Big Data and Marketing: Implementation Examples

Today, we want to take a closer look at how companies are using big data for marketing. The truth is, nowadays, big data and marketing are two inseparable disciplines. In fact, big data plays such an important role in marketing, and there are many different tools that help you manage your marketing big data in order to keep your efforts on track. Why is big data in marketing so important today? And how companies are using big data for marketing purposes? Let’s find out!

First of all, let’s talk about why big data and marketing are connected so tightly. We have indicated four major reasons:

Using big data for marketing: Why?

Generally speaking, big data offers priceless knowledge that improves your marketing campaigns and allows to reach your target audience effectively. How can this knowledge be used?

Big data in marketing: cost reduction

Everyone who runs online marketing campaigns knows that, when not optimized correctly, they can be bottomless pits. That’s why every decent marketer does whatever they can to optimize campaigns and gain more knowledge about their target audiences and how they respond to communication. And this is where big data analytics steps into play.

With this service, you can find valuable insight regarding your campaigns and customers. For instance, you can uncover essential trends or patterns, and that frequently leads to finding new solutions and discovering new approaches that help you save money.

Let’s say you run an online store, and you decide to implement big data analytics. After conducting some research, you may find out that some of your products are not attractive to your customers, and they simply take up valuable space in your warehouse.

This insight can cause you to stop ordering these items and, as a result, save money. And yes, we’ve done some simplification here, but, in essence, this is how big data in marketing works. It helps you find patterns in data you already possess, analyze them, and, as a result, draw useful conclusions, that will lead you to better decisions and, most likely, some savings as well.

Big data and marketing: increase sales

As you probably know, big data does not have to be limited just to your customer base or website. There are many publicly available sources and reports that help you understand the market and your customers. For example, there are open-source analytic tools such as Google Analytics that help you measure traffic on your website and assess how customers are responding to your ads.

This way, you can get to know your target audience in a better, more insightful way. You can see what the specific characteristics of people who buy your products or order your services are. With this knowledge, you can introduce changes and adjustments that will improve your:

• Website content
• Offer
• Promotions and special offers
• Ads and marketing campaigns

As a result, you’ll be able to increase sales and find many new customers.

Big data in marketing improves the decision-making process

This application is particularly interesting when you run a small company. In such organizations, frequently, the decision-making process is not based on reliable, verifiable sources, but on the manager’s intuition or experience. With big data in marketing, you can take your decision-making process to the next level. Online website monitoring and price monitoring tools help you get more feedback from the market and make more informed decisions.

This is especially important when it comes to aspects that are not zero-one, and more than one solution can be correct.

Big data builds competitive advantage

The last point on our list is, in fact, a combination of the previous three. With properly set prices, in-depth analysis of your customers and the market, and optimized online marketing campaigns, you can easily build a competitive advantage and grow sales.

Soon, all of your competitors will be using this approach to get more customers and enhance their offers.

It’s all just a matter of time. But you are in a privileged position. You already know that big data and marketing is a marriage made in heaven. Now it’s time to act. All of that we’ve talked about so far is at hand! All you need is a reliable big data analytics company that will help you make the most of big data in marketing.

Big data and marketing implementation: Tools

When it comes to using big data in marketing, we simply have to mention one of our favorite tools–Google Analytics. Why are we such huge fans of this solution? Because it’s a starting point for every big data in marketing activity. And it’s free to use!

Big data in marketing: Google Analytics

Google Analytics is a web analytics platform that’s based on big data in marketing. Google Analytics provides statistics and basic analytical tools for website optimization, Search Engine Optimization (SEO), and other online marketing purposes. Google Analytics comprises many fascinating features that help you run better online campaigns, for example:

• Data visualization tools, including a dashboard, scorecards, and motion charts, which help you understand what happens with your website’s performance and campaigns
• Segmentation that’s useful for analysis of conversions
• The advanced reporting module, so that you can easily obtain all the information you need
• Integration with other Google products, with Google Ads at the forefront

But the possibilities of Google Analytics go even further! Thanks to the advanced machine learning algorithm, Google offers so-called Analytics Intelligence. An intelligent module that helps you model conversions and build effective target audiences. This ML-based module can even answer your questions regarding conducted campaigns and other activities!

