector. I audited their data, developed new systems for collecting richer insights and visualised stats to allow for taking action that results in higher online revenues and reduced call-centre costs. Having helped companies in the finance sector, I know first hand the techniques and steps to get more value from data and power your innovation successfully. 

In my work, I specialise in using the Google suite of products to report on what users do on a website and how it affects business goals. But you can use the tips in this post even if you’re based on another technology stack.

Web analytics in banking

In this post I share 15 tips to get started with web analytics in the finance sector and get it right the first time. Keep reading to find out the seven common finance sector tracking challenges (and how to overcome them) and eight strategies you can implement to ensure your data quality stays first-rate.

But first, a little more about what to do with web analytics data once you’ve got your set up right.

Combine web analytics data with other data sources and grow towards using Big Data in finance

According to Statista, the business analytics and Big Data market was valued at 168.8 billion dollars in 2018. By 2022, it’s expected to grow to 274.3 billion dollars. Data’s ability to inform currency decisions and make economic forecasts signal even more growth. 

Many in the finance sector are already reaping the rewards of using algorithmic patterns and forecasting with their existing user data. Linking that data to your users’ online behaviour provides a new dimension.

With data warehousing tools like BigQuery you can build relationships between website data, marketing, social media, advertising and your CRM data – all in one place. Combining it all together can teach you new things about your customers and highlight new opportunities for growth.

This information gives you a full picture of client behaviour and can be used for:

  • Marketing collateral – Being aware of the different types of financial needs your users have will help your team use the right messaging in blog posts, landing pages, eBooks, case studies, email campaigns, and social media content. 
  • Business strategies – It’s easier to set business objectives when you have clearly defined target groups. Set clear vision goals that align with user journeys and measure everything in the process.
  • Predictive analytics –  Get better at forecasting which user segments are likely to opt for which products or what application decisions they’re likely to get. For example, if most young adults in London choose a specific insurance policy, you can use this information to recommend a specific plan to similar visitors and make their decision easier.
  • Targeted ads – Combining multiple data sources gives you powerful insight into user behaviour. Create targeted ads that address their specific pain points or desires.

Behavioural insights serve to add that personal touch that clients increasingly crave, whether online or offline. This will set you apart from the competition.

It’s still common that website decisions are based on the opinion of a senior executive. This happens easily when finding an answer to a question takes a team hours if not days to sift through gigabytes of disorganised data.

If you think that your team might need help developing and implementing a measurement plan that is customised for the finance industry – get in touch to book a demo. I’ll show you how I did it for past clients and how you can apply it in your own business.

Even with strict compliance procedures, you can collect rich user data like employment status, income ranges, etc. – with your users’ permission. Combine it with behaviour data on which options were clicked or what journey drop-offs were, as well as with account usage stats – and you can start building powerful user segments that you can target and retarget with messaging that resonates.

How to resolve common tracking challenges in banking

“Let’s dig into the data.” How many times have you heard one of your team say this, then learned there was nothing worth “digging into,” no actionable recommendations? 

There are some unique challenges in tracking banking and financial services websites and apps.

The first set of tips highlights these common challenges and how to resolve them.

1. Beware of combining multiple technologies in web apps that can cause disjointed user journeys in your web analytics

Visitors to banking websites often interact with various services on a single website. These pages don’t exchange information with each other by default.

Data analytics for banking

This presents a problem for web analytics and it results in losing key parts of user journeys. Even if the data is collected – but with separate systems, you often need some extra configuration to join it all together.

Often, this happens with third-party domains (PayPal, Stripe or a bespoke iframe that links to your CRM) and regional websites (loans.co.uk vs loans.com). These technologies aren’t integrated natively, and they need to be set up by a web analytics implementation specialist.

Once the connections are implemented, if customers browse your website and interact with different technologies within it, you can still see which are the main drop-off points on your website and you can confidently tell what parts need to be improved or fixed.

2. Don’t lose data when trying to improve user experience

People interact with websites and apps in dynamic ways and the technologies used are not always causing pages to refresh or reload. This dynamic content is not tracked as standard by web analytics tools like Google Analytics. Examples of such functionality in the banking sector are individual steps in an application process or seeing recent transactions update when managing your account online.

Relying on out-of-the-box web analytics implementations can result in data losses. Ensure there is a web analyst on your team that can track important progress steps or screen changes to get the full picture of what your users are doing. This will enable you to make strategic business decisions including new investments in marketing and web development.

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3. In banking, tracking user journeys in detail can get complicated 

You might be seeing a trend in these tips already – and it’s all reflective of the banking industry. User journeys are often longer than on other websites and you are likely to collect much more personal information along the way to make sure you can assess loan applications correctly, verify users’ identity or display account information.

On top of ensuring that you capture the individual steps of user journeys and you’re able to combine them together, you want to capture all the clicks, swipes and toggles that form users’ micro-conversions and provide even more valuable information. These details can later be used to identify and activate high-value segments and save call-centre costs by improving your self-serve functionality. 

