Marketing Analytics is the measuring, managing, and analyzing of marketing performance to maximize marketing effectiveness and optimize ROI [i]. This allows for increased efficiency and productivity of human resources and capital.
Businesses have expanded into new marketing channels, leveraging new technologies to increase their reach [ii]. This presents an interesting challenge for marketers and business professionals alike – how to consolidate the information from these disconnected data environments to make apple-to-apple comparisons for the sake of making more informed business decisions.
By taking into consideration all marketing efforts across all channels over a length of time, marketers are now able to make a sound decision time and time again. Analytics takes the guesswork out of the evaluation process when investing in new advertising campaigns.
The most impactful marketing analytics systems feature a balanced analytics assortment, one that derives insights when reporting on the past, analyzing the present, and predicting the future.
Organizations at the very minimum should be tracking the following KPI’s/Metrics:
Cost per click
Cost per impression
Cost per conversion
Total campaign spend
Companies should also be monitoring their marketing performance by using Advertising performance and ROI monthly report to understand the impact of your marketing dollars to determine the optimal marketing mix as well as comparing Cost of Customer Acquisition vs CLV (identify customers who are the most profitable and those who are the least)
More data driven organizations have used analytical methodologies such as Marketing-Mix Modeling (MMM) [iii]. This statistical modeling method is used to determine the effectiveness of spending per each marketing channel. The approach can comprehensively assess marketing spending by incorporating other sales drivers and external variables such as seasonality, competitor effects, as well as interaction effects. Although this method requires high-quality sales and marketing data spanning years, it will allow a savvy user to understand the implications of spending decisions.
Analytics savvy organizations will also conduct Reach, Cost, Quality (RCQ) analysis. RCQ is used to bring all different touch points to the same unit of measurement to compare each one’s effectiveness. It is a more flexible method than MMM because when the data is limited, structured judgment can be introduced. While it can consider factors such as the number of targeted customers, cost per unique touch and the quality of each touchpoint engagement, it is unable to capture network and interaction effects as MMM does.
A retail bank turned to marketing analytics to improve fiscal performance [iv]: As the world economy recovered from the 2008 Global recession, a $2.7B (yearly revenue) bank was looking to reassess their marketing mix to become more cost efficient in their marketing spend. Given that 45% of their business was driven by their retail banking arm, they focused on this division in their analysis.
They used a host of analytical tools such Marketing-Mix Modelling, Reach, Cost, Quality assessment to quantify the effect of marketing investments, and to determine the optimal marketing mix. The client was also able to further understand trends within specific industries and geographies, better equipping their employees with marketing information from the ground level to improve top line revenue.
[i] Marketing Analytics - Success Through Analysis. WordStream. Retrieved from here
[ii]Marketing Analytics What it is and why it matters. SAS. Retrieved from here
[iii]Using marketing analytics to drive superior growth. McKinsey. Retrieved from here
[iv]quantzig’s marketing mix optimization helped a prominent retail banking client improve business efficiency by 30%. Quantzig. Retrieved from here