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• Banking Data Strategies – A Primer to Zero-party, First-party, Second-party and Third-party data

  25 octobre 2024, par Daniel Crough — Banking and Financial Services, Privacy

  Banks hold some of our most sensitive information. Every transaction, loan application, and account balance tells a story about their customers’ lives. Under GDPR and banking regulations, protecting this information isn’t optional – it’s essential.

  Yet banks also need to understand how customers use their services to serve them better. The solution lies in understanding different types of banking data and how to handle each responsibly. From direct customer interactions to market research, each data source serves a specific purpose and requires its own privacy controls.

  Before diving into how banks can use each type of data effectively, let’s look into the key differences between them :

  Data Type	What It Is	Banking Example	Legal Considerations
  First-party	Data from direct customer interactions with your services	Transaction records, service usage patterns	Different legal bases apply (contract, legal obligation, legitimate interests)
  Zero-party	Information customers actively provide	Stated preferences, financial goals	Requires specific legal basis despite being voluntary ; may involve profiling
  Second-party	Data shared through formal partnerships	Insurance history from partners	Must comply with PSD2 and specific data sharing regulations
  Third-party	Data from external providers	Market analysis, demographic data	Requires due diligence on sources and specific transparency measures

  What is first-party data ?

  

  First-party data reveals how customers actually use your banking services. When someone logs into online banking, withdraws money from an ATM, or speaks with customer service, they create valuable information about real banking habits.

  This direct interaction data proves more reliable than assumptions or market research because it shows genuine customer behaviour. Banks need specific legal grounds to process this information. Basic banking services fall under contractual necessity, while fraud detection is required by law. Marketing activities need explicit customer consent. The key is being transparent with customers about what information you process and why.

  Start by collecting only what you need for each specific purpose. Store information securely and give customers clear control through privacy settings. This approach builds trust while helping meet privacy requirements under the GDPR’s data minimisation principle.

  What is zero-party data ?

  

  Zero-party data emerges when customers actively share information about their financial goals and preferences. Unlike first-party data, which comes from observing customer behaviour, zero-party data comes through direct communication. Customers might share their retirement plans, communication preferences, or feedback about services.

  Interactive tools create natural opportunities for this exchange. A retirement calculator helps customers plan their future while revealing their financial goals. Budget planners offer immediate value through personalised advice. When customers see clear benefits, they’re more likely to share their preferences.

  However, voluntary sharing doesn’t mean unrestricted use. The ICO’s guidance on purpose limitation applies even to freely shared information. Tell customers exactly how you’ll use their data, document specific reasons for collecting each piece of information, and make it simple to update or remove personal data.

  Regular reviews help ensure you still need the information customers have shared. This aligns with both GDPR requirements and customer expectations about data management. By treating voluntary information with the same care as other customer data, banks build lasting trust.

  What is second-party data ?

  

  Second-party data comes from formal partnerships between banks and trusted companies. For example, a bank might work with an insurance provider to better understand shared customers’ financial needs.

  These partnerships need careful planning to protect customer privacy. The ICO’s Data Sharing Code provides clear guidelines : both organisations must agree on what data they’ll share, how they’ll protect it, and how long they’ll keep it before any sharing begins.

  Transparency builds trust in these arrangements. Tell customers about planned data sharing before it happens. Explain what information you’ll share and how it helps provide better services.

  Regular audits help ensure both partners maintain high privacy standards. Review shared data regularly to confirm it’s still necessary and properly protected. Be ready to adjust or end partnerships if privacy standards slip. Remember that your responsibility to protect customer data extends to information shared with partners.

  Successful partnerships balance improved service with diligent privacy protection. When done right, they help banks understand customer needs better while maintaining the trust that makes banking relationships work.

  What is third-party data ?

  

  Third-party data comes from external sources outside your bank and its partners. Market research firms, data analytics companies, and economic research organizations gather and sell this information to help banks understand broader market trends.

  This data helps fill knowledge gaps about the wider financial landscape. For example, third-party data might reveal shifts in consumer spending patterns across different age groups or regions. It can show how customers interact with different financial services or highlight emerging banking preferences in specific demographics.

  But third-party data needs careful evaluation before use. Since your bank didn’t collect this information directly, you must verify both its quality and compliance with privacy laws. Start by checking how providers collected their data and whether they had proper consent. Look for providers who clearly document their data sources and collection methods.

