Fraudulent use of an individual’s identity, or ‘ID theft,’ involves obtaining their information and using it for criminal purposes. It’s common for victims to never find out exactly how their information was obtained and dealing with the repercussions can be time-consuming and expensive. For businesses, big or small, it is extremely important to know who their customers are and prevent fraud. Fraud can impact businesses in several ways, from financial losses to reputational damage. For instance, creditors in the finance sector need to be vetting new customers with stringent customer data validation procedures.
Not only do such measures help businesses protect themselves from fraudulent data, but also preserve the trust of existing customers.
But how do you implement data verification checks into your business model? And more importantly, in a way that doesn’t impact the customer experience.
This article explains how businesses can better protect themselves against customer identity fraud, with methods of how to verify genuine customer identity.
Ways businesses can prevent customer identity fraud
In today’s highly connected and digital world, it is a possibility that your customers can fall victim to identity fraud. Your company, customers, and data can be severely affected by fraudsters. This is why it is paramount to be aware of identity theft and ensure that your customer data is high quality and accurate.
There are several ways that you can stay mindful of identity theft and keep your data clean, as well as methods to identify fraudulent or spam information in your database.
Here are some simple steps to help you prevent customer identity theft and verify customer data.
Identify Verification (IDV)
The purpose of identity verification is to prove that the individual behind a process is who they claim to be. The reasoning for this is to prevent anyone from carrying out a process on behalf of another without authorization, creating false identities, or committing fraud.
Checking identities consistently reduces the likelihood that one organisation or service will do less effective identity checks than another. As a result, identity fraud may be targeted at fewer organizations and services.
Both physical and digital evidence can be used to identify an individual. These can be in the form of a passport or information stored in a database for example. Checking the evidence is vital and you must be sure it’s genuine. This will prove if it has been forged or counterfeit.
By successfully checking users’ identities, you can be confident that you’ll give the right people the right things.
Check on financial and credit reports regularly
In contrast to credit card fraud against individuals, business credit fraud can affect multiple people – and even the company’s reputation.
Fraudsters do not need physical business credit cards to commit fraud, so unauthorised activity may be occurring without your knowledge. Business credit card statements showing fraudulent transactions may indicate you have fallen victim to fraud.
Check your statements regularly for unfamiliar charges so that you can catch them as soon as possible. To make the task more manageable, consider taking advantage of online banking tools to conduct weekly reviews. Update passwords regularly and remain vigilant when accepting orders. Ensure that issues are reported to the credit card company as soon as possible.
Use identity verification software
Identity verification software helps companies verify the identity of their users in real life. Due to the ease of creating fake identities online, it’s crucial to confirm that a person is who they say they are. Software that verifies identity is a great way to make sure what you see on the website matches what you expect in person.
Sign-in processes, questions, and answers, or video IDs are typical methods of identity verification software. By using this kind of software, you will minimise the risk of falling victim to fraud for your business and maximise the trust of customers.
Find a provider of identity verification and fraud prevention solutions that can evolve quickly and easily as the tactics used by fraudsters change. See how REaD Group can help you and your business with our Smart Link by contacting us!
Online document verification
The most common method of customer verification is online document verification. Using third-party solutions that help verify online documents, you’ll be able to identify customers with ease. This kind of technology provides 100% proof of authenticity, although it can create additional inconvenience for customers. It is also important for businesses to ensure GDPR compliance here since this involves processing highly personal data.
Utilise effective decision-making based on identity composition. A more comprehensive analysis of the composition of identity and deterring fraudulent transactions can be achieved by looking at more than just a “match/match” or “pass/fail” result. If necessary, obtain a higher level of verification.
Create dynamic Knowledge-Based-Authentication (KBA) questions when suspicious identity attributes are present by executing multiple-choice questions that only your actual customer can answer.
Know Your Customer (KYC)
As part of Know Your Customer (KYC) regulations, banks verify the legitimacy of prospective customers before opening an account, as well as throughout the lifetime of the account.
KYC procedures are essential to the banking, financial, and insurance industries in particular because it prevents criminals and other bad actors from easily concealing illegitimate funds. In addition to protecting banks from financial and reputational harm, KYC processes ensure compliance with government regulations.
Anti-Money Laundering (AML)
Anti-Money Laundering (AML) regulations refer to a broad set of security measures that banks implement to reduce the risk of illegal funds being disguised as legitimate income by criminals. The financial and reputational standing of banks depends on this regulation, as it makes it tougher for such crimes to take place.
