Using big data in your inbound marketing strategy

Are you using big data already? If not, don’t worry. Big data isn’t meant to put you off. Instead, big data can provide you with a wealth of information for improving decisions and your inbound marketing efforts. We’ll cover what big data is and how you can use it to help your business grow.

What is big data?

What is big data

You may be inclined to think big data is simply a large amount of data. While that may be true to some extent, big data is much more than simply a load of data. Typically, big data contains large and complex data sets that your everyday data processing software just cannot manage.

That is because the data sets you obtain are so voluminous that trying to process and analyse such large data sets would be a mountainous task. The volume of data is so large and complex that traditional data processing methods simply cannot process or store big data.

Unlike traditional sets, big data contains a much greater variety of data which continues to grow in volume and velocity (especially from newer data sources). These points are often referred to as the 3 Vs of big data:

  • Volume – big data will often involve processing large volumes of data that are usually unstructured and low-density meaning there could be lots of hidden gems of information. Given how much data is created every day, it’s unsurprising that big data can often contain terabytes of data on storage devices. If you take a moment to ponder about all the digital information out there, from social media updates to personal information such as bank details, there’s more than anyone would care to consider.
  • Velocity – refers to how quickly data is collected or generated alongside how quickly it takes to move or turnover analysing and processing the data. Big data that is meaninglessly collected onto storage devices won’t help you any, you need to try and analyse and interpret the data you collect to reap the rewards.
  • Variety – collected data can come from a variety of different sources, meaning big data has a wide scope leading to a diverse collection of data types. However, different sources of data also lead to a variation in the value of such data. Not all data will hold the same value or usefulness to decision-making. Sometimes, it could be like searching for a needle in a haystack! It may take some time to find something of value, but persevere and it could well be worthwhile.

Big data can also sometimes involve two other Vs – these are veracity and value. Veracity refers to the accuracy and quality of the collected data while value is what you gain and take from the insights gained from your big data.

The 3 types of big data

Just like there are 3 Vs of big data, there are also 3 types of big data: structured, unstructured, and semi-structured. We’ll go through each of these in a little more detail…

Structured data

Structured data is like it sounds, data that is organised or structured based on certain set parameters. You may have already heard of it before, but structured query language (SQL) is the programming language for managing structured data.

As structured data is also somewhat organised, it makes it much easier for establishing trends or discovering variables. Structured data includes numerical quantifiable data (or quantitative data), which makes it much quicker and easier to collect and process.

Structured data has been around a lot longer, meaning it’s more universally accessible. Many businesses will rely on structured data due to how easily data can be accessed, analysed, and interpreted. However, structure data lacks flexibility and can only be used for an intended purpose.

Unstructured data

Unstructured data, as you may have guessed, is the opposite of structured data. Conventional methods cannot process and analyse unstructured data as it has no assigned numerical value. That’s because unstructured is typically qualitative data. Instead, unstructured data consists of text-based information.

If you want to work with unstructured data, you’ll need to try and interpret the data into a form of structured data depending on your data requirements. Context plays a crucial role when translating unstructured data. Without context, any takings from your data will be meaningless.

Semi-structured data

Semi-structured data is the middle-of-the-road type of data. In most cases, semi-structured data refers to unstructured data with structured data attached. For example, metadata associated with an image (such as the date and time it was created) would be structured data whereas the pixels formulating the image would be unstructured data.

Semi-structured data is considered to be much easier to store compared to unstructured data yet more complex compared to structured data. With the metadata associated with unstructured data, there is much more scope for analysing data than without.

Even this blog you are reading right now is a form of semi-structured data. In the vast amounts of data and information Google has to process when delivering search results, how can it tell them all apart? The metadata associated with each webpage (such as headings, featured snippets, and alt-image text) helps in differentiating the vast amounts of information online.

What are the benefits of using big data in inbound marketing?

Benefits of big data

You’ve uncovered what big data is, but you have not yet discovered how it can benefit you. Big data can transform your business intelligence for much better decision-making. If you want to maximise your business’s potential, you’ll need to make big data an essential part of your business. Here’s why:

You can use it to better understand your customers

If you are collecting data on your customers, you have a wealth of information that can help you to better understand your customers. If the likes of Netflix and Amazon are already doing this, why shouldn’t you?

By better understanding your customers, you can provide them with even more relevant content, experiences, and solutions to their problems. Not only that, but big data is a great way for you to improve your processes for your customers.

Understanding your customers is one of the biggest advantages you get to give yourself. Knowing their needs and what matters most to them will help set you up for success. It will be a great way for building long and meaningful relationships with your customers.

Attract and retain customers

You can gather a lot about your customers from their digital footprint. Like footprints in the sand, you can find out exactly what your customers’ preferences and needs are, what they’re purchasing behaviour is like, and the problems or pain points they are facing.

Many businesses already use big data to help attract and retain customers. Whether it’s providing exclusive offers based on regular purchasing habits or providing recommendations for new products based on your previous purchases, it happens all the time.