  Quality varies significantly among third-party data providers. Some key questions to consider before purchasing :

  • How recent is the data ?
  • How was it collected ?
  • What privacy protections are in place ?
  • How often is it updated ?
  • Which specific market segments does it cover ?

  Consider whether third-party data will truly add value beyond your existing information. Many banks find they can gain similar insights by analysing their first-party data more effectively. If you do use third-party data, document your reasons for using it and be transparent about your data sources.

  Creating your banking data strategy

  

  A clear data strategy helps your bank collect and use information effectively while protecting customer privacy. This matters most with first-party data – the information that comes directly from your customers’ banking activities.

  Start by understanding what data you already have. Many banks collect valuable information through everyday transactions, website visits, and customer service interactions. Review these existing data sources before adding new ones. Often, you already have the insights you need – they just need better organization.

  Map each type of data to a specific purpose. For example, transaction data might help detect fraud and improve service recommendations. Website analytics could reveal which banking features customers use most. Each data point should serve a clear business purpose while respecting customer privacy.

  Strong data quality standards support better decisions. Create processes to update customer information regularly and remove outdated records. Check data accuracy often and maintain consistent formats across your systems. These practices help ensure your insights reflect reality.

  Remember that strategy means choosing what not to do. You don’t need to collect every piece of data possible. Focus on information that helps you serve customers better while maintaining their privacy.

  Managing multiple data sources

  

  Banks work with many types of data – from direct customer interactions to market research. Each source serves a specific purpose, but combining them effectively requires careful planning and precise attention to regulations like GDPR and ePrivacy.

  First-party data forms your foundation. It shows how your customers actually use your services and what they need from their bank. This direct interaction data proves most valuable because it reflects real behaviour rather than assumptions. When customers check their balances, transfer money, or apply for loans, they show you exactly how they use banking services.

  Zero-party data adds context to these interactions. When customers share their financial goals or preferences directly, they help you understand the “why” behind their actions. This insight helps shape better services. For example, knowing a customer plans to buy a house helps you offer relevant savings tools or mortgage information at the right time.

  Second-party partnerships can fill specific knowledge gaps. Working with trusted partners might reveal how customers manage their broader financial lives. But only pursue partnerships when they offer clear value to customers. Always explain these relationships clearly and protect shared information carefully.

  Third-party data helps provide market context, but use it selectively. External market research can highlight broader trends or opportunities. However, this data often proves less reliable than information from direct customer interactions. Consider it a supplement to, not a replacement for, your own customer insights.

  Keep these principles in mind when combining data sources :

  • Prioritize direct customer interactions
  • Focus on information that improves services
  • Maintain consistent privacy standards across sources
  • Document where each insight comes from
  • Review regularly whether each source adds value
  • Work with privacy and data experts to ensure customer information is handled properly

  Enhance your web analytics strategy with Matomo

  

  The financial sector finds powerful and compliant web analytics increasingly valuable as it navigates data management and privacy regulations. Matomo provides a configurable privacy-centric solution that meets the requirements of banks and financial institutions.

  Matomo empowers your organisation to :

  • Collect accurate, GDPR-compliant web data
  • Integrate web analytics with your existing tools and platforms
  • Maintain full control over your analytics data
  • Gain insights without compromising user privacy

  Matomo is trusted by some of the world’s biggest banks and financial institutions. Try Matomo for free for 30 days to see how privacy-focused analytics can get you the insights you need while maintaining compliance and user trust.

• What Is Data Misuse & How to Prevent It ? (With Examples)

  13 mai 2024, par Erin

  Your data is everywhere. Every time you sign up for an email list, log in to Facebook or download a free app onto your smartphone, your data is being taken.

  This can scare customers and users who fear their data will be misused.

  While data can be a powerful asset for your business, it’s important you manage it well, or you could be in over your head.

  In this guide, we break down what data misuse is, what the different types are, some examples of major data misuse and how you can prevent it so you can grow your brand sustainably.

  What is data misuse ?

  Data is a good thing.

  It helps analysts and marketers understand their customers better so they can serve them relevant information, products and services to improve their lives.

  But it can quickly become a bad thing for both the customers and business owners when it’s mishandled and misused.

