We like our data to lead to doing, not drowning, but with billions of data points swirling through our clients' software and spreadsheets in any given week, we know it's hard to suss out the what's meaningful and productive from what's simply distracting. Our CEO talked with BizReport's Kristen Knight to offer some data management insights from a career spent helping clients wring every last drop of utility from their data.

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Kristina: How can marketers distinguish between useful data and distractions?

Michael Lagoni, CEO & Founder: The value of data is almost always a matter of how it's interpreted and applied. Imagine you're tasked with running a digital campaign to drive net-new customers to convert; the temptation to start optimizing for a commonly reported metric like click-through rate (CTR) would be high, but given the campaign objective, CTR needs to connect to top-funnel metrics like incremental reach and bottom-funnel metrics like incremental sales to be a useful input to optimization.

When a marketer can use data to learn more about their current performance and inform future decision-making, utility is high. When a marketer is drinking data from the fire hose and treating all inputs as equals as they try to make sense of the past and succeed in the future, they're likely getting distracted from the main plot. We encourage our clients to work backwards from their objectives to clearly define their KPIs and input metrics, and then zero in on how and why those metrics are changing over time.

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Kristina: What consumer data indicators are marketers' best options to inform strategy and drive sales?

Michael: To accelerate sales and increase profitability, marketers should be tracking and optimizing performance across metrics through their e-commerce conversion funnel, from the words and phrases a consumer types into the search bar, to the ads and products they click and the purchases they make. Having a complete view of brand and product-level KPIs is also important in order to connect the dots between advertising spend, click traffic, product pricing, ratings and reviews, buy box performance and market share.

But of all the data points we help clients monitor each week, we tend to see the most upside when we focus on new keyword bidding opportunities in our clients' paid search campaigns. The search data we make available - including all the keywords driving clicks in a category and the CPCs brands pay to win them - helps marketers understand how to position products, update content, and tune ad spend to capitalize on demand.

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Kristina: What common mistakes do marketers tend to make when analyzing consumer behavior data? How can these be avoided?

Michael: We see some marketers get off track when they treat qualitative data as a primary source of truth. Panels, focus groups and surveys capture stated preferences that may or may not closely correlate to actual consumer behavior. A clear view of both the demonstrated action and the reported intent is more powerful than either data point alone.

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Kristina: How can marketers course correct when data leads them astray?

Michael: Part of the challenge of digital channels is that reality changes so quickly. Speed is your best friend when it comes to course-correcting a mistake, but the common wisdom still applies: sometimes you have to go slow to go fast. If you can make a quick-fix that doesn't cause downstream issues, go for it. But then take time to track down the cause of your data dilemma, particularly if it's causing an error that will compound as time passes (like outsized keyword bidding or faulty targeting).

Our advice is to first check your sources and determine if the problem is in your performance or in your reporting. If nothing changed in the way you or a third party partner is capturing and transmitting data, then review your interpretation. Did you alter a critical model? Are you tracking the right input and output metrics for your KPIs? Did you extrapolate beyond the predictive limits of the data? Try to locate the moment when your data drove you down an unproductive path.

The average digital marketer is trying to manage millions of data points every week, and it's hard to imagine a scenario where every data point is equally valid and equally useful. That's why decision-making in a data-flush environment can be hard. We encourage our clients to critically evaluate their data sources and find partners who can bring objectivity and experience to the big questions facing their business.

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