For example, you can ask, which channel had the highest conversion rate in the past month? And Analytics Intelligence will provide you with an accurate answer! With this knowledge, you can quickly assess which channels and tools are the most effective and focus on them.

Big data in marketing: Microsoft Power BI

We wanted to show you this tool, primarily because even non-technical business users can get vital insights using it. Power BI can be used for aggregating, analyzing, visualizing, and sharing marketing data. With Power BI, you can get quick, in-depth answers to vital business and marketing questions and analyze data you possess.
Naturally, there are many more tools devised for using big data for marketing. And, in general, these tools can be divided into three major categories:

• Data integration and preparation tools
• Data quality tools
• Data governance tools

Each category has a different purpose and characteristics. Today, to make everything a bit easier, some of the more advanced tools can combine characteristics of two or even three categories. And there’s also a separate category of business intelligence tools. It’s another subject strictly connected to big data.

Read more about them here. In this article, we’ve also shown you our Addepto Dashboard. It’s a great, versatile tool that’s used to visualize marketing big data of our clients.

Data integration and preparation tools

These tools are designed to gather data from multiple sources and combine it in one, easily-accessible location. At this point, we should add that the data integration apps are also utilized in the ETL process, which is an inseparable part of storing data in data warehouses, but again, that’s a different story.

Data preparation tools help you clean and prepare your data for further processing. Some examples of data integration/preparation software are CloverETL, Talend Open Studio, Microsoft Power BI, and DataWatch.

Data quality tools

The main role of data quality tools is to remove possible formatting errors, typos, redundancies, and other problems with data that adversely affect its quality. If you are looking for data quality tools, check out these: Cloudingo, Data Ladder, Informatica Master Data Management.

Data governance tools

Big data governance tools help you utilize big data in your company efficiently and responsibly. These tools also frequently help you keep data integrity and security (we will talk a lot about big data security in the next blog post). If you are interested in data governance, you should check out these tools: Xplenty, Collibra, IBM Data Governance, Talend.

Big data in marketing: Continuous Intelligence (CI)

Less than a year ago, we published a blog post with big data trends for 2020 and the following years. It’s still a vital source of knowledge; we advise you to take a look at it! One of the trends we mentioned in that article was CI–Continuous Intelligence. We want to talk about it here as well because CI can play a significant role in big data in marketing, as it’s an excellent way to improve the decision-making process in your company.

CI integrates real-time analytics with business operations. CI applications and algorithms can process historical and current data to support the decision-making process. CI is based on another modern technology called augmented analytics. Although we are still in the initial stage of CI’s development, we can already say that shortly, CI will be essential support in:

• Providing more effective customer support
• Designing special offers and discounts tailored to each customer’s need and expectations

The consulting company Gartner predicts that over 50% of new business systems will be using CI by the end of 2022[1].

Using big data for marketing: Real-life examples

Now the part you’ve all been waiting for! We want to show you six examples of companies (typically worldwide corporations) that utilize big data in marketing. When it was possible, we also gathered the results these companies obtain thanks to this data-driven approach. Let’s take a look:

Evolv/Cornerstone[2]

This company helps large global corporations make better HR and management decisions through predictive analytics. Interestingly, Cornerstone (formerly Evolv) takes over 500 million data points and sources into consideration, i.a. gas prices, unemployment rates, and social media usage. They use these insights to help clients cut attrition, and predict when an employee is most likely to leave their job. And the fact is, they are very effective–Evolv’s sales grew 150% within just a year, from Q3 2012 to Q3 2013!

Amazon

Just like Facebook and Google, Amazon possesses unimaginable amounts of customer information. Current estimations are they have over 300 million active customers. And they know a lot about their shopping habits. And just like Facebook and Google, Amazon decided to make good use of this data and started to offer Amazon Advertising. With Amazon Advertising, you can target them to specific demographic groups, including past purchasers. It’s a straightforward yet accurate example of how big data in marketing can be used to grow sales and expand your offer.

Nestle

For starters, Nestle started to collect customer data for their Petfinder.com website. Next, they implemented a behavioral scoring engine made by Lytics CDP that helped them identify highly engaged customers and have been recently looking for young dogs. This approach led them to find the highly-qualified buyers who they could target with personalized messages about adoptions and their products. The results? A 300% increase in the conversion rate and a whopping 90% decrease in the cost-per-acquisition rate. Without a doubt, big data in marketing help you save money!