In order to detect suspicious transactions and assess money laundering risks, financial institutions need sophisticated customer due diligence plans and stay knowledgeable about Anti-Money Laundering regulations.
Anti-Money Laundering (AML) and Know Your Customer (KYC) regulations are constantly evolving, so adhering to them isn’t always easy.
This is particularly true when technology demands rise and departmental funds remain stagnant. By getting the right help, you can perform due diligence and affordably quantify risk.
Validate your customer data – REaD Smart Link
Get your customer data validated and prevent identity fraud with REaD Smart Link, a powerful tool designed to help verify identity and contactability across households or individuals. Smart Link cross-references customer data using the most comprehensive consumer data universe in the UK.
This tool includes all the channel variables we hold on an individual level.
- Link – Multiple databases or contact channels can be reliably linked together through links
- Verify – Utilise multiple sources of information to identify the same individual or household
- Validate – Be confident that an individual is who they claim to be by getting their identity fully verified and knowing your customer.
Ways customers can prevent identity fraud
As well as monitoring the signs of fraudulent data, it’s useful for businesses to prevent identity theft at the source, by advising customers on the best ways to protect their identity. This is especially useful for financial businesses.
Passwords and account numbers are often used to access our online accounts, and we provide these details every day. Because of this, customers risk having their personal information stolen or misused. Thankfully, there are great ways to help customers reduce the chance of identity theft that are easy to implement, and at no cost.
A fail-safe method to prevent identity fraud is unlikely, and monitoring services are usually only notified when something has gone wrong. You can, however, make identity theft much more difficult with some simple tips for customers.
Lock mobile devices
There is a real risk associated with mobile devices. According to a study by cybersecurity firm Kaspersky Labs, our mobile devices are only regularly locked by 48% of us. Make sure you use a password and/or fingerprint identification when using electronic devices. Encourage customers to use an online banking app rather than use mobile browsers for banking.
You shouldn’t throw away any credit card, bank, or investment statements that someone might find in the bin. Be sure to shred your junk mail and any other letters that are considered disposable with your personal details on them.
Be wary of phishing scams
Emails and text messages with suspicious-looking links should not be clicked. Phishing is a cyber-attack where identity thieves trick you into providing personal details such as your bank account or credit card details. They can appear like they’re coming from the storefront of a bank, credit card company, mortgage lender, or other financial institutions.
Some emails may include an attachment that you will be asked to open. Doing so could install malware that will be harmful to your device. Be wary of its legitimacy and don’t click on anything you are unfamiliar with.
In addition, fraudsters may often pose as bank employees or credit card company employees over the phone. It is a fact that no legitimate organisation will call you and ask for personal information from you.
If you suspect anything then ask for the credentials from the caller and get in contact with the company they are associated with to confirm it’s all legitimate.
Protect your documents and limit exposure
It is possible for physical documents to pose a security risk if they are not properly maintained. Personal information such as your name, address, and even bank account information can be found on these documents, making them useful to identity thieves.
Make sure not to leave your mail in the letterbox as they are a frequent target for identity fraud. Hold on to paper receipts or shred them if they are unwanted as they can prove valuable to thieves. It is wise to sign yourself up for digital statements rather than letters. This will limit your paper trail and you will have less exposure too.
Be vigilant, and stay safe
It’s critical not to take the security of your personal data for granted, since identity thieves often strike at the most inconvenient times. In addition to protecting your information and identity, you’ll make yourself more difficult for thieves to target.
Keep your information safe by monitoring your credit, protecting your devices, avoiding phishing and other scams, and ensuring that your documents are not accessed by anyone.
Have a question for us?
Get in touch with our expert team who will be happy to assist you with the right advice on how to identify genuine customer and prevent identity fraud.
Data is at the heart of every modern business. Without data, businesses would have no way to strategise campaigns, engage with customers, or discover new contacts. For many businesses, data management can come with several difficulties. Datasets can encounter many data quality issues, hindering the effectiveness and performance of the activities that rely on them.
Data quality issues are very common. So, if you’re wondering why your customer data isn’t delivering the results you need, you are not alone. It’s key for businesses to stay on top of data quality issues with the appropriate management.
This article covers the most common data quality issues that businesses face, and how to overcome them. Let’s get started!
Why is data quality important?
Data quality is a term used to describe how well your data serves the purpose it is intended for. For example, a customer database might be used by businesses to send regular email communications, or direct mail campaigns to contacts. This process might even involve additional activities, such as data segmentation, to tailor specific communications to specific customer categories.
