Marketing teams today find themselves with an abundance of data: email sends, click-through rates, ad impressions, cost per click, time on page, bounce rates and so on. If there is a metric that can be measured from any activation, there is probably an untapped data stream waiting for marketing ops teams to engineer.
In the past decade alone, martech tools have exploded across the board and continue to grow with the advent of AI, promising organizations a tangible way to visualize their marketing investments and their impact on revenue.
Yet most reporting dashboards today may cause more frustration than inspiration for teams. A report by McKinsey & Company released last year revealed that only about one-third of B2C organizations have reached a “transformational level of martech maturity” — defined as an advanced level of adoption, with usage of advanced and integrated capabilities such as automated workflows and omnichannel personalization. McKinsey also noted that when interviews were conducted with respondents directly, the proportion of those rating their maturity as “operational” was much lower, highlighting a gap between teams’ perception of their martech use and the actual maturity level it’s at.
Where traditional marketing dashboards fall short
For nascent organizations or marketing operations, it can be easy to think that any data is good data. Once they’ve invested in a set of top-rated tools, they may have access to dashboards that populate with data as soon as campaigns launch and audiences respond. But over time, these dashboards can become overloaded with visualizations and too many KPIs set by leaders, with no visibility into alignment with business initiatives or outcomes. Siloed reporting across unconnected platforms, from CRM and marketing automation to paid advertising and social media, can also pose challenges for marketing teams looking to make sense of their data
The issue these days is not necessarily gaining visibility into a company’s data, but rather figuring out how that data can guide decision-making. A report by marketing intelligence platform Funnel.io noted that 41% of in-house marketers say they report results without first discussing the "why." Answering that "why," however, is especially key for B2B, where the sales cycle can be longer than B2C, sometimes lasting years for high-profile and/or high-dollar projects. Without context for why metrics are improving or worsening month over month, insights can’t be gained, and teams waste time interpreting dashboards rather than acting on them.
Start with decisions, not metrics
A way to reframe traditional dashboard thinking is to lead with the metrics that really matter, not just the ones that are there. These metrics can vary according to levels within the organization, as each team may be responsible for different KPIs for the company. For example:
- CMOs are more likely to look at pipeline contributions, win rates, average deal size, and more that can be directly attributed to marketing campaigns.
- Demand gen leaders are concerned with the quality of leads and conversion bottlenecks.
- Marketing ops teams will want to firm up attribution and engagement scoring.
Today’s B2B marketers need leading indicators of where campaigns are going and why, not just how many views or how many followers. A strong, more dynamic dashboard will answer the question for any marketer: What decisions should you make next?
Where to drive action in reporting
Dashboards with just numbers can slow decision-making down as marketing leaders try to interpret them. Data ops and analytical teams should be prepared to add context ahead of time to reports that make the numbers more meaningful, such as:
- Industry benchmarks for comparison
- Historical trend lines
- Goal tracking
- Seasonal and economic considerations
Teams might also be wondering where they can leverage AI when it comes to reporting. Easy areas of entry can be to use generative AI for writing quick summaries or tools to surface anomalies in the data that could use attention.
In addition, marketing leaders should set best practices across the organization that encourage routine decision-focused dashboard monitoring, real-time performance alerts, and shared visibility across sales and marketing. Without healthy habits in place, dashboards can become outdated, inefficient, or worse — ignored.
Ultimately, as AI and data ecosystems mature, the competitive advantage will be the ability to translate insights into action quickly and more consistently. The idea isn’t to track all metrics possible in your dashboard, but to highlight the ones that can truly impact the business.
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