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• 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. 

  Try Matomo for Free

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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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• What Is Incrementality & Why Is It Important in Marketing ?

  26 mars 2024, par Erin

  Imagine this : you just launched your latest campaign and it was a major success.

  You blew last month’s results out of the water.

  You combined a variety of tactics, channels and ad creatives to make it work.

  Now, it’s time to build the next campaign.

  The only issue ?

  You don’t know what made it successful or how much your recent efforts impacted the results.

  You’ve been building your brand for years. You’ve built up a variety of marketing pillars that are working for you. So, how do you know how much of your campaign is from years of effort or a new tactic you just implemented ?

  The key is incrementality.

  This is a way to properly attribute the right weight to your marketing tactics.

  In this article, we break down what incrementality is in marketing, how it differs from traditional attribution and how you can calculate and track it to grow your business.

  What is incrementality in marketing ?

  Incrementality in marketing is growth that can be directly credited to a marketing effort above and beyond the success of the branding.

  It looks at how much a specific tactic positively impacted a campaign on top of overall branding and marketing strategies.

  

  For example, this could be how much a specific tactic, campaign or channel helped increase conversions, email sign-ups or organic traffic.

  The primary purpose of incrementally in marketing is to more accurately determine the impact a single marketing variable had on the success of a project.

  It removes every other factor and isolates the specific method to help marketers double down on that strategy or move on to new tactics.

  With Matomo, you can track conversions simply. With our last non-direct channel attribution system, you’ll be able to quickly see what channels are converting (and which aren’t) so you can gain insights into incrementality. 

  See why over 1 million websites choose Matomo today.

  Try Matomo for Free

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

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  How incrementality differs from attribution

  In marketing and advertising, it’s crucial to understand what tactics and activities drive growth.

  Incrementality and attribution help marketers and business owners understand what efforts impact their results.

  But they’re not the same.

  Here’s how they differ :

  

  Incrementality explained

  Incrementality measures how much a specific marketing campaign or activity drives additional sales or growth.

  Simply put, it’s analysing the difference between having never implemented the campaign (or tactic or channel) in the first place versus the impact of the activity.

  In other words, how much revenue would you have generated this month without campaign A ?

  And how much additional revenue did you generate directly due to campaign A ?

  The reality is that dozens of factors impact revenue and growth.

  You aren’t just pouring your marketing into one specific channel or campaign at a time.

  Chances are, you’ve got your hands on several marketing initiatives like SEO, PPC, organic social media, paid search, email marketing and more.

  Beyond that, you’ve built a brand with a not-so-tangible impact on your recurring revenue.

  So, the question is, if you took away your new campaign, would you still be generating the same amount of revenue ?

  And, if you add in that campaign, how much additional revenue and growth did it directly create ?

  That is incrementality. It’s how much a campaign went above and beyond to add new revenue that wouldn’t have been there otherwise.

  So, how does attribution play into all of this ?

  Attribution explained

  Attribution is simply the process of assigning credit for a conversion to a particular marketing touchpoint.

  While incrementality is about narrowing down the overall revenue impact from a particular campaign, attribution seeks to point to a specific channel to attribute a sale.

  For example, in any given marketing campaign, you have a few marketing tactics.

  Let’s say you’re launching a limited-time product.

  You might have :

  • Paid ads via Facebook and Instagram
  • A blog post sharing how the product works
  • Organic social media posts on Instagram and TikTok
  • Email waitlist campaign building excitement around the upcoming product
  • SMS campaigns to share a limited-time discount

  So, when the time comes for the sale launch, and you generate $30,000 in revenue, what channel gets the credit ?

  Do you give credit to the paid ads on Facebook ? What about Instagram ? They got people to follow you and got them on the email waitlist.

  Do you give credit to email for reminding people of the upcoming sale ? What about your social media posts that reminded people there ?

  Or do you credit your SMS campaign that shared a limited-time discount ?

