Three Steps to Preventing a Marketing Analytics Misfire
Our customers are the heart and soul of our marketing strategies. That’s why marketing teams are collecting as much audience data as they possibly can. Thanks to marketing automation systems, Python Web scrapers and social login tools, we have plenty of resources available to learn about our customers.
We can create sophisticated behavioral targeting models, build sales prediction engines and target our audiences with the right messages in their buying journeys — that is, until our predictions misfire and steer us completely off course.
Every marketer has been in this position. We think we know what our customers want, and we have access to data that suggests we’re on the right track. The reality, however, is that we’re wrong — not necessarily because our data is incorrect but because our analyses may have been incomplete.
The harsh reality is that there is no way for CMOs to prevent these mistakes. Data fragmentation and silos are challenges for almost every organization. What CMOs can do is help their teams analyze customer data with a more skeptical eye. Marketing-led teams can look for hidden trends — and opportunities — by taking the following steps.
1. Break Down Aggregates into Building Blocks
When you’re launching a new product or campaign, you likely monitoring a set of KPIs to gauge successes and failures. You might ask your team to create a report with a "birds’ eye view" of how the initiative is performing. Based on that surface-level observation, you’ll then, as a team, decide whether it’s worth it to dig deeper.
This approach may steer your organization in the wrong direction. Here’s why.
Your customer base includes many different types of segments that may vary in terms of size and contribution to revenue. Segment A, for instance, may represent 30% of your customer base but 70% of your revenue while segment B represents 70% of your customer base and only 30% of your revenue. Ideally, the two segments will be evaluated on separate terms.
“For example, when we recently launched a new, highly differentiated product, it appeared to ‘lose’ overall as compared to the control,” says Rochelle Sanchirico, head of marketing and analytics for Webs — the digital services arm of Vistaprint.
“With closer analysis of leading indicator metrics in behavioral customer segments, we determined that the campaign was ‘winning’ with our top customer segment so we kept it live.”
CMOs must encourage their teams to dig deeper and break campaigns apart — to approach reporting as a process driven by building blocks.
“As CMOs look to manage data as related to marketing, my top recommendations would be to hire smart analysts who really understand business and to focus on the most important key performance indicators,” says Sanchirico. “We’ve had analysts who are more scholarly and have had less success, since marketing automation is about actual business results, so analysis and campaigns must be practical and focused on outcomes.”
2. Connect Conversion Events to Full Buyer Journeys
KPIs can cause tunnel vision. When we focus on optimizing specific goals, we lose sight of how performance benchmarks relate to the bigger picture. Let’s consider paid advertising campaigns, as an example.
When we run advertising campaigns, we often measure success based on direct responses and conversion events. When it comes to making purchase decisions — especially in the B2B space — however, buyers aren’t necessarily ready to make an immediate decision.
If a campaign generates high advertisement click-through rates but low conversions, we’re likely to scrap the initiative as a failure. What we may not see, behind the scenes, is that people may be coming back to look at our products — maybe six months to a year down the line.
“Data is a tool, not a replacement for conversations and human interactions. Analysis and decision making cannot be done in a vacuum because the context may not always be there. There is still an equally important storytelling side to data.”
To create a story with data, CMOs need to power up their marketing analytics with information systems that join data from multiple sources. Boko and her team at Sage, for instance, use Domo to create daily graphical representations to key metrics for all of our business units, leadership teams, and international teams to provide a unified customer view.
“Unlike some organizations, we can now track waterfall and conversion metrics for all Sage business units, which provides a top level view of the prospect activity required to reach our revenue goals,” says Boko.
“We can now also visualize our awareness and engagement metrics across all marketing activities, which allows us to track our conversions for impressions to clicks, clicks to forms, forms to leads, leads to opportunities, and opportunities to revenue. This is critical in our daily view of effective activity as well as our annual strategic forecasting activities.”
3. Look Beyond Your In-House Data
Companies are collecting volumes of information – but these data points are only part of the customer story. The fact is that we don’t know what we don’t know and that external sources of information can help us sanity check our information.
To optimize marketing analytics and build more engaging processes, marketers need to continue to collect data outside of their company walls. Qualitative research – the process of understanding why and how your customers make decisions – can provide an important guide.
“Whether it's recruiting customers for online survey panels, testing creative and approach with your consumer base or understanding where and how potential customers are consuming media, a small investment in research can help save (or generate) a lot of revenue,” says Monica C. Smith, founder at i.Predictus, a demand-side platform for television advertisers.
Smith points out that when she was launching i.Predictus in 2012, the marketing landscape had undergone a significant transformation and essentially, re-written itself. As she puts it, marketers were “scrambling to keep up.”
“Emerging technologies were lagging behind evolving consumer behaviors, and our ability to establish meaningful connections with our customers was growing more and more tenuous as a result,” says Smith.
Marketers need to stay ahead of their own technologies by putting themselves "out there" and exploring what’s happening beyond company walls. After going through this process and conducting extensive qualitative research, Smith dedicated her career to understanding the customer’s journey, “no matter how many twists and turns it took.”
“We are living in one of the most exciting yet difficult times to be a marketer, and that is a challenge I will not back down from,” says Smith.