  

  Data misuse is when a business uses data outside of the agreed-upon terms. When companies collect data, they need to legally communicate how that data is being used. 

  Who or what determines when data is being misused ?

  Several bodies :

  • User agreements
  • Data privacy laws
  • Corporate policies
  • Industry regulations

  There are certain laws and regulations around how you can collect and use data. Failure to comply with these guidelines and rules can result in several consequences, including legal action.

  Keep reading to discover the different types of data misuse and how to prevent it.

  3 types of data misuse

  There are a few different types of data misuse.

  If you fail to understand them, you could face penalties, legal trouble and a poor brand reputation.

  

  1. Commingling

  When you collect data, you need to ensure you’re using it for the right purpose. Commingling is when an organisation collects data from a specific audience for a specific reason but then uses the data for another purpose.

  One example of commingling is if a company shares sensitive customer data with another company. In many cases, sister companies will share data even if the terms of the data collection didn’t include that clause.

  Another example is if someone collects data for academic purposes like research but then uses the data later on for marketing purposes to drive business growth in a for-profit company.

  In either case, the company went wrong by not being clear on what the data would be used for. You must communicate with your audience exactly how the data will be used.

  2. Personal benefit

  The second common way data is misused in the workplace is through “personal benefit.” This is when someone with access to data abuses it for their own gain.

  The most common example of personal benefit data muse is when an employee misuses internal data.

  While this may sound like each instance of data misuse is caused by malicious intent, that’s not always the case. Data misuse can still exist even if an employee didn’t have any harmful intent behind their actions. 

  One of the most common examples is when an employee mistakenly moves data from a company device to personal devices for easier access.

  3. Ambiguity

  As mentioned above, when discussing commingling, a company must only use data how they say they will use it when they collect it.

  A company can misuse data when they’re unclear on how the data is used. Ambiguity is when a company fails to disclose how user data is being collected and used.

  This means communicating poorly on how the data will be used can be wrong and lead to misuse.

  One of the most common ways this happens is when a company doesn’t know how to use the data, so they can’t give a specific reason. However, this is still considered misuse, as companies need to disclose exactly how they will use the data they collect from their customers.

  Laws on data misuse you need to follow

  Data misuse can lead to poor reputations and penalties from big tech companies. For example, if you step outside social media platforms’ guidelines, you could be suspended, banned or shadowbanned.

  But what’s even more important is certain types of data misuse could mean you’re breaking laws worldwide. Here are some laws on data misuse you need to follow to avoid legal trouble :

  General Data Protection Regulation (GDPR)

  The GDPR, or General Data Protection Regulation, is a law within the European Union (EU) that went into effect in 2018.

  The GDPR was implemented to set a standard and improve data protection in Europe. It was also established to increase accountability and transparency for data breaches within businesses and organisations.

  The purpose of the GDPR is to protect residents within the European Union.

  The penalties for breaking GDPR laws are fines up to 20 million Euros or 4% of global revenues (whatever the higher amount is).

  The GDPR doesn’t just affect companies in Europe. You can break the GDPR’s laws regardless of where your organisation is located worldwide. As long as your company collects, processes or uses the personal data of any EU resident, you’re subject to the GDPR’s rules.

  If you want to track user data to grow your business, you need to ensure you’re following international data laws. Tools like Matomo—the world’s leading privacy-friendly web analytics solution—can help you achieve GDPR compliance and maintain it.

  With Matomo, you can confidently enhance your website’s performance, knowing that you’re adhering to data protection laws. 

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  California Consumer Privacy Act (CCPA)

  The California Consumer Privacy Act (CCPA) is another important data law companies worldwide must follow.

  Like GDPR, the CCPA is a data privacy law established to protect residents of a certain region — in this case, residents of California in the United States.

  The CCPA was implemented in 2020, and businesses worldwide can be penalised for breaking the regulations. For example, if you’re found violating the CCPA, you could be fined $7,500 for each intentional violation.

  If you have unintentional violations, you could still be fined, but at a lesser fee of $2,500.

  The Gramm-Leach-Bliley Act (GLBA)

  If your business is located within the United States, then you’re subject to a federal law implemented in 1999 called The Gramm-Leach-Bliley Act (GLB Act or GLBA).