But what if this data contained inaccuracies or inconsistencies?
If there are issues with data, then it cannot serve its intended purpose, putting a halt to the business activities that require it. Data quality is therefore integral to any successful business model.
So let’s understand how to look out for the most common data quality issues, and more importantly, how to overcome them.
6 Most common data quality issues
Data quality issues can arise from all angles. They can even be hard to spot, with many businesses unaware that their data actually contains fundamental errors that are holding back its potential.
Here’s an overview of the most common data quality issues that organisations face.
1. Human error
One of the most common causes of data quality issues is human error. Data entry relies on human input, so when this goes wrong, the data becomes practically unusable.
Human error can occur on either side of data entry, both from the customer and the business.
For instance, if customers and prospects provide their contact details via a website form, there is a chance that they may input this information wrong. Equally, businesses can also be responsible for human error. It is possible for employees that manage the data to make mistakes when handing, migrating, merging or inputting data.
It is important for businesses to ensure that all employees understand how to use data management systems and reduce the likelihood of human error.
That’s why online data management platforms are so handy. These tools are specifically designed to make data management much easier for businesses.
2. Incorrect formatting
Another cause of data quality issues is inconsistent or incorrect data formatting. Formatting refers to the way your data is organised, processed and categorised.
For example, email information might be formatted under the category name ‘email’, but it could also be formatted under the name ‘email_address’ or something similar.
If this is not consistent across the dataset, this can lead to big data quality issues. Systems that process this data will not recognise that these labels actually mean the same thing, instead, attributing them to different identifier types.
This makes it very difficult to consolidate, adapt and use the data effectively. It can also increase the likelihood of human error and data duplication, as anyone who tries to reformat the data more consistently might create other data errors in doing so.
The good news is that this can easily be overcome with some simple data cleansing.
3. Data duplication
There are now so many ways for organisations to acquire data. From website sign-ups, social media, to buying customer databases. Data comes from all directions, so it’s important to ensure that data isn’t being duplicated.
Duplicate data occurs when customer information appears more than once in the database, or multiple variations of the same individual appear. This can have a negative impact on business performance for a number of reasons.
Firstly, budget is wasted on duplicate records, having a significant impact on return on investment (ROI). It is more beneficial to make space for new, unique customer records. That way, the budget is not wasted on engaging with the same contact twice.
Secondly, duplicate data can damage your brand image. It is unlikely that a contact who receives the same information twice will be happy about it. This is an easy way to frustrate customers and prospects, and can make your business appear disorganised and untrustworthy.
4. Inaccurate data
Accuracy is critical to quality data. In any industry, data inaccuracies will hold you back from achieving your aims – both in the short and long term.
In essence, there is almost no point in engaging with contacts in your database if the information is incorrect. By not addressing this key data quality issue, incorrect contact data could actively be hurting your business performance.
It is tough to identify inaccurate data. In some cases, communications might bounce. However, in other cases, you just have no idea. This is a commonly unnoticed data quality issue, since you can only really know for sure by verifying the data through a trusted source – such as our market-leading data validation service.
Why inaccurate data is a big issue
Accurate data also ensures businesses are prepared in the event of unpredictable change. For example, in the emergence of the COVID-19 outbreak, businesses quickly had no choice but to rely on customer data in order to operate their businesses online, and adapt in new directions.
This was no more apparent in the USA’s response and management of COVID-19, which was hindered as a result of health data quality issues. Reports highlight the underappreciated significance of healthcare data accuracy in the event of unprecedented change, where low-quality data made it difficult to cope and adapt.
Though, many organisations took proactive data-driven approaches to adapt their strategy in the wake of the pandemic.
For instance, Marie Curie partnered with REaD Group to incorporate COVID-19 risk data into their data strategy. This helped Marie Curie identify the impact of COVID-19 on the UK population, and manage their marketing strategy and future fundraising activities around this.
5. Incomplete data
Similar to inaccurate data, incomplete data can also have a negative impact on your business performance.
This data quality issue might not be as severe as having totally inaccurate data, but it is nonetheless another hindrance to your marketing capabilities.
If data is entered manually through form fields, the customer might not input their full details. Furthermore, some customers might opt to only input certain fields of information such as their name and phone number, whereas some might opt to input their name and email address. This results not only in incomplete information, but inconsistent information.