  Which channel is responsible for the sale ?

  This is what attribution is all about.

  It’s about giving credit where credit is due.

  The reason you want to attribute credit ? So you know what’s working and can double down your efforts on the high-impact marketing activities and channels.

  Leveraging incrementality and attribution together

  Incrementality and attribution aren’t competing methods of analysing what’s working.

  They’re complementary to one another and go hand in hand.

  You can (and should) use attribution and incrementality in your marketing to help understand what activities, campaigns and channels are making the biggest incremental impact on your business growth.

  Why it’s important to measure incrementality

  Incrementality is crucial to measure if you want to pour your time, money and effort into the right marketing channels and tactics.

  Here are a few reasons why you need to measure incrementality if you want to be successful with your marketing and grow your business :

  1. Accurate data

  If you want to be an effective marketer, you need to be accurate.

  You can’t blindly start marketing campaigns in hopes that you will sell many products or services.

  That’s not how it works.

  Sure, you’ll probably make some sales here and there. But to truly be effective with your work, you must measure your activities and channels correctly.

  Incrementality helps you see how each channel, tactic or campaign made a difference in your marketing.

  Matomo gives you 100% accurate data on your website activities. Unlike Google Analytics, we don’t use data sampling which limits how much data is analysed.

  

  2. Helps you to best determine the right tactics for success

  How can you plan your marketing strategy if you don’t know what’s working ?

  Think about it.

  You’ll be blindly sailing the seas without a compass telling you where to go.

  Measuring incrementality in your marketing tactics and channels helps you understand the best tactics.

  It shows you what’s moving the needle (and what’s not).

  Once you can see the most impactful tactics and channels, you can forge future campaigns that you know will work.

  3. Allows you to get the most out of your marketing budget

  Since incrementality sheds light on what’s moving your business forward, you can confidently implement your efforts on the right tactics and channels.

  Guess what happens when you start doubling down on the most impactful activities ?

  You start increasing revenue, decreasing ad spend and getting a higher return on investment.

  The result is that you will get more out of your marketing budget.

  Not only will you boost revenue, but you’ll also be able to boost profit margins since you’re not wasting money on ineffective tactics.

  4. Increase traffic

  When you see what’s truly working in your business, you can figure out what channels and tactics you should be working.

  Incrementality helps you understand not only what your best revenue tactics are but also what channels and campaigns are bringing in the most traffic.

  When you can increase traffic, you can increase your overall marketing impact.

  5. Increase revenue

  Finally, with increased traffic, the inevitable result is more conversions.

  More conversions mean more revenue.

  Incrementality gives you a vision of the tactics and channels that are converting the best.

  If you can see that your SMS campaigns are driving the best ROI, then you know that you’ll grow your revenue by pouring more into acquiring SMS leads.

  By calculating incrementality regularly, you can rest assured that you’re only investing time and money into the most impactful activities in terms of revenue generation.

  How to calculate and test incrementality in marketing

  Now that you understand how incrementality works and why it’s important to calculate, the question is : 

  How do you calculate and conduct incrementality tests ?

  Given the ever-changing marketing landscape, it’s crucial to understand how to calculate and test incrementally in your business.

  If you’re not sure how incrementality testing works, then follow these simple steps :

  

  Your first step to get an incrementality measurement is to conduct what’s referred to as a “holdout test.”

  It’s not a robust test, but it’s an easy way to get the ball rolling with incrementality.

  Here’s how it works :

  1. Choose your target audience.

  With Matomo’s segmentation feature, you can get pretty specific with your target audience, such as :

  • • Visitors from the UK
    • Returning visitors
    • Mobile users
    • Visitors who clicked on a specific ad

  2. Split your audience into two groups :

  1. • Control group (60% of the segment)
     • Test group (40% of the segment)

  3. Target the control group with your marketing tactic (the simpler the tactic, the better).

  4. Target the test group with a different marketing tactic.

  5. Analyse the results. The difference between the control and test groups is the incremental lift in results. The new marketing tactic is either more effective or not.

