Growth Marketing Analytics Research Findings
- 87 percent of the Best-in-Class marketers cited their contribution to revenue as the top key performance indicator. This was 56 percent higher than their lower performing peers.
- Adoption of information reporting tools varied significantly. 84 percent of the Best-in-Class regularly used predictive analytics, which was 67 percent higher than all others. This was the single biggest difference among marketing archetypes discovered from the survey results.
- 90 percent of the Best-in-Class marketers regularly used artificial intelligence (AI), which was 43 percent higher use than their lower performing peers.
The Growth Marketing Analytics Used by the Best-in-Class
Analytics make marketers smart.
Every company has them. In fact, analytics are one of the top 5 enterprise marketing solutions.
Instrumenting performance with real-time key performance indicators permits marketers to know what's working, what's not and intervene with timely course corrections to remedy deviations.
But that's not norm among most organizations.
As said by John Wanamaker over 100 years ago, "Half the money I spend on advertising is wasted; the trouble is I don't know which half." Sadly, for many marketers, this is still the case.
As part of the research for the Marketing Transformation Report, we posed several questions to measure analytics metrics, tools and outcomes. Here are some of the findings.
One KPI Stands Above all Others
We asked marketers to rank their top key performance indicators (KPIs). The results were then delineated by performance archetype.
Among the Best-in-Class marketers (i.e., the top 15 percent), the top three KPIs were all financial outcomes (revenue contribution, sales pipeline contribution and ROI).
87 percent of the Best-in-Class marketers cited their contribution to revenue as their top KPI.
That figure fell to 48 percent for Medians and 29 percent for Laggards. For these later groups the majority of KPIs measured activities.
Activity-based performance measures are useful but tactical. For example, a variety of lead acquisition and customer satisfaction measurements are insightful but only indirectly correlate with the company's top priority (revenue growth.)
The Right Tool for the Job
Different information reporting tools are needed for different information use cases. So, we also surveyed the growth marketing analytics tools and posed questions to understand how each tool was used.
The data surfaced three statistically significant findings showing how performance archetypes used the same growth marketing analytics tools differently.
First, the Best-in-Class archetype was 61 percent more likely to modify their Marketing Automation Platform (MAP) dashboards or CRM software dashboards with custom-developed KPIs.
That makes sense as this group previously indicated an overwhelming propensity to measure financial business outcomes, and most MAP and CRM systems do not provide out of the box KPIs for measures such as marketing sourced revenue or Marketing ROI.
Second, the Best-in-Class were 67 percent more likely to regularly use predictive analytics. This was the single biggest difference among performance archetypes found in the survey results.
Data becomes much more actionable when it advances from historical to predictive. In fact, without predictive analytics, the view for every marketer is entirely backward looking.
Third, the Best-in-Class cohort was 43 percent more likely to regularly use artificial intelligence (AI). 96 percent of this group cited using the AI in their MAP and CRM systems.
The data reinforce that AI for marketers is no longer in the early days. While many Medians and Laggards continue to sit on the sidelines, the Best-in-Class are putting this technology to work and substituting the technology for labor.
Putting Growth Marketing Analytics to Work
The research findings contribute to our Growth Marketing Analytics Framework. If you building a MarTech stack or are considering taking your business intelligence to the next level, consider our 7-step approach.
Growth Marketing Analytics Strategy
Start with a growth marketing analytics strategy that shows how to connect data, insights, actions and outcomes. The strategy identifies what outcomes matter most and need to be pursued first. It calculates your budget and expected ROI from the investment.
Every good business intelligence strategy and program starts with a common question. Many marketers think the question is "how do I best implement a growth marketing analytics strategy or program?" But that's not right. The first question isn't how, it's why.
Before implementing decision support systems, you need to first answer the question, "why should I implement this?" Why invest the time and money? How will this change staff behaviors, revenue contribution and Return on Investment (ROMI)? If adoption doesn't change these things you don't need to consider it further.
But for those looking for marketing transformation, the short answer to the essential question is that growth marketing analytics provide the data-driven, fact-based information to make timely decisions that aid the organization's most important objectives. These enterprise marketing technology solutions deliver benefits that cannot be achieved any other way.
Measure What Matters
There are plenty of tactical reports in your MAP and CRM system. Some can help improve operational activities, but most don't show the business contribution or value from marketers.
The C-suite doesn't care about activity and vanity metrics. They care about sales pipelines, forecasts and revenues. They want to know how marketing investments and efforts directly tie to revenue.
Our recommendation to measure what matters may sound straightforward. But it's not.
