Analytics powered marketing function is leaner, meaner & better equipped for RoI-driven decision making

Marketing Analytics unlocks optimization & rationalization

Introduction

The fact that Analytics touches every sphere of business is inevitable, and, given the strides of progress made in terms of evolving business functions to maximize stakeholder value, it is expected to make further inroads.  Marketing, over time, has morphed from its branding-centric role, where the loudest voice in the street grabbed the most eyeballs, to being able to deeply understand consumer preferences and position product with personalized content. With the advent of using data in a learned manner, we have now moved towards deploying analytics into marketing campaign data to drive towards customer acquisition. 

Changing Marketing Data Landscape

Much of the changes that marketers see typically in campaigns have been fueled by the explosion of data, with various performance metrics coming into play as a consequence. Traditional marketing models’ performance measurement was typically through directional metrics, Which gave some semblance of how effective a campaign is.

As more and more businesses move online, with the adoption of e-commerce and the complete end-to-end funnel view of business, it has forced companies to look at data closer. As is with any other data, the foundation principles of how data is to be captured and analyzed remain the same.

Prerequisites For Marketing Analytics:

1. Digital Data Audit - A quick-fire audit to understand the complete marketing data landscape is mapped correctly to achieve the end objective
2. Complete Data Capture - Ensuring that end-to-end data is captured to ensure that we can have complete funnel level analysis tied to the end objective
3. Data Completeness Assurance - All captured data is complete in terms of depth of detail & breadth of data fields available
4. Digital Data Accuracy - Accuracy of all captured data from the standpoint of as-is-captured needs to be ensured, especially if the data captured is in multiple formats

The most important and crucial part of data analytics is getting the right data, sanitizing it into malleable formats that enable a visual representation. Most companies fail in this aspect, primarily for two reasons, i.e, lack of skilled resources and lacking decision-makers who understand analytics from a bird's eye view. 

Digital Data Analysis & Visualization 

Data insights are best derived when as-is data is represented in visually easy to decipher formats, which provides decision making the required clarity to trigger business-changing decisions. With the advent of advanced visualization techniques & tools, the more crucial aspect is painting the picture that best solves the challenge at hand.

Data analysis provides product managers data with an array of data analysis of their products/services that are critical to driving the business. This in turn also has the effect of improving overall company data soundness leading to in a true sense, data-driven-decision making.

Product managers/modern-day marketers typically deploy the below-given type of data analysis in their regular day-to-day tasks, however, the skills required to deploy these solution models are scarce and far too in between.

• Ad Hoc Analysis
• Exception Analysis  
• Root Cause Analysis
• Decision tree analysis 
• Causation & correlation models 
• Statistical confidence 
• Statistical forecasting  

Objectivity when looking at a visual rendering of data can never be understated, or the decision-making process would be exposed to bias that would render the entire exercise muddled in a cesspool of personal opinions.

Automated Monitoring & Anomaly Detection

Data dashboards created to help monitor marketing performance can be enabled even further by connecting these to live data feeds. Connected dashboards in turn act as tolling bells for a marketer to course correct any dip in performance or catch the wave on its ride up, rationalizing cost at one end and improving margins on the other. A judicious mix of data, analytics, and the right tools can go a long way in helping set up a pure-play performance-oriented campaign for marketing managers.

Conclusion

The next wave of data analytics is bound to change the marketing landscape with analytics playing a major role in taking calls that can make or break the marketing intuition of any seasoned marketer. Digital marketing analytics requires skills that are scarce and expensive, which makes it even more of a case for companies to opt to Analytics Advanced Operating Models. Unlocking a disproportionate advantage by deploying Analytics Center of Excellence can help companies jump over the skill/time barrier in a cost-effective manner that looks like a good option.