One way that organisations can help control this is by making certain form fields a required entry. That way, data entries will become more consistent and complete.
However, if your incomplete data is too far gone, this fix won’t be enough.
But not to worry. There are several ways to overcome this data quality problem. For instance, through data enhancement services – which is designed to fill in those important missing gaps in your dataset.
6. Fraudulent data
A less common but very serious data quality issue is fraudulent data. Sometimes, incorrect data is inputted for spam or fraudulent purposes. In no case is this information ever valuable to businesses.
This data quality issue has a serious impact on ROI, since there is no value in this kind of data. Keeping your data clean and preventing customer identity fraud is of the utmost importance.
How purposeful is your data?
Data is only as valuable as you make it. We help businesses get the most out of their data with a range of professional data services. From making your data clean and compliant, to enhancing it with the right information, we work with you to maximise your data’s potential.
Get in touch with us to find out how we can help.
Clean up your data – REaD Online
Looking for data management? Take control of your data with REaD Online, the complete self-serving data management solution that helps you manage, validate, clean, update and enhance your data.
Data is incredibly powerful. When utilised properly, data can inform business decisions and help you create impactful marketing campaigns that resonate with your customers.
In the retail sector, this can lead to both an increase in sales and customer loyalty.
But data on its own is not enough – it’s how you use it. Our guide covers everything you need to know about retail data analytics. From what it is, to how you can use it to bring about tangible results for your business.
What is retail analytics?
Retail analytics is the process of using retail data to identify trends, patterns and consumer purchasing behaviours. Retail analytics can be used to predict outcomes with more accuracy and make better business decisions. Retail data includes consumer, sales and industry data.
The goal of retail analytics is to transform data into quantitative insights that go on to drive high-level decision-making. Retail data analytics plays an important role in just about every aspect of retail, from sales and marketing, to operations and inventory.
For instance, retail analytics can be used to help companies deliver personalised promotions, optimise marketing spend, predict better supply and demand, and attract new customers.
In short, retail data analytics is about utilising the power of your data, and using it to form strategic and sophisticated business decisions.
The importance of retail analytics
A business decision that isn’t informed by data is essentially a shot in the dark. Your customers might surprise you. Retail analytics takes away the guesswork.
For example, you might think your target market are more likely to buy if you offer 10% off, when in fact they’re more receptive to free shipping.
Additionally, the online retail space is growing at an incredible rate, and we have seen some major shifts in consumer behaviour in light of the pandemic. As retail data grows more and more rich, ignoring it would see you miss out on a huge opportunity.
The benefits of retail analytics
The use of retail analytics brings with it a multitude of advantages that will put you on top of the competition.
Here are some of the main benefits of using retail data analytics, as well as some examples of how you might use them in the world of retail.
1. Customer behaviour insights
Retail data analytics can give you a 360-degree view of your customers, which goes beyond age and gender. Find out your customers spending habits, likes, hobbies, behavioural patterns, and much more. This kind of single customer view knowledge is invaluable; it can help shape everything from your communication channels to the promotional offers you run.
For example, looking into the spending habits of your customers can arm retail companies with a valuable insight into the type of products they prefer, how much they usually spend, and when they make purchases.
As a result, you can make personalised recommendations that they’re more likely to purchase.
2. Improve marketing campaigns
Marketing efforts that attempt to appeal to everyone will appeal to no one. You need to find out exactly who your customers are, and speak to them in their language. How do you do this? By listening to the data.
Retail analytics help develop impactful marketing campaigns, that are more likely to convert and show promising ROI.
For instance, if the data is showing you that ethically sourced and sustainable products are popular within your target market, then you can emphasise and promote products that fit that criteria.
3. Choose the right channel
Not only can retail analytics inform the tone and content of your marketing campaigns, but the media by which they are delivered on, too.
For example, an analysis of your retail data could reveal that your desired customer is more receptive to Facebook ads than they are to direct mail marketing. As a result, you can choose your channel of communication accordingly.
Your campaign could be perfect, but if it’s not run on the right platform, it will fail. Retail data analytics can ensure that you’re making wise, well-though-out decisions. And, whilst this analysis cannot always guarantee success, it does increase the likelihood of it.
4. Optimise your operations
Retail analytics can help you better predict supply and demand. Analysing spending habits and sales will help you identify which products and services are in demand.
Again, retail data analytics offers you the opportunity here to take away the guesswork. Your orders and inventory can be led by the data. In turn, you can maximise profits by not wasting money on stock that won’t sell.