4. Don’t let slow pages push potential customers away

Visitors have no time to waste. According to 2018 research by Google, as page load time goes from one second to 10, chances of a mobile user leaving the site increase by 123%.

In the finance sector, the same functionalities and technologies already talked about in the previous points can result in longer page loads. 

A web analyst can help identify slow page loads and friction points, so you don’t lose another impatient potential client. 

5. Avoid customer dissatisfaction by tracking common errors

Being aware of when websites break is of particular importance in banking. Web analytics in banking can point to website errors, such as 404 error pages or form validation errors, and their root causes.

For example, high abandonment rates on the deep end of the transaction process (when users are highly invested in the process) could suggest a broken website. Error tracking can avoid customer dissatisfaction.

As a bonus, error tracking can be linked to alerts so you can quickly spot breakages and security breaches in near-real time.

6. Track client behaviour while maintaining a secure and trustworthy site

Financial institutions must be up to date with the latest cybersecurity and privacy laws, including being GDPR-compliant. Maintaining high-security standards is crucial, especially when bank account details, clients’ addresses, passwords, and other personally identifiable information (PII) are in play. 

Ensure website security when tracking

Default web analytics installations may unwittingly collect user data. You need a specialist web analytics installation to ensure that PII data is excluded from tracking. At the same time, an implementation specialist can use your existing customer ID numbers generated by your CRM to relate web analytics data to customers safely and as needed.

Similarly, Cookie consent (cookies are small text files that store user data, created when a User lands on your site) should be implemented correctly. In the UK, GDPR states that companies need valid consent before setting analytics, performance and targeting cookies.

Web analysts can examine data without storing it or breaching privacy. Ensuring this information is not collected is vital not only for legal reasons but also for giving clients peace of mind and for developing trust. 

7. Find relationships between marketing, web analytics and account data

Siloed data is a key barrier against drawing actionable insights. If your teams are not working with one another and your reports are limited to just a portion of the user journey, you’re missing out on key user data.

Connecting data can help you make more cost-effective marketing budgets decisions, more impactful product development improvements and correct market targeting conclusions.

How to maintain accurate and actionable data collection

Having reliable systems and workflows in place minimises the challenges of financial services in web analytics. Efficient processes support business goals while minimising human error and improving employees’ productivity. 

Here’s more tips that will help you establish activities to systemically deal with small problems before they inflate into emergencies. 

8. Create a robust tracking and measurement roadmap

Lizzy Foo Kune, Senior Director Analyst and author of a recent Gartner marketing report, explains that often analysts come up with graphs and charts that aren’t really useful to anyone:

“They wind up with mile-long Excel spreadsheets that are also layers deep that they hand over to stakeholders once a month. It has all of the data that you could possibly ever need. Everybody feels good about it – I call it a ‘security blanket.’ Everyone files it away, until they need to feel comfortable again.”

Wrapped in “security blankets,” the firm remains safe within its colour-coded, data-filled bubble. But ill-considered graphs don’t advance the business.

For the data to be valuable and actionable, companies need to design robust tracking and measurement roadmaps. This can involve:

  1. defining key metrics and events
  2. developing a tracking plan
  3. planning out ongoing A/B testing 
  4. customising a testing prioritisation framework to fit business requirements 

So what does this mean in practice?

When I work with a new client on their data strategy, I always start with building an understanding of all the possible user data flows: on- and off- website. I listen to what the goals of the business are, suggest the metrics and the KPIs that we can track to align with these business goals. I consider both web analytics data as well as other data: from marketing channels and from the CRM.

With all this, you can plan what needs to be tracked and how often: the smaller the interactions, the more often you should check them. For more strategic metrics, like lifetime value, you can report over longer periods of time.

Finally, I check what the future plans are for the business and prepare a tracking plan to support that.

When developing your measurement plan, bear these steps in mind so that you are confident about getting useful insights from your reports.

Web analytics tracking roadmap

9. Avoid development decisions that cause web analytics issues by involving your web analytics team early on

Getting analysts and developers to work together will save you a lot of headaches. For example, in Agile, refinement and planning meetings are imperative parts of the application production process. I suggest including a web analyst in some of those sessions. 

This warrants that data will be collected correctly and not lost as new upgrades and developments roll on. If you have good documentation and communication practices in place, you’ll know exactly which meetings will be most useful for your web analyst to attend.

Web analytics shouldn’t define your development process though. When developing data maintenance programmes for clients, I learn what processes they already follow to see how web analytics can become of them, rather than insist on a particular methodology.

avoid web analytics issues in finance websites

10. Involve your compliance team and explain how privacy is ensured by design 

Legal compliance in the banking sector is an important function: from risk assessment to fraud prevention and management. Data reaches can be costly so finance companies often veer on the side of caution.

Understandably, compliance teams are wary of data collection on websites. There’s been a fair amount of negative press around data collection and tracking in general – mostly caused by extensive remarketing practices that most online users have experienced.

