Hillary is blaming James Comey. Others say blacks just didn’t turn out in the numbers expected. And, then there are those who are positively shocked by the percentage of Latinos who voted for Trump.

Alas, the above-mentions politicians, pundits and just plain, old folk like you and me missed the REAL culprit behind Clinton’s loss last week. It was Big Data and it little brother, Analytics.

As many of you know, Big Data and Analytics have become Hollywood A-Level superstars in the marketing communications/public affairs/lobbying and polling worlds. In fact, one might liken them to Brad and Angelina prior to that oh-so-messy break-up.

After all, it’s a given that EVERY great campaign MUST begin with a deep, quantitative dive into the target audience to determine exactly who they are, what they think, where they’re concentrated, when is the best time in which to engage them and, of course, how to create that oh-so-critical connection with them.

Then, Big Data passes the baton to Analytics, which proceeds to spew out all sorts of scientifically-based, nearly indecipherable charts and graphs that enable the strategic and creative types (that’s me, BTW) to create a campaign.

Ah, but Big Data and Analytics sustained one whale of a wake-up call on Election Day.

The “experts” who crunched all the data, created all the profiles and made all the predictions (some of which called for a Clinton landslide) were dead wrong.

Why? It’s actually intuitive but, in the mad rush towards digitizing everything in marketing, the Stronger Together team forgot to listen.

They also forgot to put themselves in the shoes of every conceivable voting bloc, and not just assume the very same majority that twice put Obama over the top would do the same for Hilz.

In short, they didn’t add a qualitative overlay to their Big Data findings.

Qualitative surveying enables one to ask the one question that always trips up Big Data: Why?

So, as Clinton’s ground game went knocking from door-to-door, urging Swing State voters to back Hilz, they just shrugged their shoulders and moved on as said door was slammed in their face by an uneducated and, most likely, unemployed rural worker who proudly proclaimed she or he would be voting for The Donald instead. Hilz people never bothered to ask why.

We INSIST on adding qualitative interviewing as well as what we call Audience Experience to any significant client project.

That’s because yours truly in particular has never been a big fan of relying solely on Big Data.

I like to ask the why question to target audiences. Why do, or don’t, you like my client’s product, service or organization? Really? Tell me more? And, why is that? And, so on and so forth (Note: Please do NOT confuse the above with focus groups, which are badly flawed since the alpha personality in the room ALWAYS dominates the conversation while the Beta types nod their heads in agreement).

We also assign teams who actually experience the client’s product, service or organizational experience first-hand from the outside-in.

We invariably find gaps between a client’s brand promise and what the target prospect actually experiences (Note: most gaps are subtle, but significant; others are wider than the Grand Canyon).

I’d like to believe the 2016 election will cause my peers to take pause and think twice about relying solely on Big Data and Analytics.

As we’ve seen, Big Data has an Achilles Heel: it doesn’t humanize the fact-gathering. Nor does it allow one to rely on one’s gut instincts, rather than highly complex charts and graphs.

For all his faults, Trump ignored Big Data and Analytics, went with his gut instincts and, like it or not, came out on top as our new president.

I’m not suggesting we stop investing in Big Data or Analytics, but I am strongly advising marketers to slow down and spend time listening to the human beings you’re trying to influence. You may be surprised at their answers to the question why. And, that answer just might prevent you from making the very same mistake as Team Clinton.

Oh, and BTW, I’m Steve Cody and I approved this blog.