The importance of data-driven marketing is at an all-time high in the current era, and 64% of marketing executives ‘strongly agree’ with that. With the ever-growing number of data points available, marketers now target consumers with a high degree of specificity. There is a wealth of opportunity with the use of data in marketing; however, it’s not as easy as it seems at first glance.
To create an effective campaign, marketers need to know exactly what types of data they can and cannot use for their marketing efforts.
Whether your company is just starting to create a data-driven marketing strategy or you want to streamline your efforts moving forward, this article helps you understand what data you can and can’t use in your next campaign. Read on to discover the different types of data and how they are implemented into your next plan of action.
We’ve divided this article into two portions: one for the data that you can’t use, and one for the data you can use. Not knowing the data you can use is like missing out on an opportunity you can take advantage of. On the other hand, using the data you can’t use is even worse than missing out on an opportunity. It can bring you some serious consequences.
To save you from those consequences, let’s first take you through the data you can’t use for creating marketing campaigns. If you’re using them, IMMEDIATELY take action to save yourself from anything bad.
What is data-driven marketing?
Before we get started, let’s define what data-driven marketing is. Data-driven marketing is the use of customer data to inform marketing decisions and strategies. This data can come from a variety of sources, including website activity, CRM systems, social media, surveys, and more.
Data-driven marketing allows marketers to be more strategic and efficient with their marketing efforts. By understanding who their customers are, what they want, and how they behave, marketers can create more targeted and personalized campaigns that are more likely to resonate with their audience.
8 types of data that are a ‘straight no’ to use in your marketing campaigns
1. Sensitive data that goes against privacy-first marketing
Marketers need to be aware of the sensitive nature of data and must follow privacy-first marketing when dealing with it. What is privacy-first marketing? It is the proper handling of data that you’ve collected as per data privacy principles.
Where do these data privacy principles come from? There are some national and international data privacy laws you’ve to follow. Go through the laws of your land and check if there are some laws you must respect. Even if there are no laws in the territory you operate from, you might have to follow the laws of other lands.
For instance, if you’re collecting data of any EU resident, you’ve to abide by the data privacy laws set by GDPR—one of the most stringent data privacy laws. There are certain pieces of data that are considered sensitive. This includes data such as financial information, contact numbers, voter registration information, religious affiliation, ethnic origin, and more.
You need to make sure that you are very careful when gathering and using it. If you fail to do that, you could face some serious consequences.
You could be charged with a hefty fine or even find yourself in court if you are not careful. In 2021, Amazon was fined a whopping €746 million for breaking GDPR laws. Therefore, you need to make sure that you are following the laws and that you are using the correct procedures when gathering and using sensitive data.
2. Incorrect data
Marketers often collect incorrect data. It can make you lose as much as 12% of your revenue.
Sometimes, it’s due to sloppy research, and other times, it’s due to the fact that you are trying to collect data that doesn’t exist.
Collecting incorrect data renders any data-driven marketing campaign useless.
You need to be extremely careful when collecting data, as there are a lot of ways that it can go wrong. If you are conducting a survey, make sure that you are following the correct protocol. If you are hosting a focus group, make sure that you are asking the right questions.
Sometimes, your most basic data-gathering procedures need to be reviewed and refined because they are the root cause of incorrect data. On top of that, you also need to make sure that you are not asking your respondents questions that they cannot answer. This often leads to incorrect data. If you are dealing with any kind of data that needs to be collected manually, you need to be extra careful with how you are collecting it.
Manual data entry is prone to mistakes. Make sure that you are entering the data correctly, and if you notice any mistakes, double-check all of your work.
3. Outdated data
One of the biggest marketing mistakes that you can make is to use data that is several years old.
It sounds like an obvious oversight, but it happens most of the time. Many marketers make the mistake of gathering data from a few years ago, publishing it, and then expecting the same ROI as they would if they were using data from the present day.
Outdated data can actually be worse than incorrect data, as it can mislead your customers, and it can be a complete waste of your time and money as well.
If you use data that is several years old, you might find that your audience has changed since then. Therefore, the data would be completely irrelevant to your current customers, and you would have to start over from scratch.
That would be a huge waste of time and money when if you had just used data that was more recent, you could have put that same effort towards creating more relevant marketing campaigns.
4. Irrelevant data
While incorrect and outdated data are bad, irrelevant data is even worse. Irrelevant data is data that is correct but doesn’t apply to your target audience. For example, let’s say that you are marketing a new app to gamers. You find that your average gamer is between the ages of 16 and 25, and that they are all male.
So you take that data and use it for your marketing campaign, expecting a high ROI. Unfortunately, you then find that your campaign needs to be geared toward parents who are looking for a new app to download for their children.
