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Transparency in the Age of Big Data

Mary Ellen SlayterSeptember 1, 2017

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So many marketing agencies cite “transparency” as one of their core values, it’s become a truism, at this point. It is true that the rise of digital marketing has given us faster and easier access to real numbers than we ever even imagined before — and being able to share those with clients on the fly was a real game changer. But now we have a different issue: More data than we can wrap our minds around. AI and machine learning solutions are stepping in to help process all the data, but it still can be tough to know which numbers to pay attention to and which to ignore.

That promise of transparency becomes much more complex when it’s no longer a matter of just showing partners and clients “everything” — that’s an impossible promise in the world of big marketing data. Instead, we have to find a way to show the right data, in the right way, to present the most accurate, truthful picture of our work.

To find out how agencies are grappling with this issue, we reached out to Guillermo Ortiz, founder of Geek Powered Studios. Here’s what he had to say.

Transparency is one of your agency’s key values. What does that mean to you? What does it mean for your clients?

For me, transparency translates to radical honesty. It can seem counterintuitive to show vulnerability and be extremely open, but it helps build strong relationships and helps foster trust. Clients are busy and may not fully understand digital marketing, but having that foundation of trust helps them feel at ease. They have the confidence of knowing their agency is working hard on their accounts, and that their agencies has their company’s best interest at heart.

How do you think the volume of data available to marketers is changing how we work? In terms of both benefits and challenges?

I’m not sure who coined the phrase “data is the new oil,” but it’s 100 percent true. The biggest benefit we have is the ability to leverage information from so many sources to build campaigns that have incredible returns. The challenge lies in properly interpreting the data and not getting lost.

Many marketers are guilty of analysis paralysis, where we get stuck analyzing data for so long and fail to turn it into actionable insights. Facebook ads are a great example of this, as there are so many micro-targeting options and data available to advertisers, but many businesses are still failing to see any type of return at all.

What’s your advice for addressing those challenges?

The rise of AI is helping fight this information overload. Facebook is a great example of this, as their machine learning algorithm is helping to manage the campaigns to better meet campaign objectives and target your market.

AI will get smarter and will help us better understand the vast amounts of data available to us. Until that progresses further, marketers need to know what sources of data actually help inform decisions, versus the ones that are just noise. Unfortunately these change across advertising channels.

If you could only have one number in your marketing dashboard, what would it be?

ROI. This metric makes everyone happy.

In our experience, data and numbers don’t matter to clients if they aren’t making money. It’s best to focus on the overall spend and then work with the client to try to tie back actual sales to marketing efforts. We use call tracking to match inbound calls/forms to client sales. This helps clearly demonstrate ROI from specific keywords/campaigns.

Technology is rapidly advancing to help identify cross-device conversions and overall attribution but it still a big challenge right now. There are also many organizations like the Data & Marketing Association that are actively working to tackle multichannel attribution with the help of industry leaders.

Mary Ellen Slayter

Mary Ellen Slayter is CEO of Rep Cap, a B2B content marketing agency that she launched after working as a journalist at The Washington Post and SmartBrief. She has a master’s degree in journalism from the University of Maryland and a B.S. in agronomy from Louisiana State University.

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