The truth is, there’s no point fighting compliance – instead, it’s better to form a united front as both web analysts and compliance teams want to ensure a delightful and safe experience for customers.

It’s good to have conversations about new tracking requirements early on in the process. Analysts can make it easier by avoiding jargon and displaying the privacy-by-design principles in their work.

Providing regular internal analytics catch-ups and workshops for your compliance team guarantees everyone’s on the same page and that potential digital skills gaps are addressed upfront.

The last thing you want, is for your new digital solution to be blocked by compliance with no way out. It’s good when your web analysts can demonstrate how their work supports compliance instead of looking for ways around it.

11. Simplify onboarding and drive better insights by keeping track of changes

What gets measured gets done. When web analytics changes are stored efficiently, drawing value from data becomes easier, faster, and more reliable.

Most of your existing team might be aware of the changes that happen in your web application – but if you don’t log which changes happened when exactly, it’s difficult to gain useful insight from reports. Did changing the order of the form questions increase conversions? You may never know if you’ve not kept track of what happened.

Similarly, if you have new team members joining, it will be invaluable for them to show exactly what you’ve been working on and how it affected your performance. They can get started much more quickly, stop wasting other people’s time asking questions and start contributing to future results without delay.

Documenting naming conventions, the configuration of different events and goals and other features unique to your business will also help all your team work together better.

I feel strongly about processes, frameworks and documentation and ensure every project is supported with a guide that the team can reference. You should strive to do that too.

12. Prioritise web analytics requests and invest in robust frameworks

Collecting information is one thing – coming up with insights is another. But once you have a bunch of actionable findings, how do you know what to do next?

Implementing multiple changes at once will not allow you to test the impact of each change – and you won’t be able to measure whether it was actually beneficial. You need to make time to A/B test different hypotheses – and prioritising your top opportunities is a skill in itself.

Having worked on a number of optimisation programmes, I’ve refined my framework for prioritising opportunities – based on this one from Peep Laja at CXL. For each client I update it further, reflecting their unique set up.

In financial services web analytics, using a framework for prioritising opportunities and requests will help surface top activities to focus on.

Data analytics in financial services

13. Perform data and compliance audits regularly

Audits have a good rep, and with good reason. I’m a huge fan of testing and not relying on gut feelings alone when making business decisions. That’s why I recommend performing data and compliance audits regularly, at least quarterly. 

The things you should ensure when performing an audit should be:

  • All your pages and key interactions are tracked,
  • Your goals are working as expected,
  • Your ecommerce data is no more than 5% off from the actual numbers,
  • You’re not capturing any personally identifiable information,
  • You are attributing traffic and sales to well-defined marketing channels.

To spot tracking inaccuracies quickly in-between audits, you can also set up alerts to make you aware of major fluctuations.

Having someone perform quarterly audits ensures you’re up to date with the best data analytics practices and compliance laws.

14. Boost the positive influence of data by sharing it

Promote knowledge-sharing across various functions, departments, and branches by sharing your data and insights.

Sales and marketing are the obvious receivers of your data reports – but consider your wider internal audiences to keep them inspired and included. They may also be able to offer extra insight you might not have looked at.

Teams appreciate knowing the big picture you’re aiming towards as a business and what you’re doing to get there. Sharing your digital performance reports may offer extra motivation and help your teams appreciate each other more.

15. Use analytics data in leadership decision-making 

Finally, there’s no better way to encourage your wider business to be data-driven in their decision making, than to do it yourself. Having good quality data should give you the confidence to no longer rely on opinions. Ensure you follow through with this and show how you use data to justify your business decisions.

This top-down approach in terms of evangelising data usage will help others get on board. Show how you’re doing it and support your staff by providing them with the tools and coaching they need to put insights into action.

I feel this is such an important step towards ensuring that your business becomes data-driven not only on paper. That’s why I never deliver a project without a detailed run-through call and a recipe for how to put data into practice.

The future of financial services

The future of web analytics data in financial services 

Fast-changing customer needs are top of mind for many managers and directors of the banking sector. To make the right business forecasts, robust data and timely information are crucial.

Across the UK and the globe, web analytics and Big Data are transforming the financial industry. Web analytics support data-driven decisions and provide new profit-driving opportunities, like investing in new markets or funding challenger projects.

Digital banking transformation is a priority for 2021 for 75% of businesses. The value of web data analytics in banking and financial services is becoming widely appreciated. However, just like buildings need strong foundations, companies need a strong understanding of banking analytics to derive valuable and actionable insights.

For financial institutions and banks, limiting bias and increasing data-driven decisions are important aspects of establishing a fair process, whether for taking out a car loan or opening a savings account. 

Has your team started tracking key events and prioritising optimisation opportunities? If you were inspired by the ideas in this post and would like to know more about how I set up measurement programmes in the financial industry before, book your free demo session with me today.

Do you have any extra tips for implementing web analytics in the finance industry? Please share in the comment section below.

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