  6. Repeat the test with a new control group (with an updated tactic) and a new test group (with a new tactic).

  Matomo can help you analyse the results of your campaigns in our Goals feature. Set up business objectives so you can easily track different goals like conversions.

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  Here’s an example of how this incrementality testing could look in real life.

  Imagine a fitness retailer wants to start showing Facebook ads in their marketing mix.

  The marketing manager decided to conduct a holdout test. If we match our example below with the steps above, this is how the holdout test might look.

  1. They choose people who’ve purchased free weights in the past as their target audience (see how that segmentation works ?).
  2. They split this segment into a control group and a test group.
  3. For this test, they direct their regular marketing campaign to the control group (60% of the segment). The campaign includes promoting a 20% off sale on organic social media posts, email marketing, and SMS.
  4. They direct their regular marketing campaign plus Facebook ads to the test group (40% of the segment).
  5. They ran the campaign for three weeks with the goal for sale conversions and noticed :

  • • The control group had a 1.5% conversion rate.
    • The test group (with Facebook ads) had a 2.1% conversion rate.
    • In this scenario, they could see the group who saw the Facebook ads convert better.
    • They created the following formula to measure the incremental lift of the Facebook ads :

  

  • • Here’s how the calculation works out : (2.1% – 1.5%) / 1.5% = 40%

  The Facebook ads had a positive 40% incremental lift in conversions during the sale.

  Incrementality testing isn’t a one-and-done process, though.

  While this first test is a great sign for the marketing manager, it doesn’t mean they should immediately throw all their money into Facebook ads.

  They should continue conducting tests to verify the initial test.

  Use Matomo to track incrementality today

  Incrementality can give you insights into exactly what’s working in your marketing (and what’s not) so you can design proven strategies to grow your business.

  If you want more help tracking your marketing efforts, try Matomo today.

  Our web analytics and behaviour analytics platform gives you firsthand data on your website visitors you can use to craft effective marketing strategies.

  Matomo provides 100% accurate data. Unlike other major web analytics platforms, we don’t do data sampling. What you see is what’s really going on in your website. That way, you can make more informed decisions for better results.

  At Matomo, we take privacy very seriously and include several advanced privacy protections to ensure you are in full control.

  As a fully compliant web analytics solution, we’re fully compliant with some of the world’s strictest privacy regulations like GDPR. With Matomo, you get peace of mind knowing you can make data-driven decisions while also being compliant. 

  If you’re ready to launch a data-driven marketing strategy today and grow your business, get started with our 21-day free trial now. No credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

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• A Beginner’s Guide to Omnichannel Analytics

  14 avril 2024, par Erin

  Linear customer journeys are as obsolete as dial-up internet and floppy disks. As a marketing manager, you know better than anyone that customers interact with your brand hundreds of times across dozens of channels before purchasing. That can make tracking them a nightmare unless you build an omnichannel analytics solution. 

  Alas, if only it were that simple. 

  Unfortunately, it’s not enough to collect data on your customers’ complex journeys just by buying an omnichannel platform. You need to generate actionable insights by using marketing attribution to tie channels to conversions. 

  This article will explain how to build a useful omnichannel analytics solution that lets you understand and improve the customer journey.

  What is omnichannel analytics ?

  Omnichannel analytics collects and analyses customer data from every touchpoint and device. The goal is to collect all this omnichannel data in one place, creating a single, real-time, unified view of your customer’s journey.

  

  Unfortunately, most businesses haven’t achieved this yet. As Karen Lellouche Tordjman and Marco Bertini say :

  “Despite all the buzz around the concept of omnichannel, most companies still view customer journeys as a linear sequence of standardised touchpoints within a given channel. But the future of customer engagement transforms touchpoints from nodes along a predefined distribution path to full-blown portals that can serve as points of sale or pathways to many other digital and virtual interactions. They link to chatbots, kiosks, robo-advisors, and other tools that customers — especially younger ones — want to engage with.”