Wrong age group, wrong gender, and wrong type of person—these are all signs that your data is irrelevant, and you need to find new sources of data that are more suitable for your campaign.
5. Data from a source that cannot be verified
A source that cannot be verified is one that you don’t know where it came from or how accurate it actually is. You can’t verify the information and, therefore, you can’t know for certain if it’s accurate or if it’s relevant to your situation.
If you have data from a source that cannot be verified, it’s best to just toss it out. While it might be accurate and relevant, you have no way of knowing for sure. Don’t risk using poor-quality data in your marketing campaign. Doing so is harmful to your client’s experience and hurts your reputation as well.
6. Too general and vague data
Marketers often collect data that is too general and vague. You need to be very careful to avoid this because it renders the data useless. If your respondents are vague, there is nothing that you can do about it. There is no way to fix vague data.
However, you can avoid collecting this type of data by making sure that you are asking specific questions. Make sure that you are getting as detailed a response as possible from your respondents. Asking vague and general questions will yield vague and general answers.
7. Poor quality data
There are many ways that data can be poor quality. That’s why 72% of leading marketers are more likely to invest in the quality of the first-party data they collect. It could simply be that the respondents misunderstood the questions, or they didn’t understand the context of the survey. It could also be that you collected the data at the wrong time. Or, you used the wrong data collection method.
Regardless of what the reason is, the data you have collected is of poor quality, and you must not use it for creating your marketing campaigns. You need to correct this mistake immediately. Start by conducting a post-mortem on your data-gathering process.
8. Conflicting data
The last thing that you want to see in your data is conflicting data. Conflicting data is data that contradicts itself. This causes problems for marketers who are trying to make sense of their data and draw conclusions based on it.
For example, let’s say that you are trying to create a buyer persona based on some data that you have gathered. You have found that your data has conflicting information and that it is impossible to draw any conclusions based on it.
You must simply start over and gather more data, without wasting time inferring it, if you find that you are dealing with conflicting information. Unfortunately, this is something that every marketer has to deal with at some point, but you can reduce the risk of having conflicting data by being very careful about what you are gathering and verifying that it is correct.
8 data types you can use to build successful marketing campaigns
Now that you’ve known what data you can’t use, let’s take you through the data you can use to curate stellar marketing campaigns:
1. Demographic data
Demographic information refers to basic facts about a person’s life such as age, gender, education level, marital status, country of residence, and income level. This information helps you define your target audience and create content catered to their specific needs.
For example, if you run a tutoring service, you can target parents with school-aged children.
This demographic information helps you advertise your services to parents with school-age children. It also helps you create content tailored to this specific demographic. For example, you can create articles about “how to select the best tutoring service for your children based on your experience as a parent.”
2. Sales histories
This refers to all the sales data for a product or service over a set period of time.
This type of data is useful in creating marketing campaigns because it helps you identify which customers would be ideal for a new product you plan to launch, or which customers you should try to attract to a product that isn’t selling that well.
This data also helps you create marketing strategies based on geographical areas or customer segments. For example, let’s say you own a bakery. Sales history data could help you decide which product to sell next. If you discover that your chocolate cupcakes are the best-selling items, create a marketing campaign to attract more customers interested in buying chocolate cupcakes.
3. Customer service communications
Customer service communications are the interactions customers have with your representatives. For example, if you own a grocery store, and you have a section where customers ask questions, this information shows you how people are using your services.
The information helps you create a campaign that promotes the benefits of these services, or it also shows you where you need to improve your communication. If you’re facing customer complaints, let’s say about a product at your grocery store, pick up their pain points from their complaints. Try to address them and aim for fewer complaints about the same product next time.
4. Actions visitors took on your website
This data shows you which pages of your website are most popular, and which ones are least popular. Moreover, it also shows you what people are doing on each page and how long they spend there. For example, let’s say you sell fitness products. Track how long people spend on the pages of your website that discuss nutrition.
Then, create a marketing campaign aimed at people who spend a lot of time on those pages. If visitors spend more time on a page that discusses nutrition, a nutritional product can sell well on your website.
This data also helps you improve the user experience of your website. For instance, from the visitors’ actions on the payment page, if it seems that they’re facing difficulty paying for items they added to their cart, you need to improve your payment page.
Maybe you don’t offer enough payment options which frustrates your visitors and they eventually leave the cart abandoned. Or, maybe there’s some glitch on your payment page that results in unsuccessful payments from users’ end.
5. Completed customer surveys
If you have collected customer surveys in the past, you have data that you can use in your marketing efforts. This data is used to create marketing campaigns that target specific customers based on their survey answers.
For example, if you have collected surveys that indicate most of your customers want more information about a specific topic, create a marketing campaign that features information on that topic. This is an effective way to reach customers who have expressed an interest in your products and services and encourage them to purchase from you.
