4 Marketing Analytics Tools That Are Shaping the Industry

Radhika Sivadi

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Few marketers would admit to having “an excellent handle” on their analytics. But don’t blame it on the marketer.

Often marketing efforts are, by nature, hard to quantify in terms of dollars, revenue or impact. They tend to result in ghosts of impressions or whiffs of perception changes – or what we like to call “brand sentiment” – more than dollar signs.

But vague sentiment isn’t going to cut it for much longer.

CEOs are increasingly demanding more tangible and quantifiable metrics. In fact, in 2014 six in 10 professionals reported rising pressure from upper management to be more data-driven, with marketers feeling a majority of the heat.

As a result of rising demand, there’s been a swift emergence of tools, technologies and “scores” in the past year designed to help marketers measure their

Of the roughly $6.2 billion in deals in the marketing technology space that have occurred within the past four months, more than two-thirds come from funding, acquisitions, or mergers of businesses relating to intelligence and data.

Related: This Startup Wants to Revolutionize Search, One Data Set at a Time

Andreessen Horowitz has recognized the trend, too, and recently announced a $65 million round of funding for Mixpanel, a Silicon Valley Web analytics company.

These investors are ready for an avalanche of cash and contracts. And rightly so. The Wall Street Journal reported spending on marketing analytics is expected to nearly double over the next two years, from 7 percent to 12 percent, as marketers supersede CTOs as a business’s biggest IT spender.

However, because the industry is still rather nascent, the sheer number of companies and technologies flaunting their business intelligence solutions can inundate the digital marketer looking to implement a technology. Despite the feverish efforts to invest in marketing analytics, the lay-marketer is still struggling to get a grasp on which metrics to track.

They’re searching for answers to their questions, like:

  • Which analytics should you track?
  • How do technologies differ?
  • What’s available on the market?
  • How do these technologies integrate with my current marketing technologies?

To help sort through the chaos, here’s a quick look at the some of the most powerful tools in marketing analytics.

Measuring the effectiveness of your website

Marketing analytics start where anything starts: at the beginning, at the foundation. A proper marketing operation ready to track revenue impact contains four elements: a solid marketing automation software, a robust CRM system, a content marketing production space and a web presence tracking tool like Mixpanel.

Related: For Your Marketing Efforts to Succeed, You Need to Overcome These 3 Hurdles

Mixpanel tracks comprehensive user behavior to give companies a detailed look into what users are doing on web and mobile properties, or how much time they are spending within an application. The data, which can be sliced, diced or julienned to a business’s liking, illuminates interesting patterns like: How and where web users congregate, which buttons get pushed most frequently or usage rates for certain features.

The data is also extremely powerful for marketers. By using multifactor analysis, for instance, you could compare retention rates for users based on the marketing campaign that “brought them in” to see which ones resulted in the most valuable long-term customers.

Measuring the impact of your content marketing

The next step is to use technology to tie revenue to individual pieces of content. Kapost’s Content Scoring can help with this task. (Disclosure, I work for this company.)

Content Scoring takes a granular look at the effects of singular marketing deliverables to revenue. It could tell you, for example, the amount of revenue a single tweet or blog post contributed to the business as a whole.

The process uses marketing automation and CRM data to track successful customer “journeys” to identify the various content pieces they interacted with before committing to a purchase. It then attributes a relative percentage of the total revenue driven by that customer to the individual pieces of content (think: blog posts, whitepapers, eBooks, and social media posts).

In this way people can look at what singular component, or asset “type” is really resonating with audiences.

Related: A Data-Driven Reality Check for Your Marketing

Marketing ROI planning

Don’t forget to plan your reporting.

Marketing Evolution is an example of technology that helps marketers create ROI plans while leveraging big data.

“Big data creates a smog of numbers, and knowing how to tap into the right big data will define the differences between businesses that excel and businesses that choke,” says Rex Briggs, a bestselling author and founder of Marketing Evolution.“Big data is actually the confluence of three forces: real-time data, big data, and automation. Taken together, the change is the ability to discover, in real-time, which messages are working best with which people, in which context, in which media, and optimize accordingly.”

Predictive lead scoring and predictive conversion rates

The most nascent – but arguably the most powerful – marketing analytics tool is predictive modeling. Predictive modeling takes conventional data kept by marketers and CMOs, compiles it and crunches it to reveal patterns that confidently predict future buyer behavior. Predictive analytics allow marketers to more concretely assess what messages or content they should be creating in order to optimize their revenue potential.

Lattice Engines is a great example. one of the best examples. Used by VMWare, DocuSign, and PayPal, Lattice Engines delivers predictive apps that help marketers cut the production of crap and focus on the money makers.

“(Our clients) are looking for ways to identify the likelihood of future events and determine the best course of action based on that information,” says Amanda Maksymiw, a content marketing manager at Lattice Engines. “At a time when marketing is being measured more directly against top-line revenues, it’s critical to predict what prospects are likely to do next.”

Related: Marketers Now Need to Think Data First

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Radhika Sivadi