  However, doing so is more important than ever — especially when consumers have over 300 digital touchpoints, and the average number of touchpoints in the B2B buyer journey is 27.

  Not only that, but customers expect personalised experiences across every platform — that’s the kind you can only create when you have access to omnichannel data.

  

  What might omnichannel analytics look like in practice for an e-commerce store ?

  An online store would integrate data from channels like its website, mobile app, social media accounts, Google Ads and customer service records. This would show how customers find its brand, how they use each channel to interact with it and which channels convert the most customers. 

  This would allow the e-commerce store to tailor marketing channels to customers’ needs. For instance, they could focus social media use on product discovery and customer support. Google Ads campaigns could target the best-converting products. While all this is happening, the store could also ensure every channel looks the same and delivers the same experience. 

  What are the benefits of omnichannel analytics ?

  Why go to all the trouble of creating a comprehensive view of the customer’s experience ? Because you stand to gain some pretty significant benefits when implementing omnichannel analytics.

  

  Understand the customer journey

  You want to understand how your customers behave, right ? No other method will allow you to fully understand your customer journey the way omnichannel analytics does. 

  It doesn’t matter how customers engage with your brand — whether that’s your website, app, social media profiles or physical stores — omnichannel analytics capture every interaction.

  With this 360-degree view of your customers, it’s easy to understand how they move between channels, where they encounter issues and what bottlenecks prevent them from converting. 

  Deliver better personalisation

  We don’t have to tell you that personalisation matters. But do you know just how important it is ? Since 56% of customers will become repeat buyers after a personalised experience, delivering them as often as possible is critical. 

  Omnichannel analytics helps in your quest for personalisation by highlighting the individual preferences of customer segments. For example, e-commerce stores can use omnichannel analytics to understand how shoppers behave across different devices and tailor their offers accordingly. 

  Upgrade the customer experience

  Omnichannel analytics gives you the insights to improve every aspect of the customer experience. 

  For starters, you can ensure a consistent brand experience across all your top channels by making sure they look and behave the same.

  Then, you can use omnichannel insights to tailor each channel to your customers’ requirements. For example, most people interacting with your brand on social media may seek support. Knowing that you can create dedicated support accounts to assist users. 

  Improve marketing campaigns

  Which marketing campaigns or traffic sources convert the most customers ? How can you improve these campaigns ? Omnichannel analytics has the answers. 

  When you implement omnichannel analytics you automatically track the performance of every marketing channel by attributing each conversion to one or more traffic sources. This lets you see whether Google Ads bring in more customers than your SEO efforts. Or whether social media ads are the most profitable acquisition channel. 

  Armed with this information, you can improve your marketing efforts — either by focusing on your profitable channels or rectifying problems that stop less profitable channels from converting.

  What are the challenges of omnichannel analytics ?

  There are three challenges when implementing an omnichannel analytics solution :

  

  • Complex customer journeys : Customer journeys aren’t linear and can be incredibly difficult to track. 
  • Regulatory and privacy issues : When you start gathering customer data, you quickly come up against consumer privacy laws. 
  • No underlying goal : There has to be a reason to go to all this effort, but brands don’t always have goals in mind before they start. 

  You can’t do anything about the first challenge. 

  After all, your customer journey will almost never be linear. And isn’t the point of implementing an omnichannel solution to understand these complex journeys in the first place ? Once you set up omnichannel analytics, these journeys will be much easier to decipher. 

  As for the other two :

  Using the right software that respects user privacy and complies with all major privacy laws will avoid regulatory issues. Take Matomo, for instance. Our software was designed with privacy in mind and is configured to follow the strictest privacy laws, such as GDPR. 