5. Increase customer satisfaction
If your customers consistently abandon their carts at certain points in the sales process, or sales consistently dip on a particular national holiday, this will be reflected in your data. As such, it means you have the power to do something about it.
Perhaps there are too many steps at the check-out stage, or the free delivery on orders over a certain amount is causing customers who don’t meet that threshold to abandon the purchase.
You can design a better customer experience by knowing what keeps your customers coming back and what drives them away.
You can significantly increase your store’s customer satisfaction by making these changes based on retail analytics. Since you’re likely to be rewarded for this with their loyalty, it’s a win-win situation.
These advantages have the potential to bring about invaluable business results. Firstly, they present the opportunity to stop putting your time and resources into products, services, and marketing campaigns that won’t produce a strong ROI. Instead, you can focus your efforts on initiatives that are driving growth.
Secondly, these benefits will drive customer loyalty and satisfaction. Not only can this push sales, but it will also increase brand awareness. Brand awareness can go a long way to securing future sales and expanding your customer base.
As we can see, if you utilise data analytics correctly, you can be rewarded with some impressive competitive advantages.
Retail analytics factors to consider
Though retail analytics can form the backbone of some incredibly smart business decisions, there are still some factors you will need to consider. These include:
1. Be aware of the bigger picture
Make sure that you don’t focus too much on one single metric. Retail analytics can provide valuable insights, but even more so when you connect the dots.
Comparing data sets can provide you with deeper insights, as mixing and matching will allow you to understand the context and see the bigger picture. So delve into your retail data and look for other reports or points that you can then combine.
2. Focus on the right metrics for your business
Retail data analytics can provide you with insights to almost every single aspect of your business. However, every business is different, and metrics that might matter to some, might not to others.
Identify your business goals and priorities, and seek out the data that will edge you closer to achieving these.
3. Combine data with expert opinion
There’s no denying that retail data analytics have the power to provide you with advanced knowledge, that can lead to strategic and successful decision-making. However, it’s still vital to marry the data with human insight.
Combining the data with expert human opinion can take your findings from powerful to unstoppable – so don’t overlook it.
Start your retail analytics journey today
At REaD Group, we are the experts in retail data. Our unmatched retail data services have been proven to drive impressive results for businesses. We can provide you with the tools you need to succeed.
Our retail data services are tailored to your specific needs and variables, that will help you acquire, retain and re-engage with your customers.
Start your retail analytics journey today!
Data enhancement is the process of combining raw data with another set of data to form a more comprehensive view of customer information. The additional dataset is usually provided by a trusted third party offering specialist data enrichment services.
For instance, if you wanted to enhance your customer data with consumer spending information, data enrichment can be used to update existing customer records with this data. This can be used to enrich customer data with a range of valuable records, helping businesses maximise the use of datasets.
Enhancing your data can yield some powerful results for your marketing efforts that aren’t to be underestimated. From increasing ROI, to establishing deeper relationships with customers, the benefits of data enrichment are invaluable.
In this guide, we’ll cover everything you need to know about data enrichment, including how it works, the types of data you might combine, and how you can use it to your advantage.
How does data enrichment work?
Data enrichment seeks to enhance data by combining existing customer records with additional information. Data enrichment is most effective when the additional data is provided by a reliable, external source. Though, businesses can also enrich databases with existing first-party data. For example:
In the retail sector, you could combine demographic data with purchase history information. This would leave you with a holistic view of your customer, with meaningful insights that goes beyond the basics of age, gender, and location. In turn, this can help you understand what type of people are attracted to certain products and adjust your marketing strategy accordingly.
Combining data in this way can help you identify patterns and trends, and consequently create more targeted ads and communications.
There’s no strict limit on how many datasets you can combine, either, it will depend on what you are looking to find out by combining them. For example:
A retailer selling high-end wellies might want to find out their customers’ geographic location, age, gender and salary, or average spend, combining this information to tailor marketing efforts and directly target specific customer segments.
Online data enrichment
One of the most simplified ways that businesses are enriching their data is through the use of online data management platforms, such as REaDOnline.
This offers a self-serving data enrichment solution, where organisations can upload their existing data and view insights into data accuracy and enhancement opportunities.
The advantages of data enrichment
Data enrichment brings with it an abundance of benefits for your business that shouldn’t be overlooked. Here’s an overview of the main benefits of data enrichment.