  The GLBA is also known as the Financial Modernization Act of 1999. Its purpose is to control the way American financial institutions handle consumer data. 

  In the GLBA, there are three sections :

  1. The Financial Privacy Rule : regulates the collection and disclosure of private financial data.
  2. Safeguards Rule : Financial institutions must establish security programs to protect financial data.
  3. Pretexting Provisions : Prohibits accessing private data using false pretences.

  The GLBA also requires financial institutions in the U.S. to give their customers written privacy policy communications that explain their data-sharing practices.

  4 examples of data misuse in real life

  If you want to see what data misuse looks like in real life, look no further.

  Big tech is central to some of the biggest data misuses and scandals.

  

  Here are a few examples of data misuse in real life you should take note of to avoid a similar scenario :

  1. Facebook election interference

  One of history’s most famous examples of data misuse is the Facebook and Cambridge Analytica scandal in 2018.

  During the 2018 U.S. midterm elections, Cambridge Analytica, a political consulting firm, acquired personal data from Facebook users that was said to have been collected for academic research.

  Instead, Cambridge Analytica used data from roughly 87 million Facebook users. 

  This is a prime example of commingling.

  The result ? Cambridge Analytica was left bankrupt and dissolved, and Facebook was fined $5 billion by the Federal Trade Commission (FTC).

  2. Uber “God View” tracking

  Another big tech company, Uber, was caught misusing data a decade ago. 

  Why ?

  Uber implemented a new feature for its employees in 2014 called “God View.”

  The tool enabled Uber employees to track riders using their app. The problem was that they were watching them without the users’ permission. “God View” lets Uber spy on their riders to see their movements and locations.

  The FTC ended up slapping them with a major lawsuit, and as part of their settlement agreement, Uber agreed to have an outside firm audit their privacy practices between 2014 and 2034.

  

  3. Twitter targeted ads overstep

  In 2019, Twitter was found guilty of allowing advertisers to access its users’ personal data to improve advertisement targeting.

  Advertisers were given access to user email addresses and phone numbers without explicit permission from the users. The result was that Twitter ad buyers could use this contact information to cross-reference with Twitter’s data to serve ads to them.

  Twitter stated that the data leak was an internal error. 

  4. Google location tracking

  In 2020, Google was found guilty of not explicitly disclosing how it’s using its users’ personal data, which is an example of ambiguity.

  The result ?

  The French data protection authority fined Google $57 million.

  8 ways to prevent data misuse in your company

  Now that you know the dangers of data misuse and its associated penalties, it’s time to understand how you can prevent it in your company.

  

  Here are eight ways you can prevent data misuse :

  1. Track data with an ethical web analytics solution

  You can’t get by in today’s business world without tracking data. The question is whether you’re tracking it safely or not.

  If you want to ensure you aren’t getting into legal trouble with data misuse, then you need to use an ethical web analytics solution like Matomo.

  With it, you can track and improve your website performance while remaining GDPR-compliant and respecting user privacy. Unlike other web analytics solutions that monetise your data and auction it off to advertisers, with Matomo, you own your data.

  Try Matomo for Free

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

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  2. Don’t share data with big tech

  As the data misuse examples above show, big tech companies often violate data privacy laws.

  And while most of these companies, like Google, appear to be convenient, they’re often inconvenient (and much worse), especially regarding data leaks, privacy breaches and the sale of your data to advertisers.

  Have you ever heard the phrase : “You are the product ?” When it comes to big tech, chances are if you’re getting it for free, you (and your data) are the products they’re selling.

  The best way to stop sharing data with big tech is to stop using platforms like Google. For more ideas on different Google product alternatives, check out this list of Google alternatives.

  3. Identity verification 

  Data misuse typically isn’t a company-wide ploy. Often, it’s the lack of security structure and systems within your company. 

  An important place to start is to ensure proper identity verification for anyone with access to your data.

  4. Access management

  After establishing identity verification, you should ensure you have proper access management set up. For example, you should only give specific access to specific roles in your company to prevent data misuse.

  5. Activity logs and monitoring

  One way to track data misuse or breaches is by setting up activity logs to ensure you can see who is accessing certain types of data and when they’re accessing it.

  You should ensure you have a team dedicated to continuously monitoring these logs to catch anything quickly.

