W. Edwards Deming, ground-breaking statistician and management consultant of the twentieth century, famously said, “It is not enough to do your best; you must know what to do, and then do your best.” Yes. A thousand times this. Particularly in the world of omnichannel B2B digital marketing, you have to know what to do, or you’ll never be able to achieve your business goals. You can no longer just “throw spaghetti at the wall to see what sticks” because there’s just too darned much spaghetti and there are far too many walls (channels) to throw it at. You must be focused and strategic to remain competitive today.
So what should B2B marketers be focusing on? Customers.
You need to be continually looking at your interconnected customer data to solve the mystery of who your customers are and what they care about, and then sift through them to find the customers or prospects that are likely to impact your bottom line the most.
The Gap Between Analytics and Action
Lots of B2B companies are investing lots of money into business intelligence tools to collect customer data. But it’s not enough to just collect a ton of data and report on it; you must make sense of the data to know who is best to target and why you should do something. A spreadsheet full of information means nothing without the analysis that connects information, tells a story, gives it meaning and makes it actionable. That’s the gap that most organizations need to close – between analytics and action
But, of course, that’s all far easier said than done.
In an extremely fluid marketplace, more and more B2B firms recognize the need to step up their digital marketing efforts and create a seamless customer experience (CX). Yet, they find themselves drinking from a firehose of data in an attempt to stay ahead of ever-increasing customer expectations. Most aren’t staying ahead at all, though – they’re doing the best they can not to fall grossly behind customer expectations.
That’s because many B2B firms are very much in a reactive mode, only able to respond to relatively disconnected data that represents customer behaviors that have already occurred. Some are moving aggressively into more predictive analytics that help them anticipate what customers are likely to do in the future based on past and current behaviors; and a few are already in the world of artificial intelligence (AI), or machine-learning that can aggregate data from interconnected systems to anticipate future states before they even happen.
But most aren’t anywhere near that ideal. 74% of firms say they want to be data-driven, but only 29% are good at connecting analytics to action. What are they missing? Where are B2B marketers falling short? How can they turn it around?
Build a Culture of Analysis
To find out how B2B marketers can derive meaning from their customer data and turn it into action, we spoke to Adele Sweetwood, head of global marketing at business analytics software and services firm SAS and author of The Analytical Marketer: How to Tranform Your Marketing Organization.
Sweetwood recommends starting with understanding where you are today in your analytics maturity and comparing it to where you want to be in the next few years. Ideally, she says, you should aim for a marketing culture that is infused with, and empowered by, analytical thinking at every level. A marketing culture of analysis leads directly to action and a quantifiable return on investment. By initiating such a transformation in your marketing organization, you can begin plotting out the strategic plan governing the people, processes and technologies that will get you there.
Evaluate Your Analytics Maturity
So where are you on the continuum of marketing analytics maturity? Sweetwood says most organizations are at an emerging or mid-market stage, collecting and looking at data to some degree with varying levels of effectiveness. It’s not like anyone is ignoring customer data entirely.
“B2B marketing has always done historical analysis of specific efforts – like campaigns, tactics or messages – and their effects on customers’ behaviors,” Sweetwood says. “At this point, we can all report on things that have happened. And that’s valuable, but it’s backward-looking and doesn’t tell us what could still happen. That’s the next level of sophistication.”
Assuming you’re shooting to build a culture of analysis similar to that of SAS, you’ll need to:
- Establish the right mindset or vision by defining and empowering analytics for every marketer in your organization
- Address your organizational structure to orchestrate and integrate marketing and customer experience data and activities across the entire customer lifecycle
- Acquire the talent (and/or train existing employees) to optimize data analysis and turn it into action
- Get leadership to define clear and measurable objectives that drive the right types of behaviors, with an eye on the customer experience and revenue impact
Recreated from The Analytical Marketer: How to Transform Your Marketing Organization, Harvard Business Press. Copyright 2016 SAS Institute Inc. All rights reserved.
Get Buy-in from Company Leadership
Sweetwood advises getting executive sponsorship and buy-in from top-level company leaders across multiple departments early in the process to help initiate and support your transformation to a culture of analytics. It eventually needs to extend beyond marketing to include every customer touchpoint and channel throughout the customer journey to eliminate silos and facilitate a convergence of goals, tools, data and workflows.
To that end, C-level leaders will be interested to know that the impact of customer analytics on corporate performance is significant, and clearly underestimated. Strikingly, companies that use customer analytics comprehensively report outstripping their competition in terms of profit by 93%, sales by 82%, sales growth by 112% and ROI by a whopping 115%.
Be Agile and Iterative in Your Implementation
Know that once you have buy-in and have put the pieces of your new data-driven marketing framework in place, you’re not done. Sweetwood emphasizes that the process of building an analytics culture is never finished. It’s continuous and ever-changing. She recommends approaching it like agile software development: Work in sprints; monitor your data all the time; test frequently; learn, change, test again, and do it quickly.
Note also that “customer data” means more than “behavioral data.” In addition to monitoring performance, it’s critical to maintain data integrity and the flow of data between systems and applications to keep customer records updated and complete. This is particularly critical if you are pursuing account based marketing (ABM) or strategy segmentation. This requires aligning your data strategy with your talent acquisition and technology plans as well.
Unify and Empower Your Marketing Team Members
No matter how automated your marketing operations have become, though, and no matter how smoothly integrated your customer data sources are, the success of an agile data-driven marketing strategy ultimately depends on the human beings in your organization understanding the business strategy and how their individual contributions move that strategy forward. “When it becomes part of marketing’s culture, analysis is an everyday part of life. We live it all the time,” says Sweetwood.
And it really is every marketer, not just marketing analysts and data scientists. “Data scientists look at more sophisticated sentiments – marketing automation, operational components, reporting, analysis for strategy and so on. They’re looking for big trends and stories for behavior modeling, like for scoring and nurturing components,” Sweetwood explains. “But every marketer should have access to the tools to see campaign performance on their own desktops – the very same tools and data I have on my desktop.”
Understand How to Make Meaning from Data
Once your team members have the tools they need to access customer data, how can they use that data to make decisions and take action? Ideally, data analysis should be derived from questions that ultimately roll up under a guiding business strategy. That in turn means teams need to understand the business strategy well and see how their decisions move that strategy forward before they can act in impactful ways. “We’ve changed our expectations for our marketing team members by giving them the technology and incentives to be able to act confidently and back up their decisions with data,” Sweetwood says.
In short, your team members can and should know why they’re doing something – and to whom their marketing is speaking. They should use the customer data and analytics available to them to target precisely, personalize stories, design campaigns and make investments. As Sweetwood has seen first-hand at her own company and in others, this gives marketers tremendous confidence. They’re more willing to take risks and do more A/B testing so they can make better decisions.