How to Data Driven Marketing

Data Driven Marketing No Data, No Sales

Large portals like Google, Facebook, Instagram, YouTube, Pinterest, TikTok, LinkedIn or XING are free. Of course, they offer additional services you can pay for additional services. But the platforms themselves are free to use. 

And why? Because you are the product! All those big platforms and others like Apple, Amazon or Netflix have mastered one thing in particular: how to collect and use data. The question now is how you too can use data for your business.

Why is data so important?

In this day and age, we generate an extremely large amount of data. Even cars generate a lot of data (source). The use of various platforms such as Google, Facebook, Amazon, Apple, Netflix, YouTube, Pinterest and other well-known social networks generates even more data. 

Those who master collecting and using data are particularly good at understanding their own customers, making them better offers and responding much more precisely to their needs.

So for us, the advertiser, data is also extremely important. Data can make the difference between a profitable and a highly profitable campaign. Because with it, you as an online marketer know exactly what specific customers prefer in a specific area, how they react to certain things and what they particularly like.

The special thing about digital marketing is that every visit to the website, every enquiry and every purchase can be precisely tracked and used for further marketing. The highlight is that every participant on the internet – including yourself – usually already have a lot of data that could be used.

What is data driven marketing?

Data is important because it can be used to achieve different goals particularly efficiently. There are different variations and levels of detail in the meaning and definition of data driven marketing. Basically, data driven marketing means that data is collected and used for marketing purposes. This should be used to understand the needs of potential customers, usually your own target group, to a much better extent. If this has been understood, these people can be addressed immediately or more easily and effectively in a second step.

The data can come from different areas. It can be structured – but also unstructured. This is all summarized under the now common technical term "big data". 

Benefits of Data Driven Marketing
The advantages of data driven marketing at a glance

However, big data is mostly used in larger companies like Amazon, Google and Netflix. Most smaller companies then use the "finished product" where the data has already been ordered, filtered and structured.

Using data driven marketing, it's possible to predict the future behavior of interested parties from the large numbers of data, interactions and engagements, purchasing behavior and other information. Or at least interpret it much better. 

It's important not only to collect the data, but also to evaluate and structure it correctly. Only when the data is properly structured and brought into shape can it be read and interpreted well. Each scenario may require different data.

Where can data be collected?

If you want to collect data for your own marketing, there are many different ways you can do it. The options vary depending on the size of your company.  

It doesn't matter if your options are limited or unlimited, you have to define a goal for why the data is needed. This will make collecting the data easier, help you form the structure and realize the opportunities you have with the data. Once the goal has been set and it's clear what the data is needed for, it's time to define the channels for collecting it.

Data Driven Marketing Channels
Numerous platforms collect data. You can also benefit from it, especially when it comes to social media. 

Buyer persona 

But before you start collecting data, you should create a buyer persona. Buyer personas are the image of ideal customers, also known as customer avatars. 

A buyer persona includes, among others, the following components:

  • Age
  • Gender
  • Education
  • Family status
  • Income
  • Difficulties
  • Needs
  • Wishes
  • Address

I recommend creating customer avatars in great detail and giving the persona a name and an image. The more detailed the research, the easier it will be for you to approach your ideal customers – regardless of the platform.

In the following sections, we'll look at different channels and what data for these channels actually means in practice.

Data in search engine optimization (SEO)

Search engine optimization is very important nowadays. In Germany, this is usually only understood as optimization for Google but SEO is more far-reaching. Nevertheless, we will still be focusing on Google in this section. 

What is search engine optimization (SEO)?

In SEO, you attempt to optimize your website so that it ranks at the top for the desired search terms and thus attracts more visitors organically. These visitors should then sign up for your newsletter, book an appointment or buy something directly from you. The reasons for carrying out SEO can thus vary.

When someone visits your website and navigates to further sub-pages, you can track this action – and much more. Of course, the website must be optimized so that visitors can find the website in the search engine and reach the website in the first place. 