1. Make informed business choices
Decisions without data are essentially a stab in the dark. Data enrichment allows you to utilise and strengthen data, and then use it to make informed, stronger business decisions.
That’s not to say that every data-driven decision will soar, but it will increase the likelihood of success.
2. Create impactful campaigns and increase ROI
Data enrichment gives you the opportunity to produce marketing campaigns that speak to your customers in their language, and promote products or services you know they are interested in.
For example, through data enrichment, you might discover that millennial women are more likely to purchase a certain product over Gen Z. You can create targeted ads and promotions that appeal to millennial women. As a result, you’re likely to increase your sales and ROI.
3. Forge meaningful connections with your customers
Securing sales and a strong return on your investment is desirable. But let’s not forget your customers are people, too. Data enrichment allows you to see your customers as just that, by providing you with a deeper insight into their behaviours, characteristics, and personal preferences.
You can take this information and use it to forge meaningful relationships with your customer base. This is important in and of itself, but will also undoubtedly lead to increased customer loyalty and satisfaction.
4. Reliable, accurate data
We’ve talked about how data enrichment can inform smart business choices, but to be led by data, first you need to trust it.
Enhancing data doesn’t just broaden your view of individual customers, but also ensures the data is up-to-date and accurate too in combination with data cleansing.
Consequently, you’re left with datasets you can actually rely on to improve business performance.
Let REaD Group take care of all your data enrichment needs!
We’re proud to offer the most comprehensive data enrichment service the UK has to offer. Our REaD Enhance service consists of:
Core – A comprehensive individual level product containing over 50 million UK adults, with over 800 actual and modelled attributes across demographic and lifestyle variables.
Property – An address level product built using REaD’s trusted, comprehensive and relevant data assets.
Postcode Indicator – A postcode level product containing all PAF valid residential postcodes, with indicators across over 300 variables. This data supports location analysis, marketing strategies, targeting, and product development.
Geo – Compiled with a number of open-source data points with additional modelled attributes including GeoSociety; a rich source of data that gives valuable insight into what issues are concerning particular locations and sections of society.
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Data processing is an integral part of any modern day business. There can be many reasons why organisations need to process personal data, from acquiring new customers, to collecting cookies and running marketing campaigns.
GDPR regulations outline six lawful bases by which businesses can process personal data. These 6 lawful bases include: consent, contractual requirements, vital interests, legal requirements, public interest, and legitimate interest.
What is legitimate interest?
Legitimate Interest is one of the six conditions outlined by GDPR regulations that allow organisations to legally process personal data. Legitimate interests can include commercial, individual, or societal interests. The data processing must be necessary in order to be considered legitimate.
Legitimate interest can be a confusing concept to grasp. Other GDPR conditions are more self-explanatory, such as ‘contractual requirements’, ‘legal obligations’ and ‘vital interests’. Although, legitimate interest is less definitive.
This article covers everything you need to know about legitimate interest to help organisations unpack this broad area in more detail.
When is legitimate interest mostly used?
Legitimate interest is the most flexible condition of GDPR’s six lawful bases of processing data, and relates to processing data in the interest of legitimate business, individual, or third party needs.
Legitimate interest is mostly used to process personal data in ways that people would reasonably expect, in ways that have minimal impact on privacy. To process personal data on the basis of legitimate interests, organisations must have a compelling justification for processing the data.
For instance, it could be in the legitimate interest of a charity to increase its donor database. It could be the legitimate interest of a new business to obtain new customers via an acquisition-based marketing campaign.
The Information Commissioners Office (ICO) guidance states the following:: “the legitimate interests can be your own interests or the interests of third parties. They can include commercial interests, individual interests or broader societal benefits.”
Defining legitimate interest sits at an organisational level. When processing personal data for direct marketing purposes, the organisation must complete a Legitimate Interest Assessment (LIA) and balancing test in order to document their legitimate interests.
Choosing to process personal data on the basis of legitimate interests can come with extra responsibility and obligation. Organisations must weigh up individuals’ rights and interests using a Legitimate Interest Assessment.
What counts as a ‘legitimate interest’?
Under GDPR, legitimate interest applies when organisations process personal data in ways that individuals would expect their data to be handled. Legitimate interests must be clearly specified and cannot apply against the law, ethical reasoning, or public policy.
This can make it difficult to determine whether legitimate interest can apply to your organisation’s data processing activities. To get a better understanding of what counts as legitimate interest, here are some examples of cases where this lawful basis is often applied.
