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We’re studying marketing analytics at VB Insight and would love your input.

The speed and volume of customer data is on a storied rise. As the amount of data increases, the need to parse and predict future outcomes becomes increasingly important. Investors are betting big on analytics software to actually do something with the data to the amount of over $670 million in Q1 of 2015 alone.

We’ve found a growing need for marketers to truly understand what’s available to them today for data and analytics. So VB Insight developed an extensive study with nearly 1,000 participants so far using 800 tool providers.

If you work in marketing with a role in data analysis, take our survey and we’ll share the results with you.

We’re capturing significant user data on each of the categories for marketing analytics roles in the graphic below.

marketing analytics

The common thread that these diverse roles share is that the goal is the same: Get more customers, and keep more customers.

In a sense, figuring out what you know — what you know you don’t know, and what you don’t know that you don’t know — will help you get there.

What you know

You can only analyze what you can see. For most marketers using widely available tools (Google Analytics, for example), this means historical data. Customers generate data through their activity (visits, logins, Likes, transactions, and so on), which triggers a cascading series of events for the business. Many organizations have a version of this down pat, but we’re still finding laggards in industries like energy or B2B, where the transactional or “decision data” isn’t so cut and dried as buying a pair of shoes through a web browser or mobile device.

What you know you don’t know

These are the known, tough questions marketers and business leaders need to answer to stay relevant. “What’s our average customer lifetime value” is a common one. “How likely are future customers through X and Y acquisition channels likely to recommend us over competitors” is more challenging, and this is a more future decision-oriented question. Similar types of future-focused questions extend beyond marketing, with critical implications, such as “How likely is my top talent to leave to my competitors based on X, Y, and Z signals?”

What you don’t know you don’t know

This is the real meat to what’s possible with ‘solving’ for big data and by far the most challenging to address. What future consumer technology do we need to account for? How will wearables alter customer behaviors for our e-commerce channels? You can bet major retailers, retail sites, and payments companies are thinking hard about this one. And it’s really difficult to understand what signal data they should be scanning for to build these sorts of predictive models.

Taming data

Solving for big data in the marketing organization starts a positive feedback loop. For example, marketing insights can drive recommendations to the e-commerce team, figuring out shopping patterns that have predictive value moving forward. Understanding customer experiences at this level means better offers for the customer. Happy customers forking over their data that can actually be used in a meaningful context means better insights that inform product or strategy moving forward.

Everyone wins, right?

Well, most marketers just don’t see it that way yet. Either that, or they lack the skills or the tools — or both. It’s likely a combination of all three. And for many companies, the amount of data they have on their customers versus the amount of data they’re actually using is a huge gap.

For the most part, even at leading organizations, the majority of data analysts’ time is spent figuring out what’s already happened.

Marketing analytics

It’s important to note this is summary data. Across different categories of businesses, it looks drastically different. For instance, we’re finding positive correlations to marketing analytics organizations that are more future-focused and predictive as being more useful to their organization, and ultimately making the organization more successful.

In any event, many see marketing analytics as more than a box to check in the marketing process. Fifty-five percent view it as “very important” or “critical” to their company’s financial goals. Another 40 percent will spend “significantly more” on it in the following year.

We’ll be announcing the results of the study later in June at VB Insight.


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