There are a huge number of ranking factors, here is just a sample:

  • General functioning of the website, broken areas as well as links
  • Loading speed of the website (PageSpeed), this should be as low as possible
  • Ease of use and user experience (e.g. navigation)
  • Quality of the text
  • Number of links including link text

By using SEO tools, you can find out whether and where the website still needs to be optimized. You can find out what your competitors' websites look like, which links they have from which websites and much more. 

Using SEO tools can provide a lot of clarity and save a lot of (wrong) work. It's also important to analyze the behavior of users on the website. If the website has now been optimized and there are plenty of visitors on your site, it's good to know how they behave on the site itself.

Different tracking tools such as Google Analytics, Matomo and others can reveal a lot about the individual users as well as about the target group. 

The information you can collect includes:

  • Origin, location, region (country)
  • Resolution
  • Operating system and device used
  • Visited pages including actions
  • Total length of stay on the website
  • What page the user left the site from

If you use a heatmap tool, you can also analyze the scrolling behavior of visitors. This shows you how far users scroll down on the page, where they click and gives much more valuable information. Based on this information, you can further optimize your site.

I was able to optimize one of my landing pages using a heat map. It was clear that users were clicking on a field where they thought a button was – but there wasn't one. As a result, I made this place clickable and significantly increased my conversion as a result. 

Search engine advertising (SEA) and data

What is search engine advertising (SEA)

Data is extremely important when it comes to the big topic of search engine advertising. SEA involves different search terms that are used for the ad so that the target group searches for them and sees the ad.

Based on these search terms, different campaigns can be created with different content formats, headlines and descriptions. This can even be expanded further and the campaigns given corresponding images or videos. 

The exciting part, however, is that due to the different design of the advertisements, it's possible to address different users. A split test can be used to find out which target group, or which part of it, reacts how well to which type and variant of the advertisement. 

In a split test, only one component is changed and then tested. This helps you make the ad even better and more lucrative. The keyword may be the same, for example, but the headline, description and possibly even the image could be different. 

But you can not only improve and test the ad, you can try it with the landing page too. This enables you to create the best possible combination of ad and landing page to best speak to your visitors. 

There are really so many possibilities and combinations that can be tested. It wouldn't ever be possible to list them all in this article. One good take away is that you should carry out multiple tests to address your target group in an even more efficient way. Multiple tests can increase your profitability significantly.

You can also split the target group and create age groups, for example people aged 24-34, 35 -44, 45-54, etc. And test them against each other. You can do the same with married, single, divorced, single. Interests, educational attainment and many other criteria. 

Data Driven Marketing Split Testing
Split testing of different aspects, elements, interests, etc. can significantly increase the results.

This also allows you to split your ads and target your audience more precisely. You can see which group of people responds best to which ad and offer so you can optimize them further.

In a nutshell: by addressing the person again, it's possible to respond to them in a more targeted way. This ensures the price for a new enquiry (lead) or also for new customers can be reduced – sometimes even to a significant extent. 

Paid advertising on Facebook & Instagram

Data is enormously important, especially on social networks like Facebook and Instagram. The reason is quite simple: the people who use social media can be addressed much better because they reveal interests and a lot more about themselves. 

The right target group research, including interests and the corresponding images, videos, texts, headlines and language of the customers can decide the success or failure of a campaign. Of course, the corresponding landing page needs to be appropriate and reflect the message and words from the advertisement. 

The more precise the target group research, the tests, including the analyses and evaluations, the better the results will be for the respective marketing campaign. This effort will be reflected in the price per lead and thus also in the costs per new customer. 

It's important that every single step in the process can be tracked, however, so that you can trace exactly when a person clicked on the link, got to the landing page and signed up. 

All this information is very important for remarketing and target group expansion (Custom Audience and Lookalike Audience). Based on this data, you can do the following:

  • Tell the Facebook algorithm that you want more of these people to click on your website and visit the landing page.
  • Tell the Facebook algorithm that you would like to have more people who are more willing to book an appointment with you.

The same can be done if you want to reach more people who've interacted with your profile or your site. If you use a video for your ad, you can retarget those who've watched 90% of the video, for example. 

As you can see, you can use the data to find out more about your target group and customers and show them even more relevant offers. This is also how we work in our agency, DIVA Consulting, to achieve the results as quickly as possible and with highest quality, at the lowest possible lead and customer price. What's special is that we guarantee results – otherwise the service is free of charge.