  6. Behaviour alerts 

  While manually monitoring data is important, it’s also good to set up automatic alerts if there is unusual activity around your data centres. You should set up behaviour alerts and notifications in case threats or compromising events occur.

  7. Onboarding, training, education

  One way to ensure quality data management is to keep your employees up to speed on data security. You should ensure data security is a part of your employee onboarding. Also, you should have regular training and education to keep people informed on protecting company and customer data.

  8. Create data protocols and processes 

  To ensure long-term data security, you should establish data protocols and processes. 

  To protect your user data, set up rules and systems within your organisation that people can reference and follow continuously to prevent data misuse.

  Leverage data ethically with Matomo

  Data is everything in business.

  But it’s not something to be taken lightly. Mishandling user data can break customer trust, lead to penalties from organisations and even create legal trouble and massive fines.

  You should only use privacy-first tools to ensure you’re handling data responsibly.

  Matomo is a privacy-friendly web analytics tool that collects, stores and tracks data across your website without breaking privacy laws.

  With over 1 million websites using Matomo, you can track and improve website performance with :

  • Accurate data (no data sampling)
  • Privacy-friendly and compliant with privacy regulations like GDPR, CCPA and more
  • Advanced features like heatmaps, session recordings, A/B testing and more

  Try Matomo free for 21-days. No credit card required.

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• Marketing Touchpoints : Examples, KPIs, and Best Practices

  11 mars 2024, par Erin

  The customer journey is rarely straightforward. Rather, each stage comprises numerous points of contact with your brand, known as marketing touchpoints. And each touchpoint is equally important to the customer experience. 

  This article will explore marketing touchpoints in detail, including how to analyse them with attribution models and which KPIs to track. It will also share tips on incorporating these touchpoints into your marketing strategy. 

  What are marketing touchpoints ? 

  Marketing touchpoints are the interactions that take place between brands and customers throughout the latter’s journey, either online or in person. 

  

  By understanding how customers interact with your brand before, during and after a purchase, you can identify the channels that contribute to starting, driving and closing buyer journeys. Not only that, but you’ll also learn how to optimise the customer experience. This can also help you : 

  • Promote customer loyalty through increased customer satisfaction
  • Improve your brand reputation and foster a more positive perception of your brand, supported by social proof 
  • Build brand awareness among prospective customers 
  • Reconnect with current customers to drive repeat business

  According to a 2023 survey, social media and video-sharing platforms are the leading digital touchpoints among US consumers.

  

  With the customer journey divided into three stages — awareness, consideration, and decision — we can group these interactions into three touchpoint segments, depending on whether they occur before, during or after a purchase. 

  Touchpoints before a purchase

  Touchpoints before a purchase are those initial interactions between potential customers and brands that occur during the awareness stage — before they’ve made a purchase decision. 

  Here are some key touchpoints at the pre-purchase stage : 

  • Customer reviews, forums, and testimonials 
  • Social media posts
  • Online ads 
  • Company events and product demos
  • Other digital touchpoints, like video content, blog posts, or infographics
  • Peer referral 

  In PwC’s 2024 Global Consumer Insights Pulse Survey, 54% of consumers listed search engines as their primary source of pre-purchase information, followed by Amazon (35%) and retailer websites (33%). 

  Here are the survey’s findings in Western Europe, specifically : 

  

  Social channels are another major pre-purchase touchpoint ; 25% of social media users aged 18 to 44 have made a purchase through a social media app over the past three months. 

  Touchpoints during a purchase

  Touchpoints during a purchase occur when the prospective customer has made their purchase decision. It’s the beginning of a (hopefully) lasting relationship with them. 

  It’s important to involve both marketing and sales teams here — and to keep track of conversion metrics. 

  Here are the main touchpoints at this stage : 

  • Company website pages 
  • Product pages and catalogues 
  • Communication between customers and sales reps 
  • Product packaging and labelling 
  • Point-of-sale (POS) — the final touchpoint the prospective customer will reach before making the final purchasing decision 

  Touchpoints after a purchase

  You can use touchpoints after a purchase to maintain a positive relationship and keep current customers engaged. Examples of touchpoints that contribute to a good post-purchase experience for the customer include the following : 

  • Thank-you emails 
  • Email newsletters 
  • Customer satisfaction surveys 
  • Cross-selling emails 
  • Renewal options 
  • Customer loyalty programs

  Email marketing remains significant across all touchpoint segments, with 44% of CMOs agreeing that it’s essential to their marketing strategy — and it also plays a particularly important role in the post-purchase experience. For 61.1% of marketing teams, email open rates are higher than 20%.

