Marketing is data rich, but insight poor. As the number of ways to reach consumers proliferates, marketers are drowning in data. Each of our channel-specific execution teams and tools spit out huge volumes of data exhaust. We have business intelligence, data visualization, and data exploration tools. We have data scientists, data mining teams, and marketing analysts digging night and day. So, why are marketers sinking? Because the way we go about making sense of our data is all wrong.
But all we have to do is borrow a few pages from the data management playbook of our friends in finance. They, too, deal with very messy big data. (You should see the pile of receipts I bring home from a two-week tour of our European clients!) Finance long ago devised a few foundational practices that marketers would do well to emulate -- must emulate, in fact -- if we want credibility with the C-suite.
Marketers need to fundamentally change our approach to how we use our data to report on performance. For more reliable, useful, and flexible measurement and reporting, we can start by emulating these tried and true data management best practices:
A single system of record
The finance department doesn't let one person keep their receipts for company expenses in their desk drawer, another in their purse, and yet another in an Excel spreadsheet. To get reimbursed, our expenses (be they travel expenses or software purchase orders) must be logged in a single financial or expense tracking system. That gives the finance team instant visibility into aggregate and categorized spend -- and importantly, easy reporting. Marketers, on the other hand, let our data remain, well, everywhere. It's in Nielsen, Google AdWords, Omniture, DART, and scores of agency spreadsheets and slide decks stuck in our email inboxes. Following the lead of the finance department, only a single system of record will save us from the all-night cutting and pasting sessions we marketers routinely face when cobbling together our reports.
The financial discipline has adopted industry standards in the form of Generally Accepted Accounting Principles (GAAP) in order to make their reporting credible and to enable benchmarking. If every company reported Earnings Per Share (EPS) but calculated it differently from company to company, we shareholders would have no basis for making decisions about what are good investments and what are bad investments. Finance is meticulous about using consistent naming conventions, reporting formats (e.g., P&L statements, balance sheets) and formulas for calculating financial metrics. We marketers can't wait for an industry body to tell us how we should calculate our metrics and KPIs (at least, it hasn't happened yet). But for maximum insight and credibility, we need to institute internal consistency in our own measures and reporting. "Cost per Engagement" must be measured the same way year to year, brand to brand, campaign to campaign and market to market. Otherwise, we'll have no basis for understanding whether or not we're being effective and efficient with our campaign spend. Likewise, we need consistency in our campaign naming conventions. How can we possibly hope to close the loop on marketing performance measurement for a campaign if every execution team named and trafficked that campaign with different words, tags, and campaign IDs? We need to take a page from the finance playbook and develop -- and enforce -- consistency in our naming conventions and how we define metrics and KPIs.
Application of a consistent taxonomy
A financial chart of accounts (or general ledger) is fundamentally a taxonomy -- a system of classification. It's a model for tagging or categorizing data to give it structure and flexibility. General ledger categories are considered so foundational they're typically defined just as a company is formed. When the first piece of data comes in the door (an invoice or receipt), or goes out the door (a check, a credit card charge), it's labeled or tagged according to the chart of accounts. This way, financial data is structured as it goes into the measurement system for easy access via reporting later. Marketing needs its own version of this -- a marketing chart of accounts, of sorts -- to both create intentional reporting categories and provide a methodology for labeling data as it gets stored.
Marketing leaders are notorious for being interested in slicing their data a million different ways. We see a report on sales results by channel and immediately we want to see it by customer segment, by brand, by region, by line of business and product. Structuring our data on the way in makes all that possible. It enables insightful comparisons too. Categorizing our performance data by agency, for instance, can very easily tell us which agency delivers the most per $1 we pay them in fees. By describing data up front and tagging spend and marketing activity data according to marketing's reporting categories, marketing can have the same instant visibility into performance that finance has. (With no all-night cut and paste sessions.)
Better data management practices like these have done very well for the finance discipline. They can also go far in helping marketing teams to tame the big data beast now scratching at our door and finally enjoy the same easy and reliable data management process, the reporting flexibility, and the C-suite credibility of our friends in finance.
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