Is it worth the effort?

You might already be thinking this all sounds like a huge effort and asking yourself whether it's worth it? Of course, you could just go ahead and select the interests of the supposedly known target group for the campaign. 

Any effort is relatively high – when you compare it to something else. Everything always has to be put into perspective. If you go at it running, you can very quickly burn through a lot of money. And that really can happen in the Pay Per Click (PPC) area.

That's why we believe the extra effort is definitely justified. The special thing about data is that it is brutally honest. A click through rate (CTR) of 3% and a conversion rate of 10% are exactly what they are. This data helps you figure out how much money you need to invest in ads to get X return on investment (ROI).

An example calculation

I'd like to show you the profitability of your effort and why it's justified using an example:

  • 100,000 impressions with a CPM (cost per 1,000 impressions) = €25 => €2,500 advertising budget
  • Of which 1% CTR = 1,000 people click on your website
  • Of these, 5% (= 50 people) sign up for a consultation
  • The completion rate in the interview is 20% and equates to 10 new customers.
  • Customer value = €2,500, so €25,000 in sales were generated and €2,500 in costs. This corresponds to an ROI of 10 and €22,500 profit after deducting advertising costs.

If we now optimize the ad and apply the following results:

  • 100,000 impressions with a CPM (cost per 1,000 impressions) = €25 => €2,500 advertising budget
  • Of which 3% CTR = 3,000 people click on your website
  • Of these, 15% (= 450 people) sign up for a consultation
  • The closing rate remains at 20%, which means 45 new customers were acquired.
  • Customer value = €2,500, so €112,500 in sales were generated and €2,500 euros in costs. This corresponds to an ROI of 45 and €109,000 remain after deducting advertising costs.

In the second example, €87,500 more turnover was made even though the other parameters remained the same. Only the landing page and ad including text, image / video contributed to the better results. If the budget were higher, higher sales would likely also be recorded.

The same is true for a better completion rate. Even if this example was created purely for this article, the figures show what prior analysis and optimization can achieve. You're invited to answer the question for yourself as to whether this effort is worth it.

Which tools should I use for data driven marketing?

Generally speaking, all the platforms offer good tools. For SEO, you can also use Google Analytics (or alternatively: Matomo) in addition to the Google Search Console. Other good SEO tools include Searchmetrics, Ryte and Sistrix. 

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For small sites and those just starting out, there are also free SEO tools that you can use for the beginning. For paid advertisements in search engines (SEA), Google Data Studio, Google Analytics as well as Google's Keyword Planner are particularly well-suited. 

For Facebook and Instagram Ads, you can also use Audience Insights and the Facebook Ad Library. These are good starting points for research and inspiration. It doesn't matter which platform you use, the tracking pixel and code need to be installed so that all actions are tracked accordingly and data is collected.

Conclusion: Efficient online marketing is not possible without good data

After all the information above, it should now be clear that no efficient online marketing is possible today without decent data. Paid advertisements are becoming more expensive and, at the same time, people are more and more immune to advertisements. People can quickly tell whether something is an ad when they see it.

For this reason, it's impossible to do without data and not make use of it. Of course, this can go much further with Big Data – but it would go too far at this point. Big data would mean that further information could be taken into account, such as hormonal changes in the influence of the weather, activities on weekends or holidays, etc. If you're interested in the topic of big data, I can recommend this film: Cambridge Analytica.

The fact is that data is incredibly important and you should definitely use it if you want to reach your target group and place lucrative ads. You must keep data protection in mind too, however. When you collect and analyze data extensively, it needs to be done in the appropriate way according to the GDPR. And if you don't do collect and analyze data, you're leaving behind a lot of untapped potential. 

As mentioned above, the collection, analysis and application of data could well go much further – as depicted in the film Cambridge Analytica. But a lot of people aren't even using the opportunities explained in this article yet. Why do you think that is? Is it ignorance, fear or laziness? It would certainly be an interesting question to research. Where do you stand on data driven marketing?

Do you have any other questions?

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