People throw out the term "data-driven" like it's going out of style. As a business built around empowering marketers with analytics, we think making decisions with data is a great thing. Unfortunately, it doesn’t happen as often as you’d think.
Many people elect to make an informed decision over going with their gut. Data-driven marketing should be possible. With each person producing over a megabyte of online interaction data a day, businesses are drowning in data.
Most executives demand data-driven behavior from sales and marketing. They want to see for every dollar invested in marketing, what revenue is coming out. The C-Suite reasons that if it's online, we have data and should be able to tie it into bookings.
Things aren't that simple.
A Dun & Bradstreet and Forrester survey found that 50% of B2B sales and marketing decisions aren't backed by data. More disturbingly, only 1.9% of marketing leaders reported that they had the adequate talent necessary to leverage marketing analytics in the CMO Survey. This number has remained the same since the question was first asked in 2013.
The Wrong Goals
Looking back at a Harvard Business Review article from 2007, the authors felt the answer to misalignment between the marketing organization and the rest of the business was simple:
Find metrics that force marketing to align with the rest of the business.
"[I]f today's boards wanted to exercise their governance role over marketing activities, they often wouldn't have the information they need to make sound judgments. Boards need a fundamental understanding of how the company is meeting its customers' needs and how marketing strategy supports this goal. It is rare to find a firm that provides its board with a scorecard that allows this," stated Gail McGovern, a professor of management practice associated with Harvard Business School's Educational Technology Group.
Thirteen years later, I believe McGovern would come to the same conclusion. Boards need data to make sound judgments, and it's rare to find a business that provides a marketing scorecard to support their need.
Infrastructure and talent play significant roles in the data disconnect. However, the larger problem lies in not understanding what should be measured, how to translate data into insights, and what actions come next.
Many growth-stage, and some later-stage, companies are still measuring MQLs, SQLs, and opportunity sources to measure marketing's success. These aren't bad lead generation indicators for marketing teams to use internally. However, customer journeys are not linear. One marketing activity does not correlate to one sale. Particularly in longer sales cycles, multiple people from a target account interact with marketing across numerous channels before a salesperson makes contact, and this buyer committee moves between platforms and buyer stages throughout the process.
Sometimes executives demand MQL, web traffic, and name acquisition because that's what they know as a best practice. Oftentimes, they take what they're given by marketing leadership. Because of data complexity and lack of analytics resources, these are the only numbers they can gather quickly.
If a marketing department has embraced a digital strategy, every sale should be influenced by marketing messaging. Marketing should be viewed as an early sales partner with a lot of leverage. While salespeople are good at connecting one-on-one with individuals, marketing leverages platforms that connect with many people at once. If analytics aren’t fully developed, it would be more useful to assume marketing has some part in all transactions and measure cost per lead, cost per sale, and lifetime customer value and then watch these data points for positive or negative trends.
When organizations are allowed to invest in data infrastructure and the talent needed to translate information into insights, scorecards can become more sophisticated. Attribution models can more definitively unveil which channels are the most influential at which stage of the buyer journey. Marketers can report on top-performing channels, return on marketing investments, and, most vitally, pipeline/revenue generation.
With the right infrastructure, trends can be spotted across industries or buyer personas. Marketing can play a more strategic part in guiding the business in their go-to-market plan and product development strategy.
No Data Strategy
When it became clear COVID-19 wasn't going away without making a major impact on the market, we watched many companies slash their marketing budget. Many marketing leaders decided to continue to invest in what they viewed as lead generating activities (social, digital ads, retargeting, etc.) and analytics cut funds and resources.
The irony is, we need data now more than ever before. When market volatility is introduced in the form of three black swans (pandemic + recession + social unrest), real-time data is the only way to make educated decisions. We can't use historical data to figure out what will happen next. We've never seen anything like this before, and buyer behavior has changed in ways we didn't expect. For example, we may have predicted toilet paper and cleaning supplies would fly off the shelves. Still, I doubt many of us anticipated a climb in swimming pool installations, home entertainment build-outs, and indoor golf simulator sales.
To be truly data driven, people must consider what they want to achieve and the data they need to reach their goals before putting anything in motion.
Marketing lead generation tool purchase decisions happen too quickly. People hear about a new tactic, and they need to try it ASAP. Too often, people don't consider what success looks like and what we need to measure to determine whether it worked. They just want to get a campaign out the door and "help sales."
