Marketers, you are sitting on a goldmine yet most of it is turning to rubbish. In this post I would like to discuss why marketers have to be mindful about what they do with their data, what is Data Capital, how to use it effectively and what are the main challenges they are facing. I would also like to share a basic framework of how we approach big-data questions in small steps and how we see successful b2b companies leverage it to outperform their competition.

Why Bother With Data?

Data holds the key to sustainable growth. In marketing, similar to the scientific world, innovation and growth stem directly from a continuous cycle of asking questions and critically analyzing the answers to generate insights. Insights can answer macro questions like what is the impact of your marketing, to supporting micro-level decisions like whether I should promote a certain post in a certain channel to a certain audience at a certain time.

Insights can emerge by combining data with context, and context comes from something much more elemental – asking questions. As firm believers in Evidence Based Marketing, we at TrenDemon are investing tremendous amounts of effort to build and better externalize content marketing insights and help our customers understand and grow their content marketing ROI. Although we’ve made significant progress, we are continuously striving, together with our customers, to provide clearer, more actionable insights. The paradox is that although we all are drowning in data, we still sometimes struggle to find a context to that data to give it meaning and use it to guide decision making. In the past, these problems were in the sole domain of Business Intelligence experts and technologies. Today, with big data all around us, marketers need better access not just to BI tools but also methodologies.

Asking the Right Questions

The Answer to the Great Question… Of Life, the Universe and Everything… Is… Forty-two, said Deep Thought, with infinite majesty and calm.

― Douglas Adams, The Hitchhiker’s Guide to the Galaxy

but what is the question?

These two ideas, of data and questions, have a unique relationship. They amplify each other and grow together – the deeper the questions, the deeper, more abstract the data you require and the new questions it raises. Before I lose you back to Facebook, let me assure you this is not just a theoretical post in praise of critical thinking and big data but an attempt at offering a pragmatic look at the role of data in b2b marketing, why companies cannot afford to waste their data capital, which questions can asked and how they data should be structured in order to be effective.

What is Data Capital? 

If data is all around us and so abundant, what makes it so important? Data, on its own, is useless. But when raw data is transformed into a meaningful structure, designed to provide answers and guide decisions, it becomes capital. As with other types of capital (financial, human), it is a finite precious resource that you can either leverage or waste. It holds the key to your company’s growth. Only with data capital can you truly understand your customers, where they come from, what are they interested in and why and where they disengage. Your data capital also holds prophetic powers – hidden in the patterns of your data are forecasts about what will happen next, to take an example from the b2b space, how many leads are expected to convert in the coming period.

B2b Companies with online presence, in all sizes, generate titanic amounts of data. A company’s website for example, creates data about who is coming to their site, what they are doing, reading, how they are behaving etc. The CRM creates and stores information about the company’s customers, their status, value, source, etc. But as we mentioned, data, without context, is meaningless. There are many ways to leverage this data automatically, for example, using real time personalization to optimize website performance, but in terms of transform data into meaningful insights, the first and crucial part is by simply asking questions.

Why Now?

Because it is still early in the game, and especially for startups looking to take down bigger competitors, better use of data can pack a powerful punch. Financial economist Andrew Lo, who is Charles E. and Susan T. Harris Professor of Finance at the MIT Sloan School of Management and director of the MIT Laboratory for Financial Engineering says: for most companies, data is their single biggest asset,”. But, he notes: “Many CEOs in the Fortune 500 don’t fully appreciate this fact.He also adds that “companies still don’t seem to understand that they’re sitting on a gold mine, and that if they ignore it, the gold mine can just turn into a trash heap.” (source)

Many companies are still not leveraging their data capital effectively but there’s always the risk your competitor is, beating you to better deals, growing faster and at lower costs.  

The Main Challenges – Data Quality and Structure

A recent Forrester study published on Forbes found that “Marketers most often face the two challenges of ensuring data quality and managing data from a variety of sources (both 47%) in attempting to gain greater insights about customers and prospects.” while “89% of marketers have predictive analytics on their roadmap” (source)

Forbes

Forbes

But besides not collecting it, there is another way you can waste your data – collecting it in a way that does not allow ask it meaningful questions. In computer science this is known as ‘garbage in – garbage out’.  Here are some examples we encounter with “corrupted data” in online marketing and content marketing:

No distinction between different sections in the site – this makes it impossible to compare the performance of various sections (like your resources section vs. the product features area). To fix this, make sure your different areas are easily identified through the URL.

