The marketer’s mandate will always be “more” — more traffic, more sales, more margins. Add to it that in order to get more, we’ll need to test more ideas, try new strategies, new media and mediums — not all of which will work.
More ultimately means sales conversion, and there’s a data-driven approach to getting more that leverages a new currency. Not Bitcoin, but relevancy, because relevancy is the “Currency of Conversion.” That conversion currency is based on the intelligent use of data.
Truly accomplishing data-driven success requires focus and simplifying — one of the few constants in business marketing.
Through advising dozens of organizations on the intelligent use of data to inform and improve performance, it is often helpful to come back to some of the fundamentals in thinking about the application of our data to business problems. And while often we focus on the “what” that has to do with data, let’s consider perhaps the most important question — “Why?”
Why Should I Inform Marketing With Data?
While it’s likely considered risky nowadays to lack a data strategy or better yet, a data-driven strategy, we do need to ask why. I’ve been surprised at the lack of fluency even experienced IT people and all kinds of marketers have when asked why they need to invest in data strategies. That’s despite the “reality” that everyone knows they “should.” Let’s deal with that.
- Reporting. Many organizations still desire better reporting, Key Performance Indicators (KPIs) being the most important. It’s a baseline use of data, and it’s important. So data serves a purpose and provides consistent, specific solutions to the questions “how are we doing?” It’s hard to operate without it, but it should become “table-stakes” in short order.
- Analysis and Insights. Data, if organized and governed reasonably well, can yield insights. This requires you have an analyst with a big brain to pore through it. The analyst needs to know enough about your business to understand what is relevant and what is not. The analyst must also consider materiality and the difference between correlation and causality.
This last point being an all-too-common mistake. For example, “our customers are rich” so we need to target rich people. Being affluent may be correlated with buying your product, but it may not be causal! We’ve found this example many times when actually statistically testing to see what attributes have the most causal/predictive relationship. For a full study on causality vs. causation, see this piece from Stats.org.
- Customer Intelligence. Customer Intelligence is the next-level beyond analytics. In CI, we now use purpose-specific algorithms to derive new data and to identify valuable patterns that arise in large amounts of data. It’s fair to call it “the union between marketing and data mining.” Customer Intelligence provides us the answers to questions we don’t ask because we don’t know how to answer them.
The Most Important Reason to Inform Marketing With Data
The low cost of communicating digitally has, in some cases, left relevancy underrated. This is no coincidence. When you spend real money to send a quality, brand-appropriate direct mail piece or even more money on television — you care a lot about relevancy. This message has to be right, it has to be on-brand, it has to resonate. Today, that mass-market TV ad isn’t a winner if it doesn’t “break the Internet.”
But when it’s an email that costs a fraction of a cent to deploy and just a few fixed dollars to create amortization over millions of recipients, we as marketers can get impressively lazy. Relevancy is trumped by low cost and high ROI. Who cares if the message is perceived as irrelevant? The email drop “worked.”
Let’s consider this further.
Let’s say the “less than relevant” drop had an out-sized 35 percent click rate. We know the sender names were likely those they anticipated email from, and the subject line was likely relevant. We can’t know the breakout of which send carried more weight without testing them. But if you subscribe to the school of thought that relevancy isn’t important, then testing probably is irrelevant to you, too. Before you decide “well, of course we think relevancy is important” — think about whether you’re really using it as a principle in your outbound marketing.