  

  Sixty-nine percent of consumers say they’ve stopped doing business with a brand following a bad experience, so the importance of customer service touchpoints shouldn’t be overlooked. Live chat, chatbots, self-service resources, and customer service teams are integral to the post-purchase experience.

  Attribution models : Assigning value to marketing touchpoints 

  Determining the most effective touchpoints — those that directly contribute to conversions — is a process known as marketing attribution. The goal here is to identify the specific channels and points of contact with prospective customers that result in revenue for the company.

  

  You can use these insights to understand — and maximise — marketing return on investment (ROI). Otherwise, you risk allocating your budget to the wrong channels. 

  It’s possible to group attribution models into two categories — single-touch and multi-touch — depending on whether you assign value to one or more contributing touchpoints.

  Single-touch attribution models, where you’re giving credit for the conversion to a single touchpoint, include the following :

  • First-touch attribution : This assigns credit for the conversion to the first interaction a customer had with a brand ; however, it fails to consider lower-funnel touchpoints.
  • Last-click attribution : This focuses only on bottom-of-funnel marketing and credits the last interaction the customer had with a brand before completing a purchase.
  • Last non-direct : Credits the touchpoint immediately preceding a direct touchpoint with all the credit.

  Multi-touch attribution models are more complex and distribute the credit for conversion across multiple relevant touchpoints throughout the customer journey :

  • Linear attribution : The simplest multi-touch attribution model assigns equal values to all contributing touchpoints.
  • Position-based or U-shaped attribution : This assigns the greatest value to the first and last touchpoint — with 40% of the conversion credit each — and then divides the remaining 20% across all the other touchpoints.
  • Time-decay attribution : This model assigns the most credit to the customer’s most recent interactions with a brand, assuming that the touchpoints that occur later in the journey have a bigger impact on the conversion.

  Consider the following when choosing the most appropriate attribution model for your business :

  • The length of your typical sales cycle
  • Your marketing goals : increasing awareness, lead generation, driving revenue, etc.
  • How many stages and touchpoints make up your sales funnel

  Sometimes, it even makes sense to measure marketing performance using more than one attribution model.

  With the sheer volume of data that’s constantly generated across numerous online touchpoints, from your website to social media channels, it’s practically impossible to collect and analyse it manually.

  You’ll need an advanced web analytics platform to identify key touchpoints and assign value to them.

  Matomo’s Marketing Attribution feature can accurately measure the performance of different touchpoints to ensure that you’re allocating resources to the right channels. This is done in a compliant manner, without the need of data sampling or requiring cookie consent screens (excluding in Germany and the UK), ensuring both accuracy and privacy compliance.

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  Customer journey KPIs for measuring marketing campaign performance 

  Measuring the impact of different touchpoints on marketing campaign performance can help you understand how customer interactions drive conversions — and how to optimise your future efforts. 

  

  Clearly, this is not a one-time effort. You should continuously reevaluate the crucial touchpoints that drive the most engagement at different stages of the customer journey. 

  Web analytics platforms can provide valuable insights into ever-changing consumer behaviours and trends and help you make informed decisions. 

  At the moment, Google is the most popular solution in the web analytics industry, with a combined market share of more than 70%. 

  However, if privacy, data accuracy, and GDPR compliance are a priority for you, Matomo is an alternative worth considering. 

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  KPIs to track before a purchase 

  During the pre-purchase stage, focus on the KPIs that measure the effectiveness of marketing activities across various online touchpoints — landing pages, email campaigns, social channels and ad placement on SERPs, for instance. 

