We are living in a great world. According to Internet Live Stats, there are over 3.7 billion internet users, over 1.2 billion websites, and close to 4 billion search queries on Google each and every day!
So who are these people? Well, the funny thing is: many companies know exactly, who these users are. Thanks to smart companies and engineers, we live in a hyperconnected world powered by thousands of servers with many aspects of our lives now dependent on this technology.
Not only you can find useful locations on a map, but as a business, you can use this map to let people know about your business. And as a user, you can find out about a certain fashion brand and its latest collection on Facebook - and other fashion businesses can advertise their products to you. And it does not stop at social networks. There are many other digital marketing channels that give us the possibility to precisely reach our target audience at a fraction of the cost of older and more traditional media outlets.
For many marketers and businesses, this is the basis of their success: creating appealing content, publishing it on different channels, adding a few paid ads to the mix, analyzing the results, and repeating. Sounds pretty easy, huh?
Many marketers only deal with a small handful of platforms, such as Google Adwords and Facebook, and are quite happy with the possibilities these native campaign managers offer.
But what if you want to dig deeper and add your display campaign data to your analysis? You may need to incorporate data from Adroll or Sizmek that is enriched with data from Meetrics. You may also have a number of local media deals and some PPC campaigns on your favorite product listing pages.
Moreover, we also have the possibility of adding TV data, outdoor performance data, and sales data from Nielsen into the mix – don’t let me get started with weather data.
So, you get the message. Before you know it, you might find yourself drowning in the sheer amount of data generated by these campaigns, unable to generate the best insights to optimize your campaigns and improve those all-important KPIs.
To conclude our introduction, we are living in great times where businesses are able to use the latest cutting-edge technology to reach customers more effectively than ever before. And if that in itself is not enough, you can harness the power of smart data to beat the competition, get the best possible return on your investment and finish top of the class.
Get ready to analyze your efforts and by learning from every step that you make.
We created this handy e-book to explain why marketing data is often fragmented and complicated to tame.
For one, you may have the feeling that pretty much everything about your day-to-day has become more overwhelming. And you’re likely going to be right.
Over the past years, businesses have expanded and diversified their marketing activities, leading them to adopt - and often master - a plethora of new tools and technologies. Today, marketing is about being creative and well-versed, just as much as it is about being able to collect and analyze tons and tons of data.
It’s no secret that the beauty of marketing data is its ability to be measured. As marketers branched out to more and more online platforms, the tools they used to measure their performance became more specialized. They can now track anything from social media and website activity to conversion rates and even sentiment. The more data, the better, right? Yes. And it also depends.
While a variety of analytics tools gets marketers a step closer to understanding the wants and needs of their customers, it also leads to data being collected in different places, and often, in different formats. It’s what we call marketing data fragmentation. In theory, social media data is great. Web analytics data is also great. But they’re truly powerful only when they are collected and analyzed in parallel, and when put in the context of your overall marketing performance.
Marketing analytics is what you need to really make things happen. Unlike tools that focus on individual channels, marketing analytics takes into account your activity across all those channels, and over time. It is your key to making informed and quick decisions when it matters the most.
Marketing analytics can help you find patterns. It can help you understand which of your marketing activities resonate with your customers, and focus on them - both in terms of time and resources spent. It is about determining the ROI of your marketing efforts.
While marketing analytics can help you get a clear focus on the past - how did your latest social media campaign perform, or how did customers respond to your latest product line - its main strength is in helping you derive insights, and perhaps even predict future trends.
What is even more important, however, is being able to use these insights and apply them to both your present and future marketing efforts. It is, thus, not just about ‘what and why it happened’, but also about ‘what will happen’ or ‘how can we make it happen’.
Marketing data, collected and analyzed in the past, can surely serve you in the long run, too. Once you know what customers want, need, buy and respond to, you can use analytics to foresee how they might react to any of your future marketing efforts.
After all, people are creatures of habit, and predicting (purchasing) behavior is not necessarily as difficult as it sounds. And if you can predict the outcome of even some of your marketing activities, then you’re already a step closer to achieving your business goals.
Data fragmentation may be the single, most pressing challenge for advertisers and marketing agencies today. And that’s understandable – after all, data is all around us. It is available in ever-growing amounts and is accumulated across a variety of platforms – from websites and blogs to TV and video, to social networks, email, and search. Ultimately, it ends up being overwhelmingly big, scattered, and messy.
Data fragmentation begins with your very first marketing efforts – or those of your clients. You launch several online campaigns, publish social media ads (perhaps print and TV ones, too), and you already have a large flow of data coming your way. What’s more, as soon as you want to take a closer look at how much you spend, what audience you reach, and how well, you need to start gathering the data from different platforms.
As a result, you get a number of different data sets – often referred to as silos – and the task is to make sense of them in the context of your overall marketing performance.
The problem with silos is that they provide no single overview of all available output and make it difficult to detect anomalies or irrelevancies in the data.
As marketing data grows in both size and diversity, it is becoming more and more difficult for advertisers and marketers to have the full picture at their fingertips. While not too long ago, it would have still been manageable to collect and structure data manually, today the sheer amounts of it make it almost impossible.
To have a clear overview of their overall marketing performance, professionals need to be able to overcome the constraints of data fragmentation. It is, therefore, crucial that marketing data is acquired in an automated way – not only to make sure it’s being gathered in its entirety but that it’s up to date at all times, too.
Solving the challenges of data fragmentation is essentially a combination of collecting all relevant data, making sense of it by stripping it of its various formats, and analyzing it in real time.
In other words, it is about creating a consistent target data schema, where all relevant information exists in one place and where it’s possible to assess its overall marketing significance.
The path to getting a coherent data schema is often different for different marketing and advertising agencies.