Keeping afloat with data about your customers is an essential step to building strong customer satisfaction, loyalty, and a boost in revenue. Lovely! With a much better ability to target customers and campaigns as well, you can continue delighting and exceeding customer expectations.

Using big data helps you to save

You may be surprised to find that making effective use of big data can help to cut down your expenses. Being able to understand how you can improve and streamline processes while still obtaining the same result will help you to cut costs and improve efficiency.

From increases in productivity, better customer service or simplifying supplier and distribution networks, you can gain a lot of insights into how to more effectively and efficiently improve and streamline your process to help you save in the long run.

How can you use big data in your inbound marketing strategy?

Using big data in your inbound marketing strategy

If you’re not yet using big data and are convinced of its worth, now may be a good time to start using it in your inbound marketing strategy. The only problem is knowing how to start. Don’t worry, we’ll get you on the right track!

Lead generation

You can use big data to gauge a lot of information that is beneficial for lead generation. Through analysing big data, you could uncover details about what your customers are searching for, the challenges they face, and the factors at play which caused them to seek out your solution.

What makes your big data even better for lead generation though is combining it with your buyer personas. The two go very well together in helping you to create the right messages and strategies that will appeal to the right person and at the right time.

In turn, you could develop your buyer personas through the information you obtain via big data. The intelligence you can gain from big data can provide specific insights into who your customers are and how they interact.

Retention

If you spend so much time and energy trying to attract customers, it seems a waste to lose them afterwards. If you have a low customer lifetime value or struggle to retain customers after a purchase, big data could help you find the answer.

With a wealth of data at your fingertips, you could discover how customers interact on your site and the actions they may take after purchase. From there, you could develop content that will keep your customers delighted post-purchase.

From improving customer support to providing exclusive offers and product upgrades, you can continue to find ways to retain your customers and continue to buy from you in the future. Data from purchasing history, interactions, and reviews or feedback are all forms of data to drive retention.

Discover new opportunities

You can use big data to uncover new and exciting directions to take your marketing strategy. Identifying new opportunities will help you to continue to provide fresh and innovative solutions that will help to build long-lasting and trusting relationships with customers.

Whether it’s discovering previously untapped keywords for your SEO strategy that are driving traffic or finding new ways to reach your customers, big data could provide you with lots of new opportunities to improve and grow your inbound marketing campaigns.

Develop content that leads down the funnel

Inbound marketing is all about delivering the right message, to the right person, at the right time. Whether you are attracting or nurturing leads, you need to continue developing content that will help lead customers down the funnel and along every stage of the buyer’s journey.

Big data can help you to understand how your leads are interacting and engaging with your content, and most importantly, which content is performing better at generating a return on investment (ROI).

Through big data, you can establish a clear picture of which campaigns are successful and unsuccessful, and what draws your prospects and leads further down the funnel. Understanding these insights will allow you to create better workflows that can help to deliver content that resonates better.

The problems of big data in inbound marketing

Problems of using big data

Unfortunately, nothing is ever clear-cut. While you can benefit hugely from big data, there come some problems and challenges too. Being aware of these challenges, and how you can overcome them will stand you in good stead for success.

Focus your big data

Given that big data can encompass anything, you’ll need to begin by limiting what data you use for marketing purposes. Any data relating to your customers is essential. You may also find financial data and operational data could be beneficial. These types of data can help you measure your performance and improve processes.

Gaining the right data in the first place is the most important step. Without the right data, your results won’t provide many (if any) meaningful insights. The data you obtain also needs to be organised in a way that aids analysis.

Too much data

Big data continues to grow and change every single day. The longer you continue to collect big data without analysing it will lead to bigger problems further down the line. Not only does it become much harder to sort and analyse, but it could also leave you with lots of outdated data.

Keeping on top of the data you collect and analyse in real time will help to alleviate one of the biggest challenges of big data. Creating a method that allows you to analyse and translate collected data will help immensely in gaining useful insights.

Translating your data into success

Collecting and analysing data is one thing but turning your data into success is another. Even though you may have set up the processes for collecting, sorting, and analysing big data, there is still the problem of acting on the insights you gain.

You may have the power to help improve your business and marketing, but you fail to successfully implement the changes or don’t achieve the results you were expecting. To ensure you can effectively translate data in success, make sure that:

  • The data you use is accurate and up to date
  • Experiment to see which methods work better
  • Make sure your data sets are configured correctly so you can easily understand the data
  • Set benchmarks for your marketing in the future
  • Split customer data into segments
  • Develop your strategies with ‘why’ at the forefront
  • Know what trends in your data mean
  • Use your big data to help achieve your marketing and business goals

Big data can be daunting to begin with but taking the time to carefully understand and develop an effective process will prove fruitful. With the great benefits and insights you can gain from an effective big data strategy, you’ll be able to help grow and improve your inbound marketing strategy so it keeps attracting, engaging, and delighting customers!