5 pressing marketing analytics problems and how to solve them
Data. It’s a perennial problem for businesses and marketers.
In the B2B Marketing Benchmarks report by LinkedIn’s Marketing Technology Group, the #3 issue (predictably behind numbers 1 and 2, “Generate more and better leads”) was marketing analytics problems:
Improve the ability to measure and analyze marketing impact.
Why, with all the numbers and software and new visibility into marketing and sales and operational and predictive metrics, is it still so hard to measure and analyze the impact of marketing?
There’s a reason. Five reasons, actually. To channel my favorite analytics guru, Avinash Kaushik, we’re going to start with defining the most pressing analytics problems first, then talk about how to solve them.
“To guarantee success, spend 95% of your time defining the problem and 5% of the time solving it.” — Avinash Kaushik
Problem #1: You don’t have access to the data you need.
It’s a common problem for SaaS companies: the data exists, but your engineers are busy working on product and don’t see the value in helping the marketing and customer teams pull usage data.
Because, yanno, marketing is just “liquor and guessing,” according to Dilbert.
You dig into your Google Analytics and your HubSpot data and you report on marketing, but maybe your marketing automation platform isn’t hooked up to your CRM so you don’t really know what happens to those people after they fill out a landing page form and you pass them on to Sales, except that you know Sales doesn’t always love the leads you send and you resent that because you worked hard to create attractive marketing offers and….. (Sound familiar?)
Marketing data? Check. Sales and customer data? Little to none.
What to do?
Solution: Become an analysis ninja and convert the C-suite.
Generally the drive to connect and distribute the data has to come from the top. There has to be an understanding at the C-level that connected data will help everyone make better business decisions. As a marketer, your best bet is to put together reports with all the holes in them: This many people converted on the landing page, but we lost them in the Sales cycle and have no idea if they became customers and whether they’ve proven to be good customers. These are the blanks we want to fill so we can increase the bottom line.
“Increase the bottom line” is a powerful phrase. Use it.
Problem #2: You’re drowning in data and can’t sort through it.
Remember the days when salesmen sold door-to-door encyclopedia sets, and your family made a big investment in one and the set sat on the bottom of the bookshelf until you desperately needed some information for a school report? And that single paragraph told you next to nothing?
That’s not today’s problem.
Today’s problem is too much of a good thing. We have more data than we can possibly ever analyze. Our tools are extremely powerful and they have powerful insights hidden in lots and lots of numbers.
So what do you do when you’re drowning in data?
The solution: Data is meaningless without analysis ninjas to interpret and apply it.
Again I turn to Avinash to explain the power of human insight:
“The web is inherently complex, every bit of it… And it changes every day. In such a environment insights come not from the multi-million dollar tools that you can implement, and yes you can buy multi-million dollar tools, but the human power you can unleash to make sense of all the irrationality and ensure that valuable nuggets of insights can be found. …the tool is not the answer, it’s the people. Buy the tool you want, but remember the 10/90 rule [$10k in software and invest $90k in great staff] and invest accordingly if you want to win.”
The strategic thinking, the analysis of the marketing, sales and customer funnel and prioritization of initiatives that will have the biggest impact, is why Smoky Labs exists. Of course you can invest $100K into a copywriter and designer/developer-lite to do your content marketing, but you’re investing in tactics first instead of impactful strategy.
Problem #3: You have all the data, but there seems to be multiple ways to interpret it.
I read a piece recently on cognitive bias and global warming. It turns out that if you approach global warming with an opinion, you will actually use your bias to filter the data and become more completely convinced of your position based on … the data. And yet each side firmly believes that the data proves their position.
Even if you have no cognitive bias to your marketing numbers (other than the obvious desire for them to make you look awesome), there’s still sometimes the problem if not knowing which numbers are important and which can be filtered out.
This solution is easy: Work backwards through your funnel.
When you’re looking at top of the funnel numbers or middle of the funnel numbers and you aren’t sure what they mean, follow them down to the bottom, or work backwards to get your answers.
Let’s say you’re looking at web traffic acquisition channels. It appears on the surface that your paid campaigns are rocking it out and that social, particularly Twitter, is a crap way to bring in traffic. One is a huge slice of the pie and the other is so tiny that it wouldn’t even break your Weight Watchers diet.