Yet, what’s important is that marketing is becoming increasingly specialized, requiring professionals to master ever more specialized techniques and approaches to managing and analyzing the data that comes their way.
It is about marketers and advertisers developing a deep understanding of how different technologies can help them reach their marketing goals in a coherent, quick, and cost-efficient manner.
It’s no secret, we all know it. So learning about what your customers really want, need, and are willing to spend their money on is somewhat of a main priority.
To get the best insights, you need to invest time and resources, especially when it comes to collecting and analyzing the right bits of information. As a marketer, you are likely swamped with tons of data already that, to the best of your knowledge, may be accurate, relevant, and insightful. But what if it isn’t - at least not entirely?
How can you be sure that there is no missing or incoherent data? Or what if there are blind spots and you don’t even know where to start looking for them? To be able to fully rely on your data, you need to make sure that you don’t compromise on its quality. After all, you generate and collect data to have a fact-based decision-making process, so you better make sure you have one!
The thing with marketing data is that, while two pieces of information may look similar or almost identical to the human eye, to a data analytics tool, they may be completely different. Even when they signify one and the same thing.
The most common confusion stems from having various time and date formats, as well as inconsistencies in the spelling of users’ names and addresses. Good-quality data makes sure there are no such inconsistencies - and that the insights are accurate, timely, and as complete as possible.
Before rushing to collect the data, you must decide what you want it to help you achieve. Just like the companies in the examples above, you must identify a clear goal for the data.
Why, because your objectives will guide your next steps. You’ll know what information to collect. Where to get it from. And also, what insights to look for.
Marketing data needs to be collected as close to its original source as possible to avoid it being processed multiple times along the way. The more detailed and specific the data, the more accurate it ends up being.
Timeliness is one of the most important characteristics of marketing data nowadays, mainly because of the speed with which information moves. Collecting and analyzing data in near-real time is what helps companies respond to their customers’ wants and needs quickly, and what eventually sets them apart from their competition.
Or at least as complete as possible. Collecting and analyzing data in its entirety is key to the success of your marketing activities. Any missing information, in turn, would only get you to make decisions based on educated
guesses instead of facts.
When you have the numbers, they need to be correct - or at least you should be notified if there was an error in the loading or transformation process. Making important decisions based on the wrong numbers can hurt, so you should also make sure to not only get but also pay close attention to the error reports.
Making the right business decisions and building strong relationships with your customers is something quality data contributes greatly to. But how do you get to the point where your data is of the necessary quality?
And it’s growing further and further in size. Investing in a sophisticated data analytics tool is, thus, not just a need anymore. It’s a must.
If you are to analyze your data in near-real time, you need to be able to collect it, clean it, and analyze it as it is being generated. A next-generation marketing analytics tool, especially one that operates in the cloud, can help you work with increasing amounts of data, stripping it of its various formats, harmonizing it, and making it ready for your analysis.
It is also crucial that the technology you choose can automatically detect possible discrepancies in your data and provide you with an integrated overview of it at any time. Imagine clean, ready-to-use data, with no blanks for you to fill in. As soon as you have that, you can focus on your business’s main objective - to identify and satisfy the exact wants and needs of your customers. After all, isn’t that what marketing is all about?
In a time when marketing specialists are facing larger amounts of data every day, they have yet to learn more about leveraging the full potential of marketing analytics. In fact, for many companies extracting useful information from the piles of marketing data they generate is still quite the challenge - especially when it comes to mapping out the wants and needs of their customers.
A 2016 report by IBM and Econsultancy sheds light on the fact that only 4% of companies have a frequently updated strategy in place for optimizing their customer journey, while 75% are either beginning to develop one or don’t have any at all.
It’s clear that many are still in the very early stages of embracing the potential of marketing data. And that will have to change soon.
Without a doubt, marketing data is the key to knowing your customers: what they look for, what they want, need, and what they’re willing to spend their money on. With their online activity, however, being scattered across various platforms and channels - anything from websites and blogs to social media, newsletters, and forums - so is the data they generate.
As a matter of fact, having to handle multichannel touchpoints is what slows many companies down. Only 3% of businesses have been able to fully integrate them, while 24% manage them entirely in silos. The remaining more than 70% of companies polled admitted to a certain degree of integration, though mainly channel-focused.
We have previously talked about silos, and we’re convinced of one thing: They must go. The problem is that silos prevent marketing professionals from having a single overview of their data, making it difficult to detect irrelevancies. The key to solving this is by breaking them down and having all output up to date, in one place, and shared among all relevant stakeholders.
It’s coming at you from a number of different channels and, in theory, you can use it to derive the most specific of insights about your customers. Well, in practice, too, as long as you have the right tools at hand.
Pulling data from its original source and turning it into actionable insights is a lengthy and often complex process. Especially, if you want to be able to analyze it in near-real time, you need to be able to collect it, clean and harmonize it, and process it as it is being generated.
Next-generation marketing analytics tools can help you with the first few steps of that process, leaving you with the task to analyze your (clean and normalized) data and transform it into value-generating insights.
Now, we have so far placed a strong emphasis on the need for marketers to work with quality data in order to understand their customers’ needs and respond effectively to them.
It is true, however, that being able to generate high-quality data is only half of a job well done. The other half is being able to interpret your data so that it creates long-term impact. You need to be able to provide real value to your customers. Makes sense, right? Yes, but it isn’t always that simple.
Creating value with your marketing data is about making several things happen at the same time: getting the right data in the hands of the right company stakeholders, at the right time, to drive the right decisions. At the end of the day, it’s about having clean and ready-to-use data as much as it is about having the right people pursuing the right objectives with it.
So break down those silos, get your marketing data flowing across your organization, and create the value that your customers are looking for!
