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Why Marketing, Product Teams Should Collaborate on Analytics

By Published on .

Credit: iStock

In the next three years, marketing departments will dedicate 22% of their budgets to analytics, yet companies still use less than one-third of their data to drive business decisions. Despite high hopes, analytics have yet to deliver on their promise.

Many marketers cite a lack of expertise as a primary reason why analytics aren't informing business decisions. While that may be part of the issue, a deeper problem lies in how the analytics industry has divided itself along marketing and product lines, and the way companies have organized their data in response.

In an effort to differentiate themselves in a crowded market, analytics providers are inadvertently encouraging siloed decision-making. Businesses, in turn, don't think of data as an opportunity for collaboration -- a misstep that's stunting big data's massive potential.

A branding problem
The market offers no shortage of analytics platforms developed specifically for marketers -- leaving other departments, like product development, stuck with ill-fitting solutions. In response, a handful of startups have emerged to fill the underserved market, branding themselves as providers of "product-based analysis" to help product teams succeed. In their positioning, these vendors reason that product managers deserve their own analysis systems, just as IT adopts specific solutions to manage servers or developers use particular tools to write code.

To analytics providers' credit -- Adobe for marketing, Mixpanel and Amplitude for product – it's smart branding to specialize in a single audience. Product managers and marketers each have their own set of priorities, customer attributes to examine and lexicons of industry-specific terms and acronyms. But in the next wave of customer data platforms, segmentation spells trouble that will only multiply over time.

All business departments share one big thing in common: the customer. Today's most successful companies are the ones that identify exactly what their customers want, and then deliver on those desires. That means when businesses let their analytics tools get stuck at the department level, they're missing out on a big opportunity. In fact, those companies are putting themselves at a severe disadvantage by failing to paint a full picture of what customers want and need.

Unify data, people
Data should bring business functions together rather than divide teams. The philosophy sounds simple, but implementing it is a different matter -- and many businesses don't in practice. All business roles and levels make decisions, and the best decisions are driven by customer data. That information must be standardized, self-serve and readily available to every person in every department, from product and customer service to marketing.

By running marketing and product data on separate platforms, companies face bigger problems than simple consistency issues. Marketing's analysis of a user begins with engagement, and ends at acquisition. The product team's analysis, however, starts with someone's purchase, then extends into customer support. But shouldn't marketing care about how their customer actually uses the tool? Shouldn't product know the type of experience a user expects before signing up?

Take digital advertising as one example of the dangers of separating marketing and product data. For an ecommerce brand, for instance, Facebook may convert customers, but lead to poor retention; Google Adwords might be more expensive, but drive engagement with customers who are in it for the long haul. You have no way of uncovering comparative insights -- such as the relative efficacy of ad platforms or the nuanced connections between acquisition and retention metrics -- without a unified analytics tool.

Imagine if marketing and product teams could share all information, arming themselves with maximum context on customer behavior. Teams not only make better, faster decisions within their own departments but collaborate more productively across business functions. In the process, they may discover insights they didn't know they needed. Companies that unify along both technological and cultural lines prove to be far more effective at serving customers in a world where customer experience must be nothing but flawless. The good news? With advancements in data collection and schematization, it's now possible for companies to keep customer data in a central, fully integrated, easy-to-access place.

As the number of digital channels and customer touch points proliferates, the question, "What are our customers doing and where?" becomes far more complex. From social media, to mobile browsing, to actions happening directly within your product, it's imperative to capture these interactions in a central repository under a common schema. That way, you can ask important, cross-cutting questions. The answers open powerful new ways of understanding behavior over the long term, enabling you to create meaningful experiences that continually entice customers to come back for more. That's a mission that every successful company has no choice but to embrace.

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