So let’s follow those all the way through the funnel, because the ultimate data point is “which of those channels converts at a higher percentage” and also “which of those channels tends to bring in our very best customers who stay with us, spend a lot of money, and recommend us to their friends and colleagues?”
Now we see that the paid traffic tends to convert at a lower percentage, although still at a higher overall piece of the revenue pie, and that the Twitter traffic converts at a higher percentage but there’s less of it.
Ah, but what do we do with this insight? Read on.
Problem #4: You’ve got insights but don’t know what actions to take.
In the previous example, you’ve determined that paid advertising converts at a lower rate but brings in more overall revenue than Twitter, which converts at a higher rate but is a smaller piece of the revenue.
What do you do with this insight?
You could put more resources into Twitter, which converts at a higher rate, and hope to increase the total number of Twitter conversions.
You could put your Twitter resources into paid ads because even though the conversion rate is lower, the overall revenue increase would be worth it.
Or, you could keep digging. What else do you need to know to do something with this insight?
- The customer acquisition cost and lifetime value for each channel. Twitter may cost very little in customer acquisition and result in high-value customers, in which case it would be stupid to give up on the channel just because the overall number of conversions is low.
- Major company goals. If your company is in a high-growth phase and you’re out for a land grab, the total number of customers is more important than hand-selecting a smaller number of high-value customers. On the other hand, if your company is stable in terms of market share, the focus may be on acquiring customers that fit an ideal profile of long-term, high-value, delighted advocates.
Problem #5: You’re not sure whether your numbers are comparatively good or bad.
There’s an art and a science to evaluating the competition. The science is in using their best practices and industry benchmarks to rise to the top. The art is in selectively ignoring what everyone else is doing because you have the capacity to go so beyond the competition, and the only thing limiting you is the idea that if they get 3% you should go for 3.25%.
So you’ve got numbers, but you’re in a vacuum. You have no idea if they’re better or worse than what everyone else is doing. You have no idea if you’re rocking out those landing page conversions or if they completely stink.
You can find SaaS benchmarks in many places; one of my favorites is David Skok’s blog For Entrepreneurs.
This B2B sales benchmarks infographic from Implisit is fantastic.
Compare your numbers to benchmarks, but remember this other fantastic quote from the godfather of analytics:
“The interesting thing about averages is that they hide the truth very effectively.”
— Avinash Kaushik
That average tells you nothing about what individual rock stars are doing in your industry, nor does it tell you how much those rock stars have pulled up the losers.
The goal isn’t to hit marketing benchmarks. The goal is to exceed them.
Solution #2: Compete against yourself. Whatever your numbers are now, identify the improvements you could make that will have the biggest business impact.
You know what? The only thing the C-suite cares about is the impact on the business. Revenue, top-line and bottom-line. Number of customers. Type of customers. Longevity of customers. You get the idea. Work backwards from the business goals and look at the marketing metrics you have the power to improve, and focus on those.
Some generally good examples:
- Landing page conversion rate: Of all the traffic coming to the site, how many leads are we capturing? Also, what do we know about them?
- Email campaign outcomes: What percentage click through to the site, and what do they do once there?
- Blog post calls to action that lead to lead capture: You do have calls to action on blog posts that help you capture more leads, right? Which posts do the best job and could be tweaked and republished and redistributed? Which calls to action consistently overperform?
- Free trial signups: A “duh,” but had to throw it in there.
- Free trial email nurturing campaign engagement and in-app engagement: Once someone’s signed up to a free trial, how well are they interacting with your company and the software itself? Which actions are they taking? Specific actions can be a huge indicator of a future conversion.
Some generally bad examples:
- Email open rate: A total vanity metric. All that tells you is that you had a good subject line, but where does it fit in with the bottom line?
- Time on page: Although this is a good marketing metric in terms of understanding how engaged your users are, some pages aren’t designed to be browsed forever. Sometimes the goal is to get the user off the page and taking an action.
- Social shares: Another good marketing metric to judge the value of your content, it’s not deep enough to get to the sale.
It’s a perennial problem for businesses and marketers, but it doesn’t have to be your problem.
Speaking of analysis ninjas….
Are you an analysis ninja like Avinash? A Gary Vee-like social guru? A prolific influencer in the ranks of Seth Godin? Take the newest Smoky Labs quiz, Which Famous Marketer are You? and find out!
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Originally published at smokylabs.com on February 22, 2016.