6. Behavioral data
Behavioral data refers to the actions your customers take on the internet, such as what websites they visit, what apps they use, and what products and services they buy. You can collect customer behavior data by tracking your customers’ online activities using cookies or some tracking software.
However, be sure to follow the data-privacy laws mentioned above in the article. As long as you’re not breaching any data privacy law, you’re good to go with behavioral data. Behavioral data is used to create marketing campaigns that target specific customers based on the activities they engage in online.
For example, if most of the people who visit one of your website pages also visit a specific competitor’s website, create a marketing campaign that encourages those customers to visit your website instead. Or, if most of the people who visit your website also use a specific app that offers features similar to yours, create a marketing campaign that encourages them to visit and use your website instead.
7. Geographic data
Geographic data refers to the location of your customers. Collect this data by tracking your customers’ locations, such as the city they live in or the state or country they are in. Geographic data is used to create marketing campaigns that target specific customers based on their location.
For example, if most of your customers are from a specific geographic location, create a marketing campaign that features information tailored to that area, such as the national language of that area, culture, and cuisine. This helps you reach more customers and encourage them to purchase from you.
Again, be sure to respect data privacy laws here as well.
8. Marketing effort and ROI data
The data relating to the amount of effort you have put into marketing campaigns and the resulting return on investment (ROI) can also be used in your future marketing efforts.
The data you can use includes:
- The amount of money you have spent on marketing campaigns
- The amount of time you have spent on marketing campaigns, and
- The results of those campaigns such as increased sales or more website traffic
Use this data to create future marketing campaigns that have lesser levels of effort and aim for higher ROI. For example, if you have spent a certain amount of money on a particular marketing campaign and it resulted in a certain amount of ROI, use that information to create marketing campaigns in the future that achieve more results with the least amount of effort.
Final thoughts on data-driven marketing
Marketers use data for a number of different purposes, but the type of data used and how it is collected make a huge difference.
Data is collected from a variety of sources but not all of that data can be used for data-driven marketing campaigns.
The key to using data for marketing purposes is to:
- Collect it with consent
- Use the right data collection procedures
- Collect it for a specific purpose, and
- Double-check & verify your work at the end
Now that you understand what data can be used and what can’t be used for your marketing efforts, start to put together a campaign that engages customers and potential buyers and make them purchase from you.
Frequently Asked Questions
What does a data-driven strategy look like?
A data-driven marketing strategy is one that relies on customer data to create and execute marketing campaigns. The goal of a data-driven marketing strategy is to use data to improve marketing campaigns and ultimately increase sales and ROI.
To create a data-driven marketing strategy, businesses first need to collect data from their customers. This data can be collected through a variety of methods, such as surveys, website cookies, and customer data platforms. Once businesses have this data, they can then perform data analysis to identify trends and patterns. From there, marketing teams can create targeted marketing campaigns that are more likely to result in sales.
What are some data-driven marketing channels?
There are a number of data-driven marketing channels that businesses can use to reach their target audiences:
– Social media platforms: Social media platforms, such as Facebook, Twitter, and LinkedIn, offer businesses a way to collect data about their customers. Businesses can use this data to create targeted marketing campaigns that reach the right people with the right message.
– Pay-per-click (PPC) advertising: PPC advertising is a type of online advertising that allows businesses to pay for ads that are shown to potential customers. PPC advertising is a data-driven marketing channel because businesses can use customer data, such as search terms and location, to target their ads.
– Display advertising: Display advertising is a type of online advertising that uses banner ads, videos, and other types of creative content to reach potential customers. Display advertising is a data-driven marketing channel because businesses can use customer data, such as demographics and interests, to target their ads.
– Email marketing: Email marketing is a type of direct marketing that uses marketing messages via email to reach potential customers. Email marketing is a data-driven marketing channel because businesses can use customer data, such as purchase history and email engagement, to target their messages.
What are some data-driven marketing tools?
There are a number of data-driven marketing tools that businesses and data scientists can use to collect and analyze customer data.
– Customer relationship management (CRM) tools: CRMs help businesses track and manage customer data and interactions. They can be used to segment customers, track customer behavior, and personalize marketing messages. Hubspot, for example, is a CRM that also offers marketing automation, sales, and customer service features.
– Analytics tools: Analytics tools help businesses track website traffic, online conversions, and other digital marketing metrics. They can be used to identify trends and optimize marketing campaigns. Some examples of analytics tools include Google Analytics, Adobe Analytics, and Mixpanel.
– A/B testing tools: A/B testing tools allow businesses to test different versions of their website or marketing materials to see which performs better with customers. This can be used to optimize website design, landing pages, email campaigns, and more. Some examples of A/B testing tools include Optimizely and VWO.