November 21, 2024

3 ways to link marketing to revenue without metrics

I’m looking forward to our annual ITSMA spring road trip. This time, I’ll be speaking about how to tie thought leadership to revenue, starting in Santa Clara, CA next Wednesday, and in New York and Newton, MA the following week. Hope you can join us.

Now, you may think that because I’m using revenue and thought leadership together in the same sentence that I’m going to reveal some secret way to measure the link between the white paper you published last month and the complex solution sale you make six months from now. Alas, no such magic metric exists.

We’re focusing on the wrong things
In fact, our most recent thought leadership survey found that few marketers are measuring much besides consumption of their marketing content. I’m not saying that you should stop measuring consumption; but it’s clear that those kinds of metrics don’t give business people the answers they’re looking for when they ask about the value of marketing. They want more strategic answers, such as whether marketing is increasing the velocity of contacts through the buying process and reducing the time and effort that salespeople need to expend in making a sale.

If you have the ability to measure those two things, then great. But if you don’t, there are still ways to make sure that those things are happening. Here are three ways to do it:

  • Connect ideas to offerings. Too much of our content just tries to look and sound smart—great focus on ideas, but no real connection to how our companies can solve the problem. At the other end of the spectrum are the brochures that masquerade as idea marketing by making the offering descriptions longer and the production values higher. One great way to connect ideas to offerings is to create a business theme—think IBM’s Smarter Planet or Cognizant’s Future of Work. Both of these themes give subject matter experts and marketers plenty of leeway to focus on ideas while maintaining a link to the company strategy and its offerings.
  • Use ideas to attract and nurture leads. If you’re a regular reader of this blog, you know that I’m constantly beating the drum of integrating content with an automated lead management process. A lead management process gives you the ability to get the right content to the right people at the time they need it.
  • Train salespeople to use and talk about ideas. Creating good idea-based marketing content is hard and takes a long time if done right. That’s why the urge to start drinking kicks in about the time the white paper finally hits the website. But hold the beverages. Most salespeople don’t know what to do with a 20-page white paper. Marketers tell me that if they can get salespeople to even send the thing to prospects and customers they’re happy. We need to do much more than that. We need to create talking points for salespeople to use when communicating to customers and prospects, and we need to find ways to integrate salespeople into the content development and dissemination processes from the start.

How do you link content to revenue? Please give me your thoughts. Hope to meet you live, in-person soon!

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We need a chief marketing analytics officer

There’s lots of talk out there these days about the need for a technology guru within the B2B marketing department. Paul Dunay makes the case for one in this post, and Scott Brinker has been beating the drum for this for some time.

Maybe I’m splitting hairs here, but I wonder about the long-term need for a marketing technologist. In the short term, I think marketing has a lot of catching up to do in terms of technology. Most companies do not yet have closed-loop lead management processes supported by systems, for example.

So we need some important systems installed in the short-term. But once the system of record is installed (and many of them are SaaS), do we really need a CIO for marketing?

We need to connect the analytical dots
I think the larger and more long-term need is for marketing to become data driven. We need to use analytics to quantify and manage how fast we move prospects through the buying process and to increase loyalty and trust after they’ve bought from us.

I’d rather see a chief marketing analytics officer than a chief technologist. Or if this person is going to be a technologist, he or she must have a serious grounding in analytics. B2C companies have these “wonks” today. I think B2B marketing groups need the same emphasis–and that need will never go away once the systems are installed.

What do you think?

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Analytics means looking ahead

I want you all to throw out whatever definition you have in your heads for analytics—just for a moment—so we can talk about what analytics should mean. If there’s one thing I’d like to bring across to you it’s that analytics is about looking ahead—about being predictive. What most of us do today with analytics is report. We look at what we have already done and report on it. Analytics is much more than that. It is about making future decisions with more certainty of success.

And in these times, we must make the right choices in marketing—choices that will translate into revenue. There simply isn’t any room for mistakes right now. So the timing of the online briefing that I’ll be doing on December 16 about marketing analytics is pretty good.

In our presentation we are going to talk about three things you can do today to start improving your ability to predict. First, we’re going to talk about methodologies for analyzing marketing programs’ success before you have to commit the big bucks. Second, we will talk about why finance is a key player in helping you improve your analytics program. And we will talk about how you can start to shift the culture of marketing and your business from what I call a talent approach to what our friend and colleague Tom Davenport, who recently presented at our annual conference, calls a fact-based culture. By the way, Tom has written a book called Competing on Analytics that you should check out if you haven’t already. I’ll also reveal some selected findings from our recent survey on marketing analytics.

I think it’s important to distinguish analytics from metrics because I see these two get jumbled together a lot. Analytics is essentially gathering data and looking at it to gain insight, while metrics are the descriptive performance measures that we use to gauge progress.

The goal of both metrics and analytics, of course, is not just to track and measure marketing programs, but to build business success. To that end, we have created what we call ITSMA’s Analytics Best Practice Model. I won’t go through all of the elements of it in detail here, but these are the basic goals:

  • One is to find and coordinate the data we need across the organization so that we can start to make better decisions across all of marketing and the business, not just in selected pockets.
  • Second, we want to create a link with finance—where the analytics experts are—to start to look at marketing programs as part of a greater whole. it’s great to optimize within marketing, but as we all know, marketing is just one piece of business success.
  • Third, we want to create a fact-based culture.

We’ve all heard of gut-based decision making, right? I get this vision of a fat guy with a cigar chomped in his mouth and his suspenders between his thumbs barking about how “My gut has never failed me yet!”

That’s not it at all. Marketers don’t operate from the gut, we operate from talent. We rely on our talent to develop creative programs that will, in general, be successful.

What we have not done in our organizations is to make room for the facts before we start to exert our creative energies. We tend to think that we have hired good people and they should simply go forth and do their best.

But we need to create the organizational patience—the time and tolerance—to gather the facts about the prospects of success before we go forward. And that means that we need to change our thinking to be more like financial analysts and engineers.

More left-brained, in other words.

Good car companies don’t skip crash testing of their new models, even if the new model is not much different than the previous ones that have done just fine in testing.

What do you think?

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