Netflix

It’s one of our favorite examples, perhaps because we simply like Netflix 🙂 Anyhow, Netflix is famous for their intelligent recommendation engine that’s based on their customer big data. With this engine, they can propose other movies and series to their customers, engaging them into more interactions with this streaming platform. And such an approach produces some solid results!

Neil Hunt, Netflix’s Chief Product Officer, said that “the combined effect of personalization and recommendations save us more than $1B per year.”[3] Why? It’s actually quite simple. As Netflix estimates, customers are usually willing to look for more shows and movies only for 90 seconds. This means they have just 1.5 minutes to grab a subscriber’s attention. Otherwise, the risk of departing this platform increases.

That’s why they need a flawless product recommendation engine to keep their regular customers with them.

Airbnb

Airbnb uses big data i.a. to tailor the search experience demographically. They found out in 2014 that users from some Asian countries tended to have a high bounce rate when visiting AirBnb’s homepage. By analyzing the data further, they discovered that the reason was these users clicked the “Neighborhood” link, started browsing photos, and then never come back to book a place. Airbnb decided to replace these links with the top traveling destinations in Asian countries, primarily China, Japan, South Korea, and Singapore. The result? 10% increase in conversions. And yes, 10% may doesn’t sound like much, but think that it was possible by just one slight change on AirBnb’s website![4]

Coca-Cola

Their goal was to strengthen data strategy by creating a digital-led loyalty program. Coca-Cola fully realizes that data plays a critical role in modern marketing and product development. For starters, they use big data to understand what customers think about their brand.

As Justin de Graaf, Coca-Cola’s Director of Data Strategy and Precision Marketing, said in an interview: “that allows us to hear their voice and adjust our approach”. But it doesn’t end here. They also use marketing big data to focus on creating advertising content that speaks differently to different audiences.

That’s why Coca-Cola is active both in music and sports activities–to reach different customer groups effectively. Coca-Cola believes that branded content should be aligned with people’s passions[5].

Moreover, Coca-Cola has a separate bottling division. CCBC is Coca-Cola’s largest independent bottling partner. The company was struggling with manual reporting processes. These manual processes were quite a problem, as they restricted access to real-time sales and operations data. That was significantly slowing the company down. CCBC decided to use their big data insights.

The results? The team automated manual reporting processes. This has resulted in saving over 260 hours a year. The CCBC’s example shows that big data helps you with marketing, but also with other aspects of doing business. In fact, it’s a very versatile and comprehensive tool that’s simply designed to help you work better.

Addepto is an AI consulting company, and big data in marketing is one of our primary fields of interest. If you are interested in using big data in your company to speed up your development, drop us a line. We will gladly show you what your company can do to attract more customers, retain current ones, optimize marketing processes, and cut some costs. Big data in marketing will indeed allow you to reach new levels of growth. Find out how with us!

References

[1] URL: https://www.gartner.com/en/conferences/apac/data-analytics-india/gartner-insights/rn-top-10-data-analytics-trends/continuous-intelligence. Accessed Feb 22,2021.
[2] Rob Petersen. 37 Big Data Case Studies with Big Results. URL: https://businessesgrow.com/2016/12/06/big-data-case-studies/. Accessed Feb 22,2021. Fastcompany.com. How Evolv Is Arming Companies With Predictive Data On Employees. Aug 17,20214. URL: https://www.fastcompany.com/3034748/how-evolv-is-arming-companies-with-predictive-data-on-employees. Accessed Feb 22,2021.
[3] Nathan McAlone. Why Netflix thinks its personalized recommendation engine is worth $1 billion per year. Jun 14, 2016. URL: https://www.businessinsider.com/netflix-recommendation-engine-worth-1-billion-per-year-2016-6?IR=T. Accessed Feb 22,2021.
[4] Neil Patel. How Airbnb Uses Data Science to Improve Their Product and Marketing. URL: https://neilpatel.com/blog/how-airbnb-uses-data-science/?lang_geo=pl. Accessed Feb 22,2021.
[5] Alicia Tan. How Coca-Cola uses data to supercharge its superbrand status. Mar 20,2017. URL: https://www.adma.com.au/resources/how-coca-cola-uses-data-to-supercharge-its-superbrand-status . Accessed Feb 22,2021.