Buyer behavior is changing all the time, and trying new tactics is necessary. But doesn't it make sense to take a minute to establish how you're going to test the tactic and measure results?
In the past five years, system integrations and marketing decision-making behavior haven't improved. Unless people embrace a cultural change and place more importance on building the foundation necessary to see results, this will continue to be the case.
Too Much Data, Too Little Information
As we stated earlier, businesses are drowning in data. Marketing has gone from relying on television and newspaper advertisements (which were also difficult to tie to sales) to hundreds of online interactions. It's like moving from an organized gas station with products lined up on shelves to a Costco sized warehouse with stuff dumped in random piles.
We know aisle six holds social media data, and aisle 8 is website analytics, but we don't know if someone visited both piles or even if they visited the same pile multiple times. Marketing is trying to process information in bulk, and none of it is organized using the same inventory system.
With sophisticated normalization techniques, constant enrichment, and machine learning models, you can build a robust marketing analytics platform. This requires a firm belief that data-driven decision making is better than what people have been trying to date.
What happens next requires the right talent.
The Wrong Talent
Put a chart in front of the wrong person, and they'll see a bunch of meaningless squiggly lines. Put the same chart in front of a skilled analyst, and they'll be able to tell you possible implications behind new trends and where to dig next to understand the bigger picture. Combine an analyst's pattern matching and cause and effect abilities with an executive's market and product knowledge, and meaningful strategy development gets a whole lot easier.
Data-driven marketing leadership requires an investment in data architecture, business owners willing to provide context, and at least one person who can translate the findings for the rest of the team. It also requires a lot of trust in your analyst.
With only 1.9% of marketing leaders reporting they have the right level of talent to leverage marketing analytics, one or more of these components is missing. Either marketing leaders expect too much from disjointed systems, haven't invested in enough resources, don't have the time to meet with their analyst to give them the context needed to solidify their findings, or don't trust their employee has the right skillsets to correctly interpret the data.
We see the same marketing leaders who willingly throw money at unproven marketing tactics balk at investing in analytics. With more buying share shifting online, marketing analytics is something companies can't afford to get wrong.
Not Speaking the Same Language
Not all marketing leadership values data. A great deal of marketing is creative in nature. People study psychology and best practices to formulate messages that resonate with their audience. Data is sometimes a source of discomfort or even insecurity, and some marketers claim it’s not possible to measure marketing in a meaningful way.
CFOs and CEOs don't tolerate data avoidance for long, particularly in an unstable market. They demand results--something they can tie back to their investment to determine whether or not marketing is pulling their weight.
Marketing has long been considered a cost center, but it shouldn't be. If the right systems and people are in place, it's possible to tie activities to revenue. Once that happens, marketing's contribution is no longer abstract. Definitive results prove marketing’s contributions as a profit center.
A culture change also needs to take part in the C-Suite. Executives need to understand that buyer journeys are not linear. There is not and never will be a one-to-one relationship between a single marketing interaction and purchase, even if you sell a low barrier product.
Marketing deals in bulk transactions. Emails go to thousands of people. Tens of thousands may see online advertisements. Social media content is developed to draw in more followers and, hopefully, convert them into a sale. But that sale will likely first be associated with multiple people from the same account interacting with the website, videos, and webinars.
It's not possible to calculate a dollar-in-dollar-out model. Not in the way the C-Suite thinks of their investments.
We need the C-Suite to realize many interactions lead to a given sale, and we need to build trust in attribution models. Anyone who has tried to drive executive adoption of an attribution model knows it's difficult to do. You're dealing with linear thinkers who appreciate simple logic, and marketing is anything but simple.
We've done it, and we can show you how. At CaliberMind, we understand the nuances of the buyer journey and how critical insights are to building an efficient marketing team. It's more than possible to tap into the data you already have and turn it into a go-to-market strategy that works.
Ask us how -- we're here to help.
Raviv Turner A second time Co-Founder with over 10 years experience in product design and marketing technology, Raviv started CaliberMind to help B2B companies better understand buyers and ultimately increase conversion to revenue with dynamic buyer personas and buyer journey analysis. Prior to founding CaliberMind, Raviv was Director of UX at FullContact and VP Product at TapInfluence – an Influencer Marketing SaaS. He is a product design & UX mentor at Techstars and holds a MPS in Interactive Media from New York University.
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