  KPIs to track during the consideration stage include the following : 

  • Cost-per-click (CPC) : The CPC, the total cost of paid online advertising divided by the number of clicks those ads get, indicates whether you’re getting a good ROI. In the UK, the average CPC for search advertising is $1.22. Globally, it averages $0.62.
  • Engagement rate : The engagement rate, which is the total number of interactions divided by the number of followers, is useful for measuring the performance of social media touchpoints. Customer engagement also applies to other channels, like tracking average time on-page, form conversions, bounce rates, and other website interactions. 
  • Click-through rate (CTR) : The CTR — or the number of clicks your ads receive compared to the number of times they’re shown — helps you measure the performance of CTAs, email newsletters and pay-per-click (PPC) advertising.

  KPIs to track during a purchase 

  As a potential customer moves further down the sales funnel and reaches the decision stage, where they’re ready to make the choice to purchase, you should be tracking the following : 

  • Conversion rate : This is the percentage of leads that convert into customers by completing the desired action relative to the total number of website visitors. It shows you whether you’re targeting the right people and providing a frictionless checkout experience.
  • Sales revenue : This refers to the quantity of products sold multiplied by the product’s price. It helps you track the company’s ability to generate profit. 
  • Cost per conversion : This KPI is the total cost of online advertising in relation to the number of conversions. It measures the effectiveness of different marketing channels and the costs of converting prospective customers into buyers. It also forecasts future ad spend.

  KPIs to track after purchase 

  At the post-purchase stage, your priority should be gathering feedback : 

  Customer feedback surveys are great for collecting insights into customers’ post-purchase experience, opinions about your brand, products and services, and needs and expectations. 

  In addition to measuring customer satisfaction, these insights can help you identify points of friction, forecast future growth and revenue and spot customers at risk of churning. 

  Focus on the following customer satisfaction and retention metrics : 

  • Customer Satisfaction Score (CSAT) : This metric, which is gathered through customer satisfaction surveys, helps you gauge satisfaction levels. After all, 77% of consumers consider great customer service an important driver of brand loyalty.
  • Net Promoter Score (NPS) : Based on single-question customer surveys, NPS indicates how likely a customer is to recommend your business.
  • Customer Lifetime Value (CLV) : The CLV is the profit you can expect to generate from one customer throughout their relationship with your company. 
  • Customer Health Score (CHS) : This score can assess how “healthy” the customer’s relationship with your brand is and identify at-risk customers.

  Marketing touchpoints : Tips and best practices 

  Customer experience is more important today than ever. 

  

  Salesforce’s 2022 State of the Connected Consumer report indicated that, for 88% of customers, the experience the brand provides is just as important as the product itself. 

  Here’s how you can build your customer touchpoint strategy and use effective touchpoints to improve customer satisfaction, build a loyal customer base, deliver better digital experiences and drive growth : 

  Understand the customer’s end-to-end experience 

  The typical customer’s journey follows a non-linear path of individual experiences that shape their awareness and brand preference. 

  Seventy-three percent of customers expect brands to understand their needs. So, personalising each interaction and delivering targeted content at different touchpoint segments — supported by customer segmentation and tools like Matomo — should be a priority. 

  Try to put yourself in the prospective customer’s shoes and understand their motivation and needs, focusing on their end-to-end experience rather than individual interactions. 

  Create a customer journey map 

  Once you understand how prospective customers interact with your brand, it becomes easier to map their journey from the pre-purchase stage to the actual purchase and beyond. 

  By creating these visual “roadmaps,” you make sure that you’re delivering the right content on the right channels at the right times and to the right audience — the key to successful marketing.

  Identify best-performing digital touchpoints 

  You can use insights from marketing attribution to pinpoint areas that are performing well. 

  By analysing the data provided by Matomo’s Marketing Attribution feature, you can determine which digital touchpoints are driving the most conversions or engagement, allowing you to focus your resources on optimising these channels for even greater success. 

  This targeted approach helps maximise the effectiveness of your marketing efforts and ensures a higher return on investment.

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  Discover key marketing touchpoints with Matomo 

  The customer’s journey rarely follows a direct route. If you hope to reach more customers and improve their experience, you’ll need to identify and manage individual marketing touchpoints every step of the way.

  While this process looks different for every business, it’s important to remember that your customers’ experience begins long before they interact with your brand for the first time — and carries on long after they complete the purchase. 

  In order to find these touchpoints and measure their effectiveness across multiple marketing channels, you’ll have to rely on accurate data — and a powerful web analytics tool like Matomo can provide those valuable marketing insights. 

  Try Matomo free for 21-days. No credit card required.

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