Marketing Analytics Consulting Insights
I’ve been doing marketing analytics consulting for more than two decades and will use this post to distill my experience into what I believe are the four most influential insights to make these projects wildly successful.
4 High Impact Marketing Analytics Consultant Insights
Start with a Data-Driven Marketing Culture
Every good marketing business intelligence program starts with a single question. Most marketers, IT professionals and MarTech consultants think the question is "how do I best implement a marketing business intelligence program?" But that's not the right question.
The first question isn't how, it's why.
Before deploying business intelligence (BI) or analytics tools, you should first answer the question, 'why should I implement this technology?' Why invest the time and money? How will this change marketing behaviors, customer relationships and company profitability? Because if staff don't apply the technology to do these things you don't need to consider it further.
Even great analysis tools will fail if the company culture does not promote data-driven and fact-based decision making. Sounds logical, right? But the norm for most companies is to make intuitive, subjective and gut-based decisions and unless management is prepared to change that culture, the technology will be under-utilized and deliver a disappointing payback.
But for those marketing leaders committed to a combination of culture and technology to improve business performance and customer relationships, the tools provide the data-driven, fact-based information to make timely decisions that aid dramatically improved marketing conversions and customer experiences.
Successful MarTech is never implemented in a vacuum. To achieve lasting value, it must be aligned with specific use cases and measurable business outcomes.
As a marketing analytics consultant I ensure my clients start with use cases. Many use cases are trivial, so I also help them surface those that deliver the highest impact.
To cut to the chase, below are four use cases that consistently deliver significant and sustained payback.
A) Increase Marketing Conversions
BI can identify the most effective campaign component assemblies. The technology applies multivariate propensity models to show the combination of offers, content, channels, and call to actions by customer type or target audience to optimize lead acquisitions, lead conversions and sales pipeline growth.
Using analytical models that show what engagement mix (i.e., flight, offer, call to action, channel) delivered at each state of the buyer journey and for each buyer persona consistently and immediately increases lead acquisition rates by double digits.
AI can take it a step further to identify the right offer for right audience on the right channel and the right time, and drive impressive precision marketing campaign results.
B) Decrease Cost Per Lead
As you acquire more leads the cost per lead goes up. That is, unless you implement proactive measures.
For example, in B2B industries, new sales lead acquisitions follow a bell curve in terms of buyer readiness. About 20-25% are sales-ready when received (and immediately distributed to the salesforce), about 45-55% are not sales-ready when received and about 25-30% of new leads are not sales-ready when received and never will be.
That middle tier offers the biggest upside. That's because about 45-65% of this group will eventually become sales-ready over about 10 to 18 months IF they are properly nurtured. Applying a nurture marketing campaign to convert these leads over time will double the total lead acquisitions and cut the cost per lead in half.
C) Improve Marketing ROI
A good marketing analytics consultant keeps ROI front and center. Fortunately, the right BI tools make it a lot easier.
The starting point is to apply the tools in a two-step sequence. First, use them to measure and improve marketing conversions. Then use them to improve campaign portfolio optimization by shifting your limited budget from lower to higher performing campaigns in near real-time.
When you can configure these tools to connect data, insights, actions and outcomes, you will have a visual road map that identifies what outcomes matter most and need to be pursued first. You will also be able to see calculated budget figures and forecasted ROI for each campaign or investment.
D) Grow Marketing-sourced Revenue
It's no secret that marketers measured by marketing activities don't carry the same weight among the C-suite as marketers measured by their revenue contribution to the company.
Revenue marketers get a seat at the executive table because they are accountable for revenue. A few of the BI tools to help these marketers drive the company's most important goal include revenue engineering, strategic pricing (i.e., price elasticity models), white space mapping and process automation that drives sales and marketing alignment.
Apply Marketing Benchmarks
Marketing benchmarks show what good looks like. They bring context to performance measures.
For example, if your nurture marketing conversion rate is 3 percent per month, is that good? Well, not if the average for your industry is 5.5 percent. And when multiplied by the large volume of sales leads this would result a big deviation that would otherwise go unnoticed and unresolved.
Marketing benchmarks show a relative comparison of where the organizations stands and most needs to improve. They also show the under-performing areas that can generally deliver the fastest and biggest uplift.
Focus on the 3 Highest Impact Tools
BI tools are needed to convert data from a raw material to a finished product of information or insight. That's when data becomes your most valuable asset.
There is no shortage of available tools. But our marketing analytics consulting experience has clearly shown that 3 types of tools deliver fast and lasting value.
A. Marketing Dashboards
To a first-time observer most CRM or marketing dashboards looks good. But if good looks were the factors for success my first marriage would have made it, and marketing dashboards would get much more utilization. Research shows that dashboards achieve 30 percent utilization following deployment, but within 3 weeks that utilization falls to 9 percent. Over time it falls further. The decline is due to dashboards not providing real help to users.
Fortunately, the challenge can be proactively remedied. For example, we know information must advance from being merely interesting to inducing action for dashboards to be effective. We also know the eight methods to make data actionable include the following:
- Focus on fewer, higher impact key performance indicators (KPI)
- Make the most important KPIs highly visual and prominently displayed
- Align KPIs with company financial outcomes
- Show KPIs alongside budgets or industry benchmarks for context
- Shift from lagging to leading KPIs
- Allow the data to be interrogated, manipulated, and used for predictive analytics
- Link the data findings to recommended actions such as a Playbook, and
- Deliver real-time variance notifications to permit course corrections before performance problems exacerbate. Follow up the variances with detailed information reporting that identifies the causes and linkage among performance problems to accelerate their resolutions.
B. Predictive Analytics
A recurring pattern among marketers unable to accelerate their performance results is that they don't know what actions deliver the biggest financial returns, so they pursue what they know instead of what is most effective.
Predictive analytics such as the below pro forma pyramid show how lower levels of execution impact top line company results. This allows marketers to compare alternatives and know exactly where they should invest their limited time and budget.
The pro forma pyramid is useful because no marketing program lives in isolation. Each has cascading effects that impact other areas and those impacts must be considered when making tradeoffs. This holistic visualization is helpful in determining the programs that can be accomplished in the least time and cost and deliver the biggest financial results.
3. Artificial Intelligence
Marketing automation systems hold high volumes of leads and CRM systems hold a treasure trove of campaign data. But there is such a thing as too much data, or at least more data than can be manually processed.
AI is the tool to sift through all that data and deliver precision insights exactly when they can be applied. It correlates data with desired outcomes and makes recommendations to achieve those results.
When marketers integrate AI into their daily work routines, they become far more efficient and effective. For example, staff can apply AI to surface the leads being neglected, the campaigns that need attention, the customers at risk for churn, and the social conversations that may impact the company brand.
Marketers can use AI to improve lead conversions, customer experiences, campaign results and scale the marketing operation.
CRM applications such as Microsoft Dynamics and Salesforce have lowered technical barriers with simpler AI tools, such as Azure Machine Learning and Salesforce Einstein. This puts the technology into the hands of marketing managers and power users.
AI is no longer in the early days. We crossed that chasm and any company not using this technology is clearly substituting labor for technology.
Remember This
BI tools are effective at churning through large volumes of data and delivering insights and recommendations that are just not possible otherwise. But to achieve these types of insights at scale, you need to start with a data-driven culture, the right use cases, and the right mix of decision support tools.
Then BI can alert marketers of performance deviations in near real-time, allowing them to intervene with course corrections that head off poor performance before it happens.
When BI is effectively used to get the right information to the right person at the right time, even small improvements are shown to deliver significant financial impact.