No separation between people, sessions, goals and actions (all clustered together in groups) – can you connect a single journey to a goals? Can you see that breakdown by sessions, days, sources, events? The higher the abstraction of the data (feel free to geek out here), the easier it is to manipulate and compare different variables.

Lack of proper interface between the different systems in your technology stack – are your services (marketing automation, CRM, analytics, online tools) talking to each other or only to themselves? Make sure that the right interfaces exist and before implementing a new technology that can support your data capital, make sure it can communicate with your other systems.

This brings us back to the unique relationship between data and questions. Before you can tell if you are collecting garbage or gold, you first need to define the questions. Here’s the cycle we use at TrenDemon to leverage our data capital:

Step 1 – Ask Anything

Marketing data can be especially tricky since for it to be meaningful, you need to connect data from several sources, event types and platforms that would allow you to looking at it from several perspectives. But, it also hold great potential for creating unique insights that cannot be generated elsewhere. The only rule – there are no dumb questions. Break complex inquiries to bite-size questions.

For example, connecting marketing and sales data allows building a model which describes your customer’s’ online journey and which sources and touch points along that journey had the most influence. You can learn which topics customer are actually interested in and use this insight to predict conversions, guide content creation efforts and also future product offerings. Which sources are effective at exposing your offering to new audiences vs. which channels are more effective and returning an already exposed user.

 

Step 2 – Ensure your data is collected, structured in an accessible way, and can answer your questions

Asking The Right Questions

After you defined the questions, see if you can get those answers from your current data collection and analysis platforms (either through your analytics system, marketing automation or other solutions like TrenDemon).

Once you is the data structured in a way that can be queried to generate meaningful answers. For example, if I want to know how my website’s content area is performing in relation to other parts, we first need to define and tag those areas accordingly. In cases where the data is not organized or abstracted, it is very difficult to derive insights. Another example is if your goals are not well defined or the data is not readily available, it is impossible to determine the impact of sources or assets on those goals.  

Step 3 – Compile Answers from The Data and Form New Questions

The last part is where you can finally start identifying signals from noise. To help you navigate through the information you can use analytics tools. Whatever the answers will be, they will help you either pivot your efforts, optimize or double down on them. Some of the insights our customers discover when looking at their data is how many people are actually reading the content they spend so much time creating, how many of them continue on to become customers, which call to action perform best on which audience types and how sources that may seemed ineffective before when measured only against conversion rates, are now seen in whole new perspective when looking at their actual customer value.

Marketing Insights Process

Transforming Data into Data Capital

What Successful Companies Do Different with Data Capital?

As we are growing, we are lucky to work with more and more successful companies who understand the value of data capital. This offers a unique glimpse into their work processes, mostly in our space of online marketing and sales. Always searching for patterns in journeys, we also try and find similarities in how successful companies operate. Even in different verticals, business models and growth stages, one attribute stands above the rest – it is not just how much they spend, it’s how little they waste. Many companies are working hard to stop wasting money, but capital is only one type of resource that can wasted.

How Can TrenDemon Help you Access your marketing Data Capital?

One of the things we religiously obsess over here at TrenDemon is how to keep transforming the growing volumes and depths of data into more actionable insights. We know that the team which asks the right questions and reaches the right answers sooner, wins. We see first hand how successful marketers who leverage insights to action gain massive improvements on their business results. 

Over the past year we’ve been working on a completely new data architecture that not only allows asking deeper, more complex questions but also explore your data in a more accessible way to find overlooked opportunities. Some of those new abilities will be live in our upcoming dashboard update for all customers, some will be part of Sentinel, our new Marketing Business Insights offering. Sentinel helps explore patterns in the buyer journeys, and uses data visualization to better externalize insights. In our journey for better data capital extraction tools, we are also asking you, the marketers, to challenge us with all kinds of questions about your data. We believe BI and big data insights increase our joint knowledge base and should accessible to companies in all sizes.

Marketing Insights Navigator

As discussed above, data can be wasted or leveraged. What about your company? Make it your new year’s resolution to cut down on your capital data waste.  In our next post, we’ll explore how machine learning and AI is helping deal the big data challenge. If BI is aimed at helping you understand what happened, AI can help figure out what will happen next. We’ll share how we use deep learning in TrenDemon to provide predictive analytics and real-time personalization. Feel free to subscribe or get in touch with us to learn more on how you can transform your data into data capital. Good luck and have an awesome 2017!


About Avishai Sharon

CEO at TrenDemon. 16 years of developing and designing online products, some which also actually worked.