Examples of legitimate interest
Examples of legitimate interests can include (but are not limited to):
- Processing client and employee data
- Prevention of fraud
- Intra-group transfers
- IT security
How to demonstrate legitimate interest
Demonstrating legitimate interest is essential if it is to be used as a lawful basis for data processing.
Article 6(1)(f) in the GDPR guidelines incorporates three key elements that can be used to test whether your activities demonstrate legitimate interests.
These three elements of legitimate interest include:
- Purpose test – is there a legitimate interest to process data?
- Necessity test – is data processing required to fulfil that purpose?
- Balancing test – are the legitimate interests outweighed by the individual’s rights, interests, and freedom?
Purpose, necessity and balancing tests can be used to ascertain whether your data processing activities are within the realm of legitimate interests.
What does Article 6(1)(f) state about legitimate interests?
Official GDPR regulations state that organisations must adhere to a lawful basis when processing personal data – this should follow principles of lawfulness, fairness and transparency.
Article 6(1)(f) in the EU GDPR regulations states:
“1.Processing shall be lawful only if and to the extent that at least one of the following applies:
(f) processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party, except where such interests are overridden by the interests or fundamental rights and freedoms of the data subject which require protection of personal data, in particular where the data subject is a child.”
Does legitimate interest apply to marketing purposes?
Legitimate interest is one of the most lawful bases used to collect personal data for marketing purposes. There are many reasons why businesses may choose to store personal data for marketing, such as acquiring new customers.
This lawful basis can apply to marketing purposes, but the legitimate interest must be justified and documented.
This means that the GDPR basis of legitimate interest can depend on the circumstances, since interest can differ amongst businesses, sectors, markets and individuals.
Recital 47 of GDPR
Recital 47 of GDPR states that “direct marketing purposes may be regarded as carried out for legitimate interest”. The key word here is ‘may’, meaning that the justification of legitimate interest for direct marketing can depend on the context.
The best way for businesses to demonstrate legitimate interest is to carry out a legitimate interest purpose test. The results from this will give a more definitive impression of whether legitimate interest can apply to your marketing activities.
Does legitimate interest apply to cookies?
Legitimate interest does not apply to cookies. Cookies that collect website visitors’ personal information cannot be processed lawfully under GDPR without consent.
Following the introduction of GDPR laws in 2016, websites required pop-ups that ask users for consent to collect cookies. If users do not accept the website’s request to collect cookies, then the site cannot lawfully process cookies to collect personal visitor data.
Where the required consent is not obtained, organisations cannot choose to rely on legitimate interests as an alternative.
What are the individual’s rights?
Under GDPR regulations, individuals have the following rights in regard to the processing of their personal data:
- The right to be informed
- The right of access
- The right to erasure
- The right to rectification
- The right to restrict processing
- The right to object
- The right to data portability
- Rights in relation to automated decision making and profiling.
Recital 75 of the GDPR regulations provide guidance on the individuals’ rights and freedoms when it comes to data processing and legitimate interests. Individuals have protective rights in cases where data processing has the potential to impact the individual in any way. This includes physical, financial, personal impacts and many other types, such as:
- Prevention from exercising rights
- Loss of control over personal data
- Social, economic, or reputational disadvantage
Can individual rights override legitimate interests?
Individual rights can override legitimate interests if their personal data is processed in ways that they would not reasonably expect. If processing of personal data is unexpected in any way, the individual can exercise their rights to object and restrict processing, as well as other freedoms.
This is because the individual loses control over how their personal data is used, and that the processing does not align with their expectations and interests.
It is important to manage reasonable expectations from the outset of data processing under legitimate interests through clear transparency obligations that inform the individual of their ability to exercise rights.
When to avoid legitimate interest as a lawful basis
Avoid legitimate interests as a lawful basis of data processing if:
- You believe individuals might have personal reservations about the way their data is processed
- Data processing has the potential to cause harm to individuals or groups
- If you are a public authority – public authorities cannot process data under legitimate interests unless there are clear commercial justifications.
To summarise, legitimate interest is one of the 6 lawful bases of data processing under GDPR. Legitimate interests can be a grey area that many businesses find confusing, since these are broadly defined as reasonable commercial, individual, or societal interests.
It is important for businesses to clearly define the legitimate interests they intend to rely on when processing data, and ensure that these are reasonable.
Is your data GDPR compliant?
Ensure your data is lawful and compliant with our GDPR compliance services. We help businesses process data lawfully and keep databases to a high quality for maximum results and fewer risks.