Most managers limit their reporting to the standard reports available in their MAP. And while marketing systems have lots of reports, they tend to be generic and pursue a lowest common denominator approach.
Extraordinarily few systems offer the most strategic measurements that demonstrate marketing's greatest impact.
For example, very few systems report revenue uplift opportunities such as lead leakage, forward looking measures such as customer lifetime value, or marketing's contribution to earned revenue. And because they don't capture costs, they cannot calculate ROI.
So, what's needed are some custom dashboards and reports that surface the most impactful information. Only then can you bring visibility to marketing's contribution.
Here's the interesting thing about data, a data paradox really. Virtually every campaign, offer or other engagement benefits from more data. Most organizations have large, vast amounts of data. But it normally languishes, goes unused and dies on the vine.
Data offers a use it or lose it proposition. It is a powerful asset if converted to information and made actionable. Otherwise, it is a recurring cost without benefit. And for the most part, data doesn't get better with age.
Simple information reporting can be created with queries and reports accessing MAP or CRM software tables and columns. However, for more powerful insights such interactive dashboards, predictive analytics, or AI you will need to create a data model.
You will also need to define the data extract, transform and load (ETL) process and supporting tools. Data extraction retrieves data from defined source locations. Data transformation filters, cleans, modifies, normalizes, appends, formats or otherwise processes data. Data load inserts transformed data to a destination, normally into a presentation-ready format, so it can be acted upon.
Performance benchmarks show us what good looks like.
For example, if 18 percent of your target market identify your brand without prompting, is that good? Well, not if 21 percent identify your competitors first. And when you consider the increased volume of sales leads that stem from increased brand recognition, this could be a significant opportunity that would otherwise go unnoticed.
Industry leaders use benchmarking to create a performance baseline, identify the biggest uplift opportunities and apply best practices to achieve attainable targets. Performance benchmarks turn competitive knowledge into competitive advantage.
When managers have both visibility and measurability to the most significant gaps between their current state and where they want to be, they can employ an effective case for change and plot the most direct route to improvements.
And rather than guesswork or estimated ROI figures with questionable assumptions, predictive analytics built on benchmarks use real data to provide confidence in calculating pro forma business outcomes and setting realistic goals. The knowledge of what has worked for similar companies lowers risk and accelerates time to value.
Dashboards are a top delivery tool to get the right information to the right person at the right time.
Driving improvements to prospect and customer engagement, campaign results, offer conversions, lead management, brand reach, operational efficiency and financial results starts by bringing real-time visibility to the most influential metrics.
Dashboards rated as ineffective were described as all show and no go. They were visually appealing but failed to gain user adoption because they didn't display anything that helped the employee improve performance.
On a better note, dashboards rated as effective were less about displaying content and more about making the information actionable.
For example, to make key performance indicators (KPIs) more objective and meaningful, show them alongside industry benchmarks.
Predictive analytics convert static data to forward looking information such as next best campaign flight, next best offer or next best action. They are also extremely helpful for What-If modeling and predictive scenario planning.
One type of predictive dashboard that we routinely implement with clients is our Predictive Pyramid. It shows how changes anywhere in the hierarchy cascade and impact other performance measures. It's helpful in determining where to invest your limited time to achieve the biggest uplift.
Many marketers were early adopters in AI and gained both competitive advantages and remarkable ROI. However, AI for marketers is no longer in the early days. We crossed that chasm and any group not using AI today is clearly substituting labor for technology.
The question for leaders standing on the sidelines is not if AI will impact their business, but how and when.
AI creates insights that improve performance objectives. Its algorithms can sift through large volumes of campaign and lead data and make recommendations that improve conversions.
Popular MAPs such as Adobe and Salesforce Marketing Cloud as well as market leading CRM systems such as Microsoft Dynamics 365 and Salesforce Sales Cloud have removed technical barriers with simpler tools. They use web services such as Azure Machine Learning and Salesforce Einstein to put AI applications in the hands of non-technical marketers.
AI elevates data from an unused byproduct to an information asset. Data is the fuel, AI is the engine, and actionable insights are the destination.
The Point is This
Most organizations are data rich but information poor. They understand the value of data but struggle to transform it into actionable intelligence that improves revenue performance.
The Johnny Grow Marketing Analytics Framework can rid that struggle. It was built from research and has been refined over nearly two decades.
And implementing advanced information reporting need not be a daunting task.
Not every type of decision support tool is needed to improve performance or achieve Best-in-Class performance.
Many of the steps in our growth Marketing Analytics Framework can be pursued individually and incrementally. The most important thing is to get started and make continuous improvements.
The research and our experience show that even small business intelligence improvements deliver significant and sustained financial benefits.