  Tying omnichannel analytics to marketing attribution will solve the final challenge by giving your omnichannel efforts a goal. When you tie omnichannel analytics to your marketing efforts, you aren’t just getting a 360-degree view of your customer journey for the sake of it. You are getting that view to improve your marketing efforts and increase sales.

  Try Matomo for Free

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

  Start for free

  No credit card required

  How to set up an omnichannel analytics solution

  Want to set up a seamless analytical environment that incorporates data from every possible source ? Follow these five steps :

  Choose one or more analytics providers

  You can use several tools to build an omnichannel analytics solution. These include web and app analytics tools, customer data platforms that centralise first-party data and business intelligence tools (typically used for visualisation). 

  Which tools you use will depend on your goals and your budget — the loftier your ambitions and the higher your budget, the more tools you can use. 

  Ideally, you should use as few tools as possible to capture your data. Most teams won’t need business intelligence platforms, for example. However, you may or may not need both an analytics platform and a customer data platform. Your decision will depend on how many channels your customers use and how well your analytics tool tracks everything.

  If it can capture web and app usage while integrating with third-party platforms like your back-end e-commerce platform, then it’s probably enough.

  Collect accurate data at every touchpoint 

  Your omnichannel analytics efforts hinge on the quantity and quality of data you can collect. You want to gather data from every touchpoint possible and store that data in as few places as possible. That’s why choosing as few tools as possible in the step above is so important. 

  So, where should you start ? Common data sources include :

  • Your website
  • Apps (iOS and Android)
  • Social media profiles
  • ERPs
  • PoS systems

  At the same time, make sure you’re tracking all relevant metrics. Revenue, customer engagement and conversion-focused metrics like conversion rate, dwell time, cart abandonment rate and churn rate are particularly important. 

  Set up marketing attribution

  Setting up marketing attribution (also known as multi-touch attribution) is essential to tie omnichannel data to business goals. It’s the only way to know exactly how valuable each marketing channel is and where each customer comes from. 

  You’ll want to use multi-touch attribution, given you have data from across the customer journey.

  

  Multi-touch attribution models can include (but are not limited to) :

  • Linear : where each touchpoint is given equal weighting
  • Time decay : where touchpoints are more valuable the nearer they are to conversion
  • Position-based : where the first and last touch points are more valuable than all the others. 

  You don’t have to use just one of the models above, however. One of the benefits of using a web analytics tool like Matomo is that you can choose between different attribution models and compare them.

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  Create reports that help you visualise data

  Dashboards are your friend here. They’ll let you see KPIs at a glance, allowing you to keep track of day-to-day changes in your customer journey. Ideally, you’ll want a platform that lets you customise dashboard widgets so only relevant KPIs are shown. 

  

  Setting up standard and custom reports is also important. Custom reports allow you to choose metrics and dimensions that align with your goals. They will also allow you to present your data most meaningfully to your team, increasing the likelihood they act upon insights. 

  Analyse data and take action

  Now that you have customer journey data at your fingertips, it’s time to analyse it. After all, there’s no point in implementing an omnichannel analytics solution if you aren’t going to take action. 

  If you’re unsure where to start, re-read the benefits we listed at the start of this article. You could use your omnichannel insights to improve your marketing campaigns by doubling down on the channels that bring in the best customers.

  Or you could identify (and fix) bottlenecks in the customer journey so customers are less likely to fall out of your funnel between certain channels. 

  Just make sure you take action based on your data alone.

  Make the most of omnichannel analytics with Matomo

  A comprehensive web and app analytics platform is vital to any omnichannel analytics strategy. 

  But not just any solution will do. When privacy regulations impede an omnichannel analytics solution, you need a platform to capture accurate data without breaking privacy laws or your users’ trust. 

  That’s where Matomo comes in. Our privacy-friendly web analytics platform ensures accurate tracking of web traffic while keeping you compliant with even the strictest regulations. Moreover, our range of APIs and SDKs makes it easy to track interactions from all your digital products (website, apps, e-commerce back-ends, etc.) in one place. 

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

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