Have any questions? Get in touch with us.
A DMP (Data Management Platform) is used to collect, organise and optimise data from different sources. Data Management Platforms help organisations understand more about customers by matching data against 3rd party lists, segmenting customers into marketable groups and ensuring data is accurate.
Data collected in the DMP is used for personalisation in marketing and advertising, as well as ensuring data quality.
Using a DMP, such as REaDOnline, is a great way to improve marketing efforts and engage with customers using more targeted communications. All whilst keeping data organised and centralised in one platform.
A lot of companies already consider using a data management platform, but need to learn more about it before going ahead. How does a DMP work? How does it integrate with current marketing activities?
This guide covers everything you need to know about Data Management Platforms. From how they work, the kinds of data they handle, and how they enhance your marketing.
How does a DMP work?
A Data Management Platform works by gathering your customer data and storing it in a centralised database. Stored data may include customer information, demographics, buying habits and contact details.
As an audience-focused solution, DMPs help marketers draw insights from the data, using first, second, and third party data to validate the data quality and create segmented audiences.
As well as improving the quality of data and creating segmented audiences, DMPs work by unifying datasets all in one place – making it simpler for organisations to manage data.
DMPs can help improve data quality by auditing the dataset for inaccuracies, duplicates, and formatting errors.
For example, the platform can ensure the data is kept clean through data cleansing methods. This cleans data by measuring the details against 3rd party data lists. So, for example, if a customer had changed their address, the DMP could update the contact address details, using goneaway suppression to cross-reference this information against up-to-date databases. Similarly, a DMP can use deceased suppression to identify and remove deceased individuals from the database.
Additionally, Data Management Platforms help validate email addresses and check name formatting to ensure the data is of high quality.
This is a vital aspect of data management for any organisation, in any sector. If data is inaccurate, it is simply not useful to the business. In fact, 69% of organisations say that inaccurate data is the biggest challenge in data management, according to a study by Experian.
The DMP can also check for duplicate information, keeping data clean and accurate to ensure that the organisation is engaging with active customers, and is not sending duplicate communications.
As well as ensuring that information is accurate, Data Management Platforms can enhance your database using Data Enrichment and Data Segmentation methods.
This can help organisations develop more personalised experiences for customers and prospects. For instance, by using the DMP to segment audiences into meaningful groups. Based on shared qualities, these segments can then be targeted using tailored communications.
As a result, businesses can expect to see better return on investment from their marketing campaigns, since communications are more targeted towards the intended audience. Personalised communications are also shown to increase trust between consumers and brands.
DMPs help make data management more straightforward. Designed to bring all data into one place, Data Management Platforms are a dream come true for marketers. With a centralised view of customer data, organisations can optimise campaigns with more comprehensive data insights.
With unified data, all in one place, this makes day to day data management easy and simple. Not only does this make customer data easier to manage, it can also help piece together valuable information about customers to reveal key insights.
As a result, organisations can understand their customers better and develop more effective marketing campaigns.
Using a data management platform
Using a Data Management Platform is actually pretty straightforward. Data management is one of the most important, but time-consuming processes for any modern marketer. As a result, Data Management Platforms are designed to take the hard work out of handling data.
In a study from Experian, 83% of organisations said that data formed a central part of their business strategy – so it’s vital that DMPs offer a simple solution.
Our own DMP, REaDOnline, offers an intuitive user interface, making it easier than ever to manage and optimise your data.
How DMPs use data
Data management platforms often use a variety of customer data sources to ensure the data is accurate, and also enhance it with relevant information. DMPs can combine first, second and third party data, allowing businesses to gather customer insights all in one place.
This is especially useful for organisations that collect customer data through a variety of sources. For example, for companies who collect data from website visits, also buy prospect databases.
REaDOnline lets users upload data from a variety of sources, which is then audited
Using this combination of data, DMPs can:
- Collect data from different sources (online, offline, first-party, second party, third party)
- Enhance data by creating targeted audiences
- Clean and validate the data by cross-referencing databases
REaDOnline is the Data Management Platform from REaD Group. Our platform helps businesses easily manage and enhance their data. Combining the most accurate and comprehensive data available in the UK, REaDOnline cleans and enhances data in a few simple steps.
Simply register for an account and login to the REaDOnline portal. From there, upload your data to get started.
Have a question?
Have a question before getting started? Get in touch with our team, who will be happy to help you with the right advice.